Black Swan Trading: Wer hat Angst vorm Schwarzen Schwan ...

Former investment bank FX trader: Risk management part II

Former investment bank FX trader: Risk management part II
Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful.
If you didn't read the first post you can do so here: risk management part I. You'll need to do so in order to make sense of the topic.
As ever please comment/reply below with questions or feedback and I'll do my best to get back to you.
Part II
  • Letting stops breathe
  • When to change a stop
  • Entering and exiting winning positions
  • Risk:reward ratios
  • Risk-adjusted returns

Letting stops breathe

We talked earlier about giving a position enough room to breathe so it is not stopped out in day-to-day noise.
Let’s consider the chart below and imagine you had a trailing stop. It would be super painful to miss out on the wider move just because you left a stop that was too tight.

Imagine being long and stopped out on a meaningless retracement ... ouch!
One simple technique is simply to look at your chosen chart - let’s say daily bars. And then look at previous trends and use the measuring tool. Those generally look something like this and then you just click and drag to measure.
For example if we wanted to bet on a downtrend on the chart above we might look at the biggest retracement on the previous uptrend. That max drawdown was about 100 pips or just under 1%. So you’d want your stop to be able to withstand at least that.
If market conditions have changed - for example if CVIX has risen - and daily ranges are now higher you should incorporate that. If you know a big event is coming up you might think about that, too. The human brain is a remarkable tool and the power of the eye-ball method is not to be dismissed. This is how most discretionary traders do it.
There are also more analytical approaches.
Some look at the Average True Range (ATR). This attempts to capture the volatility of a pair, typically averaged over a number of sessions. It looks at three separate measures and takes the largest reading. Think of this as a moving average of how much a pair moves.
For example, below shows the daily move in EURUSD was around 60 pips before spiking to 140 pips in March. Conditions were clearly far more volatile in March. Accordingly, you would need to leave your stop further away in March and take a correspondingly smaller position size.

ATR is available on pretty much all charting systems
Professional traders tend to use standard deviation as a measure of volatility instead of ATR. There are advantages and disadvantages to both. Averages are useful but can be misleading when regimes switch (see above chart).
Once you have chosen a measure of volatility, stop distance can then be back-tested and optimised. For example does 2x ATR work best or 5x ATR for a given style and time horizon?
Discretionary traders may still eye-ball the ATR or standard deviation to get a feeling for how it has changed over time and what ‘normal’ feels like for a chosen study period - daily, weekly, monthly etc.

Reasons to change a stop

As a general rule you should be disciplined and not change your stops. Remember - losers average losers. This is really hard at first and we’re going to look at that in more detail later.
There are some good reasons to modify stops but they are rare.
One reason is if another risk management process demands you stop trading and close positions. We’ll look at this later. In that case just close out your positions at market and take the loss/gains as they are.
Another is event risk. If you have some big upcoming data like Non Farm Payrolls that you know can move the market +/- 150 pips and you have no edge going into the release then many traders will take off or scale down their positions. They’ll go back into the positions when the data is out and the market has quietened down after fifteen minutes or so. This is a matter of some debate - many traders consider it a coin toss and argue you win some and lose some and it all averages out.
Trailing stops can also be used to ‘lock in’ profits. We looked at those before. As the trade moves in your favour (say up if you are long) the stop loss ratchets with it. This means you may well end up ‘stopping out’ at a profit - as per the below example.

The mighty trailing stop loss order
It is perfectly reasonable to have your stop loss move in the direction of PNL. This is not exposing you to more risk than you originally were comfortable with. It is taking less and less risk as the trade moves in your favour. Trend-followers in particular love trailing stops.
One final question traders ask is what they should do if they get stopped out but still like the trade. Should they try the same trade again a day later for the same reasons? Nope. Look for a different trade rather than getting emotionally wed to the original idea.
Let’s say a particular stock looked cheap based on valuation metrics yesterday, you bought, it went down and you got stopped out. Well, it is going to look even better on those same metrics today. Maybe the market just doesn’t respect value at the moment and is driven by momentum. Wait it out.
Otherwise, why even have a stop in the first place?

Entering and exiting winning positions

Take profits are the opposite of stop losses. They are also resting orders, left with the broker, to automatically close your position if it reaches a certain price.
Imagine I’m long EURUSD at 1.1250. If it hits a previous high of 1.1400 (150 pips higher) I will leave a sell order to take profit and close the position.
The rookie mistake on take profits is to take profit too early. One should start from the assumption that you will win on no more than half of your trades. Therefore you will need to ensure that you win more on the ones that work than you lose on those that don’t.

Sad to say but incredibly common: retail traders often take profits way too early
This is going to be the exact opposite of what your emotions want you to do. We are going to look at that in the Psychology of Trading chapter.
Remember: let winners run. Just like stops you need to know in advance the level where you will close out at a profit. Then let the trade happen. Don’t override yourself and let emotions force you to take a small profit. A classic mistake to avoid.
The trader puts on a trade and it almost stops out before rebounding. As soon as it is slightly in the money they spook and cut out, instead of letting it run to their original take profit. Do not do this.

Entering positions with limit orders

That covers exiting a position but how about getting into one?
Take profits can also be left speculatively to enter a position. Sometimes referred to as “bids” (buy orders) or “offers” (sell orders). Imagine the price is 1.1250 and the recent low is 1.1205.
You might wish to leave a bid around 1.2010 to enter a long position, if the market reaches that price. This way you don’t need to sit at the computer and wait.
Again, typically traders will use tech analysis to identify attractive levels. Again - other traders will cluster with your orders. Just like the stop loss we need to bake that in.
So this time if we know everyone is going to buy around the recent low of 1.1205 we might leave the take profit bit a little bit above there at 1.1210 to ensure it gets done. Sure it costs 5 more pips but how mad would you be if the low was 1.1207 and then it rallied a hundred points and you didn’t have the trade on?!
There are two more methods that traders often use for entering a position.
Scaling in is one such technique. Let’s imagine that you think we are in a long-term bulltrend for AUDUSD but experiencing a brief retracement. You want to take a total position of 500,000 AUD and don’t have a strong view on the current price action.
You might therefore leave a series of five bids of 100,000. As the price moves lower each one gets hit. The nice thing about scaling in is it reduces pressure on you to pick the perfect level. Of course the risk is that not all your orders get hit before the price moves higher and you have to trade at-market.
Pyramiding is the second technique. Pyramiding is for take profits what a trailing stop loss is to regular stops. It is especially common for momentum traders.

Pyramiding into a position means buying more as it goes in your favour
Again let’s imagine we’re bullish AUDUSD and want to take a position of 500,000 AUD.
Here we add 100,000 when our first signal is reached. Then we add subsequent clips of 100,000 when the trade moves in our favour. We are waiting for confirmation that the move is correct.
Obviously this is quite nice as we humans love trading when it goes in our direction. However, the drawback is obvious: we haven’t had the full amount of risk on from the start of the trend.
You can see the attractions and drawbacks of both approaches. It is best to experiment and choose techniques that work for your own personal psychology as these will be the easiest for you to stick with and build a disciplined process around.

Risk:reward and win ratios

Be extremely skeptical of people who claim to win on 80% of trades. Most traders will win on roughly 50% of trades and lose on 50% of trades. This is why risk management is so important!
Once you start keeping a trading journal you’ll be able to see how the win/loss ratio looks for you. Until then, assume you’re typical and that every other trade will lose money.
If that is the case then you need to be sure you make more on the wins than you lose on the losses. You can see the effect of this below.

A combination of win % and risk:reward ratio determine if you are profitable
A typical rule of thumb is that a ratio of 1:3 works well for most traders.
That is, if you are prepared to risk 100 pips on your stop you should be setting a take profit at a level that would return you 300 pips.
One needn’t be religious about these numbers - 11 pips and 28 pips would be perfectly fine - but they are a guideline.
Again - you should still use technical analysis to find meaningful chart levels for both the stop and take profit. Don’t just blindly take your stop distance and do 3x the pips on the other side as your take profit. Use the ratio to set approximate targets and then look for a relevant resistance or support level in that kind of region.

Risk-adjusted returns

Not all returns are equal. Suppose you are examining the track record of two traders. Now, both have produced a return of 14% over the year. Not bad!
The first trader, however, made hundreds of small bets throughout the year and his cumulative PNL looked like the left image below.
The second trader made just one bet — he sold CADJPY at the start of the year — and his PNL looked like the right image below with lots of large drawdowns and volatility.
Would you rather have the first trading record or the second?
If you were investing money and betting on who would do well next year which would you choose? Of course all sensible people would choose the first trader. Yet if you look only at returns one cannot distinguish between the two. Both are up 14% at that point in time. This is where the Sharpe ratio helps .
A high Sharpe ratio indicates that a portfolio has better risk-adjusted performance. One cannot sensibly compare returns without considering the risk taken to earn that return.
If I can earn 80% of the return of another investor at only 50% of the risk then a rational investor should simply leverage me at 2x and enjoy 160% of the return at the same level of risk.
This is very important in the context of Execution Advisor algorithms (EAs) that are popular in the retail community. You must evaluate historic performance by its risk-adjusted return — not just the nominal return. Incidentally look at the Sharpe ratio of ones that have been live for a year or more ...
Otherwise an EA developer could produce two EAs: the first simply buys at 1000:1 leverage on January 1st ; and the second sells in the same manner. At the end of the year, one of them will be discarded and the other will look incredible. Its risk-adjusted return, however, would be abysmal and the odds of repeated success are similarly poor.

Sharpe ratio

The Sharpe ratio works like this:
  • It takes the average returns of your strategy;
  • It deducts from these the risk-free rate of return i.e. the rate anyone could have got by investing in US government bonds with very little risk;
  • It then divides this total return by its own volatility - the more smooth the return the higher and better the Sharpe, the more volatile the lower and worse the Sharpe.
For example, say the return last year was 15% with a volatility of 10% and US bonds are trading at 2%. That gives (15-2)/10 or a Sharpe ratio of 1.3. As a rule of thumb a Sharpe ratio of above 0.5 would be considered decent for a discretionary retail trader. Above 1 is excellent.
You don’t really need to know how to calculate Sharpe ratios. Good trading software will do this for you. It will either be available in the system by default or you can add a plug-in.

VAR

VAR is another useful measure to help with drawdowns. It stands for Value at Risk. Normally people will use 99% VAR (conservative) or 95% VAR (aggressive). Let’s say you’re long EURUSD and using 95% VAR. The system will look at the historic movement of EURUSD. It might spit out a number of -1.2%.

A 5% VAR of -1.2% tells you you should expect to lose 1.2% on 5% of days, whilst 95% of days should be better than that
This means it is expected that on 5 days out of 100 (hence the 95%) the portfolio will lose 1.2% or more. This can help you manage your capital by taking appropriately sized positions. Typically you would look at VAR across your portfolio of trades rather than trade by trade.
Sharpe ratios and VAR don’t give you the whole picture, though. Legendary fund manager, Howard Marks of Oaktree, notes that, while tools like VAR and Sharpe ratios are helpful and absolutely necessary, the best investors will also overlay their own judgment.
Investors can calculate risk metrics like VaR and Sharpe ratios (we use them at Oaktree; they’re the best tools we have), but they shouldn’t put too much faith in them. The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.Howard Marks of Oaktree Capital
What he’s saying is don’t misplace your common sense. Do use these tools as they are helpful. However, you cannot fully rely on them. Both assume a normal distribution of returns. Whereas in real life you get “black swans” - events that should supposedly happen only once every thousand years but which actually seem to happen fairly often.
These outlier events are often referred to as “tail risk”. Don’t make the mistake of saying “well, the model said…” - overlay what the model is telling you with your own common sense and good judgment.

Coming up in part III

Available here
Squeezes and other risks
Market positioning
Bet correlation
Crap trades, timeouts and monthly limits

***
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
submitted by getmrmarket to Forex [link] [comments]

How do you hedge your overnight naked positions?

This question is only for Swing traders and Positional traders so please refrain from answering if you are responding from a day trader point of view.
A wise trader will always hedge his trades to protect himself from unforeseen circumstances like a Black Swan.
Let's say I was short GBPUSD on 5th June at 1.2670 and I think due to a major news breaking out over the weekend, my short position will sky rocket and open at 500 or 1000 pips above my entry price not even triggering my Stop. How do I protect my self in such a scenario or how do swing/positional traders buy insurance? Please don't say buy options on CME. Any alternative apart from CME like doing something in Spot fx it self? Would love to read answers from seasoned forex traders who are profitable and are already doing this.
submitted by CosmoCrush to Forex [link] [comments]

Hibiscus Petroleum Berhad (5199.KL)


https://preview.redd.it/gp18bjnlabr41.jpg?width=768&format=pjpg&auto=webp&s=6054e7f52e8d52da403016139ae43e0e799abf15
Download PDF of this article here: https://docdro.id/6eLgUPo
In light of the recent fall in oil prices due to the Saudi-Russian dispute and dampening demand for oil due to the lockdowns implemented globally, O&G stocks have taken a severe beating, falling approximately 50% from their highs at the beginning of the year. Not spared from this onslaught is Hibiscus Petroleum Berhad (Hibiscus), a listed oil and gas (O&G) exploration and production (E&P) company.
Why invest in O&G stocks in this particularly uncertain period? For one, valuations of these stocks have fallen to multi-year lows, bringing the potential ROI on these stocks to attractive levels. Oil prices are cyclical, and are bound to return to the mean given a sufficiently long time horizon. The trick is to find those companies who can survive through this downturn and emerge into “normal” profitability once oil prices rebound.
In this article, I will explore the upsides and downsides of investing in Hibiscus. I will do my best to cater this report to newcomers to the O&G industry – rather than address exclusively experts and veterans of the O&G sector. As an equity analyst, I aim to provide a view on the company primarily, and will generally refrain from providing macro views on oil or opinions about secular trends of the sector. I hope you enjoy reading it!
Stock code: 5199.KL
Stock name: Hibiscus Petroleum Berhad
Financial information and financial reports: https://www.malaysiastock.biz/Corporate-Infomation.aspx?securityCode=5199
Company website: https://www.hibiscuspetroleum.com/

Company Snapshot

Hibiscus Petroleum Berhad (5199.KL) is an oil and gas (O&G) upstream exploration and production (E&P) company located in Malaysia. As an E&P company, their business can be basically described as:
· looking for oil,
· drawing it out of the ground, and
· selling it on global oil markets.
This means Hibiscus’s profits are particularly exposed to fluctuating oil prices. With oil prices falling to sub-$30 from about $60 at the beginning of the year, Hibiscus’s stock price has also fallen by about 50% YTD – from around RM 1.00 to RM 0.45 (as of 5 April 2020).
https://preview.redd.it/3dqc4jraabr41.png?width=641&format=png&auto=webp&s=7ba0e8614c4e9d781edfc670016a874b90560684
https://preview.redd.it/lvdkrf0cabr41.png?width=356&format=png&auto=webp&s=46f250a713887b06986932fa475dc59c7c28582e
While the company is domiciled in Malaysia, its two main oil producing fields are located in both Malaysia and the UK. The Malaysian oil field is commonly referred to as the North Sabah field, while the UK oil field is commonly referred to as the Anasuria oil field. Hibiscus has licenses to other oil fields in different parts of the world, notably the Marigold/Sunflower oil fields in the UK and the VIC cluster in Australia, but its revenues and profits mainly stem from the former two oil producing fields.
Given that it’s a small player and has only two primary producing oil fields, it’s not surprising that Hibiscus sells its oil to a concentrated pool of customers, with 2 of them representing 80% of its revenues (i.e. Petronas and BP). Fortunately, both these customers are oil supermajors, and are unlikely to default on their obligations despite low oil prices.
At RM 0.45 per share, the market capitalization is RM 714.7m and it has a trailing PE ratio of about 5x. It doesn’t carry any debt, and it hasn’t paid a dividend in its listing history. The MD, Mr. Kenneth Gerard Pereira, owns about 10% of the company’s outstanding shares.

Reserves (Total recoverable oil) & Production (bbl/day)

To begin analyzing the company, it’s necessary to understand a little of the industry jargon. We’ll start with Reserves and Production.
In general, there are three types of categories for a company’s recoverable oil volumes – Reserves, Contingent Resources and Prospective Resources. Reserves are those oil fields which are “commercial”, which is defined as below:
As defined by the SPE PRMS, Reserves are “… quantities of petroleum anticipated to be commercially recoverable by application of development projects to known accumulations from a given date forward under defined conditions.” Therefore, Reserves must be discovered (by drilling, recoverable (with current technology), remaining in the subsurface (at the effective date of the evaluation) and “commercial” based on the development project proposed.)
Note that Reserves are associated with development projects. To be considered as “commercial”, there must be a firm intention to proceed with the project in a reasonable time frame (typically 5 years, and such intention must be based upon all of the following criteria:)
- A reasonable assessment of the future economics of the development project meeting defined investment and operating criteria; - A reasonable expectation that there will be a market for all or at least the expected sales quantities of production required to justify development; - Evidence that the necessary production and transportation facilities are available or can be made available; and - Evidence that legal, contractual, environmental and other social and economic concerns will allow for the actual implementation of the recovery project being evaluated.
Contingent Resources and Prospective Resources are further defined as below:
- Contingent Resources: potentially recoverable volumes associated with a development plan that targets discovered volumes but is not (yet commercial (as defined above); and) - Prospective Resources: potentially recoverable volumes associated with a development plan that targets as yet undiscovered volumes.
In the industry lingo, we generally refer to Reserves as ‘P’ and Contingent Resources as ‘C’. These ‘P’ and ‘C’ resources can be further categorized into 1P/2P/3P resources and 1C/2C/3C resources, each referring to a low/medium/high estimate of the company’s potential recoverable oil volumes:
- Low/1C/1P estimate: there should be reasonable certainty that volumes actually recovered will equal or exceed the estimate; - Best/2C/2P estimate: there should be an equal likelihood of the actual volumes of petroleum being larger or smaller than the estimate; and - High/3C/3P estimate: there is a low probability that the estimate will be exceeded.
Hence in the E&P industry, it is easy to see why most investors and analysts refer to the 2P estimate as the best estimate for a company’s actual recoverable oil volumes. This is because 2P reserves (‘2P’ referring to ‘Proved and Probable’) are a middle estimate of the recoverable oil volumes legally recognized as “commercial”.
However, there’s nothing stopping you from including 2C resources (riskier) or utilizing 1P resources (conservative) as your estimate for total recoverable oil volumes, depending on your risk appetite. In this instance, the company has provided a snapshot of its 2P and 2C resources in its analyst presentation:
https://preview.redd.it/o8qejdyc8br41.png?width=710&format=png&auto=webp&s=b3ab9be8f83badf0206adc982feda3a558d43e78
Basically, what the company is saying here is that by 2021, it will have classified as 2P reserves at least 23.7 million bbl from its Anasuria field and 20.5 million bbl from its North Sabah field – for total 2P reserves of 44.2 million bbl (we are ignoring the Australian VIC cluster as it is only estimated to reach first oil by 2022).
Furthermore, the company is stating that they have discovered (but not yet legally classified as “commercial”) a further 71 million bbl of oil from both the Anasuria and North Sabah fields, as well as the Marigold/Sunflower fields. If we include these 2C resources, the total potential recoverable oil volumes could exceed 100 million bbl.
In this report, we shall explore all valuation scenarios giving consideration to both 2P and 2C resources.
https://preview.redd.it/gk54qplf8br41.png?width=489&format=png&auto=webp&s=c905b7a6328432218b5b9dfd53cc9ef1390bd604
The company further targets a 2021 production rate of 20,000 bbl (LTM: 8,000 bbl), which includes 5,000 bbl from its Anasuria field (LTM: 2,500 bbl) and 7,000 bbl from its North Sabah field (LTM: 5,300 bbl).
This is a substantial increase in forecasted production from both existing and prospective oil fields. If it materializes, annual production rate could be as high as 7,300 mmbbl, and 2021 revenues (given FY20 USD/bbl of $60) could exceed RM 1.5 billion (FY20: RM 988 million).
However, this targeted forecast is quite a stretch from current production levels. Nevertheless, we shall consider all provided information in estimating a valuation for Hibiscus.
To understand Hibiscus’s oil production capacity and forecast its revenues and profits, we need to have a better appreciation of the performance of its two main cash-generating assets – the North Sabah field and the Anasuria field.

North Sabah oil field
https://preview.redd.it/62nssexj8br41.png?width=1003&format=png&auto=webp&s=cd78f86d51165fb9a93015e49496f7f98dad64dd
Hibiscus owns a 50% interest in the North Sabah field together with its partner Petronas, and has production rights over the field up to year 2040. The asset contains 4 oil fields, namely the St Joseph field, South Furious field, SF 30 field and Barton field.
For the sake of brevity, we shall not delve deep into the operational aspects of the fields or the contractual nature of its production sharing contract (PSC). We’ll just focus on the factors which relate to its financial performance. These are:
· Average uptime
· Total oil sold
· Average realized oil price
· Average OPEX per bbl
With regards to average uptime, we can see that the company maintains relative high facility availability, exceeding 90% uptime in all quarters of the LTM with exception of Jul-Sep 2019. The dip in average uptime was due to production enhancement projects and maintenance activities undertaken to improve the production capacity of the St Joseph and SF30 oil fields.
Hence, we can conclude that management has a good handle on operational performance. It also implies that there is little room for further improvement in production resulting from increased uptime.
As North Sabah is under a production sharing contract (PSC), there is a distinction between gross oil production and net oil production. The former relates to total oil drawn out of the ground, whereas the latter refers to Hibiscus’s share of oil production after taxes, royalties and expenses are accounted for. In this case, we want to pay attention to net oil production, not gross.
We can arrive at Hibiscus’s total oil sold for the last twelve months (LTM) by adding up the total oil sold for each of the last 4 quarters. Summing up the figures yields total oil sold for the LTM of approximately 2,075,305 bbl.
Then, we can arrive at an average realized oil price over the LTM by averaging the average realized oil price for the last 4 quarters, giving us an average realized oil price over the LTM of USD 68.57/bbl. We can do the same for average OPEX per bbl, giving us an average OPEX per bbl over the LTM of USD 13.23/bbl.
Thus, we can sum up the above financial performance of the North Sabah field with the following figures:
· Total oil sold: 2,075,305 bbl
· Average realized oil price: USD 68.57/bbl
· Average OPEX per bbl: USD 13.23/bbl

Anasuria oil field
https://preview.redd.it/586u4kfo8br41.png?width=1038&format=png&auto=webp&s=7580fc7f7df7e948754d025745a5cf47d4393c0f
Doing the same exercise as above for the Anasuria field, we arrive at the following financial performance for the Anasuria field:
· Total oil sold: 1,073,304 bbl
· Average realized oil price: USD 63.57/bbl
· Average OPEX per bbl: USD 23.22/bbl
As gas production is relatively immaterial, and to be conservative, we shall only consider the crude oil production from the Anasuria field in forecasting revenues.

Valuation (Method 1)

Putting the figures from both oil fields together, we get the following data:
https://preview.redd.it/7y6064dq8br41.png?width=700&format=png&auto=webp&s=2a4120563a011cf61fc6090e1cd5932602599dc2
Given that we have determined LTM EBITDA of RM 632m, the next step would be to subtract ITDA (interest, tax, depreciation & amortization) from it to obtain estimated LTM Net Profit. Using FY2020’s ITDA of approximately RM 318m as a guideline, we arrive at an estimated LTM Net Profit of RM 314m (FY20: 230m). Given the current market capitalization of RM 714.7m, this implies a trailing LTM PE of 2.3x.
Performing a sensitivity analysis given different oil prices, we arrive at the following net profit table for the company under different oil price scenarios, assuming oil production rate and ITDA remain constant:
https://preview.redd.it/xixge5sr8br41.png?width=433&format=png&auto=webp&s=288a00f6e5088d01936f0217ae7798d2cfcf11f2
From the above exercise, it becomes apparent that Hibiscus has a breakeven oil price of about USD 41.8863/bbl, and has a lot of operating leverage given the exponential rate of increase in its Net Profit with each consequent increase in oil prices.
Considering that the oil production rate (EBITDA) is likely to increase faster than ITDA’s proportion to revenues (fixed costs), at an implied PE of 4.33x, it seems likely that an investment in Hibiscus will be profitable over the next 10 years (with the assumption that oil prices will revert to the mean in the long-term).

Valuation (Method 2)

Of course, there are a lot of assumptions behind the above method of valuation. Hence, it would be prudent to perform multiple methods of valuation and compare the figures to one another.
As opposed to the profit/loss assessment in Valuation (Method 1), another way of performing a valuation would be to estimate its balance sheet value, i.e. total revenues from 2P Reserves, and assign a reasonable margin to it.
https://preview.redd.it/o2eiss6u8br41.png?width=710&format=png&auto=webp&s=03960cce698d9cedb076f3d5f571b3c59d908fa8
From the above, we understand that Hibiscus’s 2P reserves from the North Sabah and Anasuria fields alone are approximately 44.2 mmbbl (we ignore contribution from Australia’s VIC cluster as it hasn’t been developed yet).
Doing a similar sensitivity analysis of different oil prices as above, we arrive at the following estimated total revenues and accumulated net profit:
https://preview.redd.it/h8hubrmw8br41.png?width=450&format=png&auto=webp&s=6d23f0f9c3dafda89e758b815072ba335467f33e
Let’s assume that the above average of RM 9.68 billion in total realizable revenues from current 2P reserves holds true. If we assign a conservative Net Profit margin of 15% (FY20: 23%; past 5 years average: 16%), we arrive at estimated accumulated Net Profit from 2P Reserves of RM 1.452 billion. Given the current market capitalization of RM 714 million, we might be able to say that the equity is worth about twice the current share price.
However, it is understandable that some readers might feel that the figures used in the above estimate (e.g. net profit margin of 15%) were randomly plucked from the sky. So how do we reconcile them with figures from the financial statements? Fortunately, there appears to be a way to do just that.
Intangible Assets
I refer you to a figure in the financial statements which provides a shortcut to the valuation of 2P Reserves. This is the carrying value of Intangible Assets on the Balance Sheet.
As of 2QFY21, that amount was RM 1,468,860,000 (i.e. RM 1.468 billion).
https://preview.redd.it/hse8ttb09br41.png?width=881&format=png&auto=webp&s=82e48b5961c905fe9273cb6346368de60202ebec
Quite coincidentally, one might observe that this figure is dangerously close to the estimated accumulated Net Profit from 2P Reserves of RM 1.452 billion we calculated earlier. But why would this amount matter at all?
To answer that, I refer you to the notes of the Annual Report FY20 (AR20). On page 148 of the AR20, we find the following two paragraphs:
E&E assets comprise of rights and concession and conventional studies. Following the acquisition of a concession right to explore a licensed area, the costs incurred such as geological and geophysical surveys, drilling, commercial appraisal costs and other directly attributable costs of exploration and appraisal including technical and administrative costs, are capitalised as conventional studies, presented as intangible assets.
E&E assets are assessed for impairment when facts and circumstances suggest that the carrying amount of an E&E asset may exceed its recoverable amount. The Group will allocate E&E assets to cash generating unit (“CGU”s or groups of CGUs for the purpose of assessing such assets for impairment. Each CGU or group of units to which an E&E asset is allocated will not be larger than an operating segment as disclosed in Note 39 to the financial statements.)
Hence, we can determine that firstly, the intangible asset value represents capitalized costs of acquisition of the oil fields, including technical exploration costs and costs of acquiring the relevant licenses. Secondly, an impairment review will be carried out when “the carrying amount of an E&E asset may exceed its recoverable amount”, with E&E assets being allocated to “cash generating units” (CGU) for the purposes of assessment.
On page 169 of the AR20, we find the following:
Carrying amounts of the Group’s intangible assets, oil and gas assets and FPSO are reviewed for possible impairment annually including any indicators of impairment. For the purpose of assessing impairment, assets are grouped at the lowest level CGUs for which there is a separately identifiable cash flow available. These CGUs are based on operating areas, represented by the 2011 North Sabah EOR PSC (“North Sabah”, the Anasuria Cluster, the Marigold and Sunflower fields, the VIC/P57 exploration permit (“VIC/P57”) and the VIC/L31 production license (“VIC/L31”).)
So apparently, the CGUs that have been assigned refer to the respective oil producing fields, two of which include the North Sabah field and the Anasuria field. In order to perform the impairment review, estimates of future cash flow will be made by management to assess the “recoverable amount” (as described above), subject to assumptions and an appropriate discount rate.
Hence, what we can gather up to now is that management will estimate future recoverable cash flows from a CGU (i.e. the North Sabah and Anasuria oil fields), compare that to their carrying value, and perform an impairment if their future recoverable cash flows are less than their carrying value. In other words, if estimated accumulated profits from the North Sabah and Anasuria oil fields are less than their carrying value, an impairment is required.
So where do we find the carrying values for the North Sabah and Anasuria oil fields? Further down on page 184 in the AR20, we see the following:
Included in rights and concession are the carrying amounts of producing field licenses in the Anasuria Cluster amounting to RM668,211,518 (2018: RM687,664,530, producing field licenses in North Sabah amounting to RM471,031,008 (2018: RM414,333,116))
Hence, we can determine that the carrying values for the North Sabah and Anasuria oil fields are RM 471m and RM 668m respectively. But where do we find the future recoverable cash flows of the fields as estimated by management, and what are the assumptions used in that calculation?
Fortunately, we find just that on page 185:
17 INTANGIBLE ASSETS (CONTINUED)
(a Anasuria Cluster)
The Directors have concluded that there is no impairment indicator for Anasuria Cluster during the current financial year. In the previous financial year, due to uncertainties in crude oil prices, the Group has assessed the recoverable amount of the intangible assets, oil and gas assets and FPSO relating to the Anasuria Cluster. The recoverable amount is determined using the FVLCTS model based on discounted cash flows (“DCF” derived from the expected cash in/outflow pattern over the production lives.)
The key assumptions used to determine the recoverable amount for the Anasuria Cluster were as follows:
(i Discount rate of 10%;)
(ii Future cost inflation factor of 2% per annum;)
(iii Oil price forecast based on the oil price forward curve from independent parties; and,)
(iv Oil production profile based on the assessment by independent oil and gas reserve experts.)
Based on the assessments performed, the Directors concluded that the recoverable amount calculated based on the valuation model is higher than the carrying amount.
(b North Sabah)
The acquisition of the North Sabah assets was completed in the previous financial year. Details of the acquisition are as disclosed in Note 15 to the financial statements.
The Directors have concluded that there is no impairment indicator for North Sabah during the current financial year.
Here, we can see that the recoverable amount of the Anasuria field was estimated based on a DCF of expected future cash flows over the production life of the asset. The key assumptions used by management all seem appropriate, including a discount rate of 10% and oil price and oil production estimates based on independent assessment. From there, management concludes that the recoverable amount of the Anasuria field is higher than its carrying amount (i.e. no impairment required). Likewise, for the North Sabah field.
How do we interpret this? Basically, what management is saying is that given a 10% discount rate and independent oil price and oil production estimates, the accumulated profits (i.e. recoverable amount) from both the North Sabah and the Anasuria fields exceed their carrying amounts of RM 471m and RM 668m respectively.
In other words, according to management’s own estimates, the carrying value of the Intangible Assets of RM 1.468 billion approximates the accumulated Net Profit recoverable from 2P reserves.
To conclude Valuation (Method 2), we arrive at the following:

Our estimates Management estimates
Accumulated Net Profit from 2P Reserves RM 1.452 billion RM 1.468 billion

Financials

By now, we have established the basic economics of Hibiscus’s business, including its revenues (i.e. oil production and oil price scenarios), costs (OPEX, ITDA), profitability (breakeven, future earnings potential) and balance sheet value (2P reserves, valuation). Moving on, we want to gain a deeper understanding of the 3 statements to anticipate any blind spots and risks. We’ll refer to the financial statements of both the FY20 annual report and the 2Q21 quarterly report in this analysis.
For the sake of brevity, I’ll only point out those line items which need extra attention, and skip over the rest. Feel free to go through the financial statements on your own to gain a better familiarity of the business.
https://preview.redd.it/h689bss79br41.png?width=810&format=png&auto=webp&s=ed47fce6a5c3815dd3d4f819e31f1ce39ccf4a0b
Income Statement
First, we’ll start with the Income Statement on page 135 of the AR20. Revenues are straightforward, as we’ve discussed above. Cost of Sales and Administrative Expenses fall under the jurisdiction of OPEX, which we’ve also seen earlier. Other Expenses are mostly made up of Depreciation & Amortization of RM 115m.
Finance Costs are where things start to get tricky. Why does a company which carries no debt have such huge amounts of finance costs? The reason can be found in Note 8, where it is revealed that the bulk of finance costs relate to the unwinding of discount of provision for decommissioning costs of RM 25m (Note 32).
https://preview.redd.it/4omjptbe9br41.png?width=1019&format=png&auto=webp&s=eaabfc824134063100afa62edfd36a34a680fb60
This actually refers to the expected future costs of restoring the Anasuria and North Sabah fields to their original condition once the oil reserves have been depleted. Accounting standards require the company to provide for these decommissioning costs as they are estimable and probable. The way the decommissioning costs are accounted for is the same as an amortized loan, where the initial carrying value is recognized as a liability and the discount rate applied is reversed each year as an expense on the Income Statement. However, these expenses are largely non-cash in nature and do not necessitate a cash outflow every year (FY20: RM 69m).
Unwinding of discount on non-current other payables of RM 12m relate to contractual payments to the North Sabah sellers. We will discuss it later.
Taxation is another tricky subject, and is even more significant than Finance Costs at RM 161m. In gist, Hibiscus is subject to the 38% PITA (Petroleum Income Tax Act) under Malaysian jurisdiction, and the 30% Petroleum tax + 10% Supplementary tax under UK jurisdiction. Of the RM 161m, RM 41m of it relates to deferred tax which originates from the difference between tax treatment and accounting treatment on capitalized assets (accelerated depreciation vs straight-line depreciation). Nonetheless, what you should take away from this is that the tax expense is a tangible expense and material to breakeven analysis.
Fortunately, tax is a variable expense, and should not materially impact the cash flow of Hibiscus in today’s low oil price environment.
Note: Cash outflows for Tax Paid in FY20 was RM 97m, substantially below the RM 161m tax expense.
https://preview.redd.it/1xrnwzm89br41.png?width=732&format=png&auto=webp&s=c078bc3e18d9c79d9a6fbe1187803612753f69d8
Balance Sheet
The balance sheet of Hibiscus is unexciting; I’ll just bring your attention to those line items which need additional scrutiny. I’ll use the figures in the latest 2Q21 quarterly report (2Q21) and refer to the notes in AR20 for clarity.
We’ve already discussed Intangible Assets in the section above, so I won’t dwell on it again.
Moving on, the company has Equipment of RM 582m, largely relating to O&G assets (e.g. the Anasuria FPSO vessel and CAPEX incurred on production enhancement projects). Restricted cash and bank balances represent contractual obligations for decommissioning costs of the Anasuria Cluster, and are inaccessible for use in operations.
Inventories are relatively low, despite Hibiscus being an E&P company, so forex fluctuations on carrying value of inventories are relatively immaterial. Trade receivables largely relate to entitlements from Petronas and BP (both oil supermajors), and are hence quite safe from impairment. Other receivables, deposits and prepayments are significant as they relate to security deposits placed with sellers of the oil fields acquired; these should be ignored for cash flow purposes.
Note: Total cash and bank balances do not include approximately RM 105 m proceeds from the North Sabah December 2019 offtake (which was received in January 2020)
Cash and bank balances of RM 90m do not include RM 105m of proceeds from offtake received in 3Q21 (Jan 2020). Hence, the actual cash and bank balances as of 2Q21 approximate RM 200m.
Liabilities are a little more interesting. First, I’ll draw your attention to the significant Deferred tax liabilities of RM 457m. These largely relate to the amortization of CAPEX (i.e. Equipment and capitalized E&E expenses), which is given an accelerated depreciation treatment for tax purposes.
The way this works is that the government gives Hibiscus a favorable tax treatment on capital expenditures incurred via an accelerated depreciation schedule, so that the taxable income is less than usual. However, this leads to the taxable depreciation being utilized quicker than accounting depreciation, hence the tax payable merely deferred to a later period – when the tax depreciation runs out but accounting depreciation remains. Given the capital intensive nature of the business, it is understandable why Deferred tax liabilities are so large.
We’ve discussed Provision for decommissioning costs under the Finance Costs section earlier. They are also quite significant at RM 266m.
Notably, the Other Payables and Accruals are a hefty RM 431m. What do they relate to? Basically, they are contractual obligations to the sellers of the oil fields which are only payable upon oil prices reaching certain thresholds. Hence, while they are current in nature, they will only become payable when oil prices recover to previous highs, and are hence not an immediate cash outflow concern given today’s low oil prices.
Cash Flow Statement
There is nothing in the cash flow statement which warrants concern.
Notably, the company generated OCF of approximately RM 500m in FY20 and RM 116m in 2Q21. It further incurred RM 330m and RM 234m of CAPEX in FY20 and 2Q21 respectively, largely owing to production enhancement projects to increase the production rate of the Anasuria and North Sabah fields, which according to management estimates are accretive to ROI.
Tax paid was RM 97m in FY20 and RM 61m in 2Q21 (tax expense: RM 161m and RM 62m respectively).

Risks

There are a few obvious and not-so-obvious risks that one should be aware of before investing in Hibiscus. We shall not consider operational risks (e.g. uptime, OPEX) as they are outside the jurisdiction of the equity analyst. Instead, we shall focus on the financial and strategic risks largely outside the control of management. The main ones are:
· Oil prices remaining subdued for long periods of time
· Fluctuation of exchange rates
· Customer concentration risk
· 2P Reserves being less than estimated
· Significant current and non-current liabilities
· Potential issuance of equity
Oil prices remaining subdued
Of topmost concern in the minds of most analysts is whether Hibiscus has the wherewithal to sustain itself through this period of low oil prices (sub-$30). A quick and dirty estimate of annual cash outflow (i.e. burn rate) assuming a $20 oil world and historical production rates is between RM 50m-70m per year, which considering the RM 200m cash balance implies about 3-4 years of sustainability before the company runs out of cash and has to rely on external assistance for financing.
Table 1: Hibiscus EBITDA at different oil price and exchange rates
https://preview.redd.it/gxnekd6h9br41.png?width=670&format=png&auto=webp&s=edbfb9621a43480d11e3b49de79f61a6337b3d51
The above table shows different EBITDA scenarios (RM ‘m) given different oil prices (left column) and USD:MYR exchange rates (top row). Currently, oil prices are $27 and USD:MYR is 1:4.36.
Given conservative assumptions of average OPEX/bbl of $20 (current: $15), we can safely say that the company will be loss-making as long as oil remains at $20 or below (red). However, we can see that once oil prices hit $25, the company can tank the lower-end estimate of the annual burn rate of RM 50m (orange), while at RM $27 it can sufficiently muddle through the higher-end estimate of the annual burn rate of RM 70m (green).
Hence, we can assume that as long as the average oil price over the next 3-4 years remains above $25, Hibiscus should come out of this fine without the need for any external financing.
Customer Concentration Risk
With regards to customer concentration risk, there is not much the analyst or investor can do except to accept the risk. Fortunately, 80% of revenues can be attributed to two oil supermajors (Petronas and BP), hence the risk of default on contractual obligations and trade receivables seems to be quite diminished.
2P Reserves being less than estimated
2P Reserves being less than estimated is another risk that one should keep in mind. Fortunately, the current market cap is merely RM 714m – at half of estimated recoverable amounts of RM 1.468 billion – so there’s a decent margin of safety. In addition, there are other mitigating factors which shall be discussed in the next section (‘Opportunities’).
Significant non-current and current liabilities
The significant non-current and current liabilities have been addressed in the previous section. It has been determined that they pose no threat to immediate cash flow due to them being long-term in nature (e.g. decommissioning costs, deferred tax, etc). Hence, for the purpose of assessing going concern, their amounts should not be a cause for concern.
Potential issuance of equity
Finally, we come to the possibility of external financing being required in this low oil price environment. While the company should last 3-4 years on existing cash reserves, there is always the risk of other black swan events materializing (e.g. coronavirus) or simply oil prices remaining muted for longer than 4 years.
Furthermore, management has hinted that they wish to acquire new oil assets at presently depressed prices to increase daily production rate to a targeted 20,000 bbl by end-2021. They have room to acquire debt, but they may also wish to issue equity for this purpose. Hence, the possibility of dilution to existing shareholders cannot be entirely ruled out.
However, given management’s historical track record of prioritizing ROI and optimal capital allocation, and in consideration of the fact that the MD owns 10% of outstanding shares, there is some assurance that any potential acquisitions will be accretive to EPS and therefore valuations.

Opportunities

As with the existence of risk, the presence of material opportunities also looms over the company. Some of them are discussed below:
· Increased Daily Oil Production Rate
· Inclusion of 2C Resources
· Future oil prices exceeding $50 and effects from coronavirus dissipating
Increased Daily Oil Production Rate
The first and most obvious opportunity is the potential for increased production rate. We’ve seen in the last quarter (2Q21) that the North Sabah field increased its daily production rate by approximately 20% as a result of production enhancement projects (infill drilling), lowering OPEX/bbl as a result. To vastly oversimplify, infill drilling is the process of maximizing well density by drilling in the spaces between existing wells to improve oil production.
The same improvements are being undertaken at the Anasuria field via infill drilling, subsea debottlenecking, water injection and sidetracking of existing wells. Without boring you with industry jargon, this basically means future production rate is likely to improve going forward.
By how much can the oil production rate be improved by? Management estimates in their analyst presentation that enhancements in the Anasuria field will be able to yield 5,000 bbl/day by 2021 (current: 2,500 bbl/day).
Similarly, improvements in the North Sabah field is expected to yield 7,000 bbl/day by 2021 (current: 5,300 bbl/day).
This implies a total 2021 expected daily production rate from the two fields alone of 12,000 bbl/day (current: 8,000 bbl/day). That’s a 50% increase in yields which we haven’t factored into our valuation yet.
Furthermore, we haven’t considered any production from existing 2C resources (e.g. Marigold/Sunflower) or any potential acquisitions which may occur in the future. By management estimates, this can potentially increase production by another 8,000 bbl/day, bringing total production to 20,000 bbl/day.
While this seems like a stretch of the imagination, it pays to keep them in mind when forecasting future revenues and valuations.
Just to play around with the numbers, I’ve come up with a sensitivity analysis of possible annual EBITDA at different oil prices and daily oil production rates:
Table 2: Hibiscus EBITDA at different oil price and daily oil production rates
https://preview.redd.it/jnpfhr5n9br41.png?width=814&format=png&auto=webp&s=bbe4b512bc17f576d87529651140cc74cde3d159
The left column represents different oil prices while the top row represents different daily oil production rates.
The green column represents EBITDA at current daily production rate of 8,000 bbl/day; the orange column represents EBITDA at targeted daily production rate of 12,000 bbl/day; while the purple column represents EBITDA at maximum daily production rate of 20,000 bbl/day.
Even conservatively assuming increased estimated annual ITDA of RM 500m (FY20: RM 318m), and long-term average oil prices of $50 (FY20: $60), the estimated Net Profit and P/E ratio is potentially lucrative at daily oil production rates of 12,000 bbl/day and above.
2C Resources
Since we’re on the topic of improved daily oil production rate, it bears to pay in mind the relatively enormous potential from Hibiscus’s 2C Resources. North Sabah’s 2C Resources alone exceed 30 mmbbl; while those from the yet undiagnosed Marigold/Sunflower fields also reach 30 mmbbl. Altogether, 2C Resources exceed 70 mmbbl, which dwarfs the 44 mmbbl of 2P Reserves we have considered up to this point in our valuation estimates.
To refresh your memory, 2C Resources represents oil volumes which have been discovered but are not yet classified as “commercial”. This means that there is reasonable certainty of the oil being recoverable, as opposed to simply being in the very early stages of exploration. So, to be conservative, we will imagine that only 50% of 2C Resources are eligible for reclassification to 2P reserves, i.e. 35 mmbbl of oil.
https://preview.redd.it/mto11iz7abr41.png?width=375&format=png&auto=webp&s=e9028ab0816b3d3e25067447f2c70acd3ebfc41a
This additional 35 mmbbl of oil represents an 80% increase to existing 2P reserves. Assuming the daily oil production rate increases similarly by 80%, we will arrive at 14,400 bbl/day of oil production. According to Table 2 above, this would yield an EBITDA of roughly RM 630m assuming $50 oil.
Comparing that estimated EBITDA to FY20’s actual EBITDA:
FY20 FY21 (incl. 2C) Difference
Daily oil production (bbl/day) 8,626 14,400 +66%
Average oil price (USD/bbl) $68.57 $50 -27%
Average OPEX/bbl (USD) $16.64 $20 +20%
EBITDA (RM ‘m) 632 630 -
Hence, even conservatively assuming lower oil prices and higher OPEX/bbl (which should decrease in the presence of higher oil volumes) than last year, we get approximately the same EBITDA as FY20.
For the sake of completeness, let’s assume that Hibiscus issues twice the no. of existing shares over the next 10 years, effectively diluting shareholders by 50%. Even without accounting for the possibility of the acquisition of new oil fields, at the current market capitalization of RM 714m, the prospective P/E would be about 10x. Not too shabby.
Future oil prices exceeding $50 and effects from coronavirus dissipating
Hibiscus shares have recently been hit by a one-two punch from oil prices cratering from $60 to $30, as a result of both the Saudi-Russian dispute and depressed demand for oil due to coronavirus. This has massively increased supply and at the same time hugely depressed demand for oil (due to the globally coordinated lockdowns being implemented).
Given a long enough timeframe, I fully expect OPEC+ to come to an agreement and the economic effects from the coronavirus to dissipate, allowing oil prices to rebound. As we equity investors are aware, oil prices are cyclical and are bound to recover over the next 10 years.
When it does, valuations of O&G stocks (including Hibiscus’s) are likely to improve as investors overshoot expectations and begin to forecast higher oil prices into perpetuity, as they always tend to do in good times. When that time arrives, Hibiscus’s valuations are likely to become overoptimistic as all O&G stocks tend to do during oil upcycles, resulting in valuations far exceeding reasonable estimates of future earnings. If you can hold the shares up until then, it’s likely you will make much more on your investment than what we’ve been estimating.

Conclusion

Wrapping up what we’ve discussed so far, we can conclude that Hibiscus’s market capitalization of RM 714m far undershoots reasonable estimates of fair value even under conservative assumptions of recoverable oil volumes and long-term average oil prices. As a value investor, I hesitate to assign a target share price, but it’s safe to say that this stock is worth at least RM 1.00 (current: RM 0.45). Risk is relatively contained and the upside far exceeds the downside. While I have no opinion on the short-term trajectory of oil prices, I can safely recommend this stock as a long-term Buy based on fundamental research.
submitted by investorinvestor to SecurityAnalysis [link] [comments]

Giving Audiobook Gifts from my large library! Pick one and I'll send it to your Audible Library :D

Hi everyone, I have a bunch of awesome audio-books and I learned that Audible lets you gift 1 book to every Audible account. I haven't done this before so everyone will be able to get a book!

Below is my list of books, I have the Sherlock collection which is over 60 hours, The Silent Patient, Bird Box, some great Sci-fi books and much much more!
Send me a message to bradkingbooks at g.mail with the book you'd like and the e.mail associated with your Audible Account that you'd like it sent to and I'll send it over asap!

I'm sure I'll get a lot of requests so I'll have to batch process these, don't panic if I don't get the book to you right away, I will :)

List of Audiobooks

The Things We Cannot Say
Kelly Rimmer

The Dark Bones
Loreth Anne White

A Killer's Mind: Zoe Bentley Mystery
Mike Omer

Paddle Your Own Canoe: One Man's Fundamentals for Delicious Living
Nick Offerman

Dad Is Fat
Jim Gaffigan

Sentiment Inc.: The Retro Sci-Fi Series, Book 2
Poul Anderson

Shadows of Tomorrow
Jessica Meats

Thinking Big: Think Differently, Grow Rich, Develop Better Personal Relationships, Move Up the Corporate Ladder, Sleep Better and Fight Mediocrity: Everything You Need to Become a Stable, Succesful Human: Superior Ultralearning Topics, Book One
Paxton Arbital

What to Expect When You’re Expecting
Heidi Murkoff

So, You Want to Talk About Government Contracting?: Everything You Need to Know in Order to Become a Government Contracting Master - 3 Guides in 1!
Brad W. King

Then She Was Gone: A Novel
Lisa Jewell

The Silent Patient
Alex Michaelides

Bird Box: A Novel
Josh Malerman

The Silver Horn Echoes: A Song of Roland
Michael Eging,
Steve Arnold

The Burnout Generation
Anne Helen Petersen

One Good Deed
David Baldacci

DragonMan: The 13th Sign: DragonMan Series, Book 8
Ted Lazaris


Visions: Knights of Salucia, Book 1
C.D. Espeseth

The Black Hussars
Mitchell Lüthi

Swing Trading: How to Become a Swing Trader. Complete Guide to Learning Strategies, Techniques, Tools & What You Need to Know About: Options, Stocks, Forex & Cryptocurrency
Ted Brown

Starblind: Starblind, Book 1
D. T. Dyllin

Akillia's Reign: Puatera Online Series, Book 4
Dawn Chapman

Confessions of a Shanty Irishman
Michael Corrigan

True Crime Stories Boxset: 48 Terrifying True Crime Murder Cases: List of Twelve Collection, Book 1
Ryan Becker

The Sisters
Dervla McTiernan

Body of Proof: An Audible Original
Darrell Brown,
Sophie Ellis

Understudies
Ravi Mangla

Academic Curveball: Braxton Campus Mysteries, Book 1
James J. Cudney

Dead on Instinct: A Dr. Jessica Coran, FBI, Medical Thriller: The Instinct Series, Book 15
Robert W. Walker

Captain
Thomas Block

To My Beloved Heart: The Last Journey of Edgar Allan Poe
James Marchiori

The Cabinet of Curiosities: A Novel
Douglas Preston,
Lincoln Child

Wally Roux, Quantum Mechanic
Nick Carr

Treasure Island: An Audible Original Drama
Robert Louis Stevenson,
Marty Ross - adaptation

Reliquary: Pendergast, Book 2
Douglas Preston,
Lincoln Child

Relic
Douglas Preston,
Lincoln Child

The Life We Bury
Allen Eskens

We Are Legion (We Are Bob): Bobiverse, Book 1
Dennis E. Taylor

The Wife Between Us
Greer Hendricks,
Sarah Pekkanen

The Deep, Deep Snow
Brian Freeman

The Evil of Father: Father Earth, Book 2
Brad W. King

Backlash: The Scot Harvath Series, Book 19
Brad Thor

Leviathan Wakes
James S. A. Corey

Ender's Game Alive: The Full Cast Audioplay
Orson Scott Card

Chainworld
Matt Langley,
Paul Ebbs

The Dead Drink First
Dale Maharidge

Alien III: An Audible Original Drama
William Gibson

The Silver City: A Prequel of the Father Earth Series
Brad W. King

The Echo Killing: A Mystery
Christi Daugherty

Sherlock Holmes
Arthur Conan Doyle,
Stephen Fry - introductions

Evil Has a Name: The Untold of the Golden State Killer Investigation
Paul Holes,
Jim Clemente,
Peter McDonnell

Infernal Devices: Mortal Engines, Book 3
Philip Reeve

A Darkling Plain: Mortal Engines, Book 4
Philip Reeve

The Expectant Father: The Ultimate Guide for Dads-to-Be
Armin A. Brott,
Jennifer Ash

Yeah Baby!: The Modern Mama's Guide to Mastering Pregnancy, Having a Healthy Baby, and Bouncing Back Better Than Ever
Jillian Michaels

Situation Momedy
Jenna Von Oy

Whoa, Baby! What Just Happened?
Kelly Rowland

Predator's Gold: Mortal Engines, Book 2
Philip Reeve

Where the Crawdads Sing
Delia Owens

Sharp Objects: A Novel
Gillian Flynn

Congo
Michael Crichton

Something in the Water: A Novel
Catherine Steadman

Mortal Engines: Mortal Engines, Book 1
Philip Reeve

The Last Mrs. Parrish: A Novel
Liv Constantine

Sometimes I Lie
Alice Feeney

Silent Child: Audible's Thriller of 2017
Sarah A. Denzil

Paradox Bound: A Novel
Peter Clines

Armada
Armada: A Novel

Ernest Cline
Ready Player One

Other Actions
The Alice Network


The Alice Network: A Novel
Kate Quinn

Killman Creek
Rachel Caine

The Woman in the Window: A Novel
A. J. Finn

Murder on Black Swan Lane
Andrea Penrose

Before We Were Yours: A Novel
Lisa Wingate

The Good Samaritan
John Marrs
Children of Time
Adrian Tchaikovsky

The Midnight Line: A Jack Reacher Novel
Lee Child

Bitter Moon: The Huntress/FBI Thrillers, Book 4
Alexandra Sokoloff

Cold Moon: The Huntress/FBI Thrillers, Book 3
Alexandra Sokoloff

Blood Moon
Alexandra Sokoloff

Huntress Moon
Alexandra Sokoloff

The Good Daughter: A Novel
Karin Slaughter

Stillhouse Lake
Rachel Caine

Little Girl Lost: Detective Robyn Carter Crime Thriller Series, Book 1
Carol Wyer

The Likeness
Tana French

In the Woods: A Novel
Tana French

Never Go Back: A Jack Reacher Novel
Lee Child

My Sister's Grave: Tracy Crosswhite, Book 1
Robert Dugoni

Persuader
Lee Child

Sycamore Row
John Grisham

The Trapped Girl: Tracy Crosswhite, Book 4
Robert Dugoni

Midnight
Dean Koontz

Plum Island
Nelson DeMille

Fear Nothing
Dean Koontz

A Perfect Spy: A Novel
John le Carré

It's Superman!
Tom De Haven

The Chemist
Stephenie Meyer

Invisible Man: A Novel
Ralph Ellison

Airborn
Kenneth Oppel
submitted by bradkingbooks to audible [link] [comments]

[FREE] 1 Audio-book Gift from my large library!

I have a bunch of awesome audio-books and I learned that Audible lets you gift 1 book to every Audible account so anyone can pick any book any number of times, so choose your favorite. I haven't done this before so everyone will be able to get a book!
Below is my list of books, I have the Sherlock collection which is over 60 hours, The Silent Patient, Bird Box, some great Sci-fi books and much much more! Send me a message with the book you'd like and the emal associated with your Audible Account that you'd like it sent to.
I'm sure I'll get a lot of requests so I'll have to batch process these, don't panic if I don't get the book to you right away, I will :)

List of Audiobooks

The Things We Cannot Say
Kelly Rimmer

The Dark Bones
Loreth Anne White

A Killer's Mind: Zoe Bentley Mystery
Mike Omer

Paddle Your Own Canoe: One Man's Fundamentals for Delicious Living
Nick Offerman

Dad Is Fat
Jim Gaffigan

Sentiment Inc.: The Retro Sci-Fi Series, Book 2
Poul Anderson

Shadows of Tomorrow
Jessica Meats

Thinking Big: Think Differently, Grow Rich, Develop Better Personal Relationships, Move Up the Corporate Ladder, Sleep Better and Fight Mediocrity: Everything You Need to Become a Stable, Succesful Human: Superior Ultralearning Topics, Book One
Paxton Arbital

What to Expect When You’re Expecting
Heidi Murkoff

So, You Want to Talk About Government Contracting?: Everything You Need to Know in Order to Become a Government Contracting Master - 3 Guides in 1!
Brad W. King

Then She Was Gone: A Novel
Lisa Jewell

The Silent Patient
Alex Michaelides

Bird Box: A Novel
Josh Malerman

The Silver Horn Echoes: A Song of Roland
Michael Eging,
Steve Arnold

The Burnout Generation
Anne Helen Petersen

One Good Deed
David Baldacci

DragonMan: The 13th Sign: DragonMan Series, Book 8
Ted Lazaris


Visions: Knights of Salucia, Book 1
C.D. Espeseth

The Black Hussars
Mitchell Lüthi

Swing Trading: How to Become a Swing Trader. Complete Guide to Learning Strategies, Techniques, Tools & What You Need to Know About: Options, Stocks, Forex & Cryptocurrency
Ted Brown

Starblind: Starblind, Book 1
D. T. Dyllin

Akillia's Reign: Puatera Online Series, Book 4
Dawn Chapman

Confessions of a Shanty Irishman
Michael Corrigan

True Crime Stories Boxset: 48 Terrifying True Crime Murder Cases: List of Twelve Collection, Book 1
Ryan Becker

The Sisters
Dervla McTiernan

Body of Proof: An Audible Original
Darrell Brown,
Sophie Ellis

Understudies
Ravi Mangla

Academic Curveball: Braxton Campus Mysteries, Book 1
James J. Cudney

Dead on Instinct: A Dr. Jessica Coran, FBI, Medical Thriller: The Instinct Series, Book 15
Robert W. Walker

Captain
Thomas Block

To My Beloved Heart: The Last Journey of Edgar Allan Poe
James Marchiori

The Cabinet of Curiosities: A Novel
Douglas Preston,
Lincoln Child

Wally Roux, Quantum Mechanic
Nick Carr

Treasure Island: An Audible Original Drama
Robert Louis Stevenson,
Marty Ross - adaptation

Reliquary: Pendergast, Book 2
Douglas Preston,
Lincoln Child

Relic
Douglas Preston,
Lincoln Child

The Life We Bury
Allen Eskens

We Are Legion (We Are Bob): Bobiverse, Book 1
Dennis E. Taylor

The Wife Between Us
Greer Hendricks,
Sarah Pekkanen

The Deep, Deep Snow
Brian Freeman

The Evil of Father: Father Earth, Book 2
Brad W. King

Backlash: The Scot Harvath Series, Book 19
Brad Thor

Leviathan Wakes
James S. A. Corey

Ender's Game Alive: The Full Cast Audioplay
Orson Scott Card

Chainworld
Matt Langley,
Paul Ebbs

The Dead Drink First
Dale Maharidge

Alien III: An Audible Original Drama
William Gibson

The Silver City: A Prequel of the Father Earth Series
Brad W. King

The Echo Killing: A Mystery
Christi Daugherty

Sherlock Holmes
Arthur Conan Doyle,
Stephen Fry - introductions

Evil Has a Name: The Untold of the Golden State Killer Investigation
Paul Holes,
Jim Clemente,
Peter McDonnell

Infernal Devices: Mortal Engines, Book 3
Philip Reeve

A Darkling Plain: Mortal Engines, Book 4
Philip Reeve

The Expectant Father: The Ultimate Guide for Dads-to-Be
Armin A. Brott,
Jennifer Ash

Yeah Baby!: The Modern Mama's Guide to Mastering Pregnancy, Having a Healthy Baby, and Bouncing Back Better Than Ever
Jillian Michaels

Situation Momedy
Jenna Von Oy

Whoa, Baby! What Just Happened?
Kelly Rowland

Predator's Gold: Mortal Engines, Book 2
Philip Reeve

Where the Crawdads Sing
Delia Owens

Sharp Objects: A Novel
Gillian Flynn

Congo
Michael Crichton

Something in the Water: A Novel
Catherine Steadman

Mortal Engines: Mortal Engines, Book 1
Philip Reeve

The Last Mrs. Parrish: A Novel
Liv Constantine

Sometimes I Lie
Alice Feeney

Silent Child: Audible's Thriller of 2017
Sarah A. Denzil

Paradox Bound: A Novel
Peter Clines

Armada
Armada: A Novel

Ernest Cline
Ready Player One

Other Actions
The Alice Network


The Alice Network: A Novel
Kate Quinn

Killman Creek
Rachel Caine

The Woman in the Window: A Novel
A. J. Finn

Murder on Black Swan Lane
Andrea Penrose

Before We Were Yours: A Novel
Lisa Wingate

The Good Samaritan
John Marrs
Children of Time
Adrian Tchaikovsky

The Midnight Line: A Jack Reacher Novel
Lee Child

Bitter Moon: The Huntress/FBI Thrillers, Book 4
Alexandra Sokoloff

Cold Moon: The Huntress/FBI Thrillers, Book 3
Alexandra Sokoloff

Blood Moon
Alexandra Sokoloff

Huntress Moon
Alexandra Sokoloff

The Good Daughter: A Novel
Karin Slaughter

Stillhouse Lake
Rachel Caine

Little Girl Lost: Detective Robyn Carter Crime Thriller Series, Book 1
Carol Wyer

The Likeness
Tana French

In the Woods: A Novel
Tana French

Never Go Back: A Jack Reacher Novel
Lee Child

My Sister's Grave: Tracy Crosswhite, Book 1
Robert Dugoni

Persuader
Lee Child

Sycamore Row
John Grisham

The Trapped Girl: Tracy Crosswhite, Book 4
Robert Dugoni

Midnight
Dean Koontz

Plum Island
Nelson DeMille

Fear Nothing
Dean Koontz

A Perfect Spy: A Novel
John le Carré

It's Superman!
Tom De Haven

The Chemist
Stephenie Meyer

Invisible Man: A Novel
Ralph Ellison

Airborn
Kenneth Oppel
submitted by bradkingbooks to FREE [link] [comments]

Giving Audiobook Gifts from my large library! Pick one and I'll send it to your Audible Library :D

Hi everyone, I have a bunch of awesome audio-books and I learned that Audible lets you gift 1 book to every Audible account. I haven't done this before so everyone will be able to get a book!

Below is my list of books, I have the Sherlock collection which is over 60 hours, The Silent Patient, Bird Box, some great Sci-fi books and much much more! Send me a message to bradkingbooks at g.mail with the book you'd like and the e.mail associated with your Audible Account that you'd like it sent to.

I'm sure I'll get a lot of requests so I'll have to batch process these, don't panic if I don't get the book to you right away, I will :)

List of Audiobooks

The Things We Cannot Say
Kelly Rimmer

The Dark Bones
Loreth Anne White

A Killer's Mind: Zoe Bentley Mystery
Mike Omer

Paddle Your Own Canoe: One Man's Fundamentals for Delicious Living
Nick Offerman

Dad Is Fat
Jim Gaffigan

Sentiment Inc.: The Retro Sci-Fi Series, Book 2
Poul Anderson

Shadows of Tomorrow
Jessica Meats

Thinking Big: Think Differently, Grow Rich, Develop Better Personal Relationships, Move Up the Corporate Ladder, Sleep Better and Fight Mediocrity: Everything You Need to Become a Stable, Succesful Human: Superior Ultralearning Topics, Book One
Paxton Arbital

What to Expect When You’re Expecting
Heidi Murkoff

So, You Want to Talk About Government Contracting?: Everything You Need to Know in Order to Become a Government Contracting Master - 3 Guides in 1!
Brad W. King

Then She Was Gone: A Novel
Lisa Jewell

The Silent Patient
Alex Michaelides

Bird Box: A Novel
Josh Malerman

The Silver Horn Echoes: A Song of Roland
Michael Eging,
Steve Arnold

The Burnout Generation
Anne Helen Petersen

One Good Deed
David Baldacci

DragonMan: The 13th Sign: DragonMan Series, Book 8
Ted Lazaris


Visions: Knights of Salucia, Book 1
C.D. Espeseth

The Black Hussars
Mitchell Lüthi

Swing Trading: How to Become a Swing Trader. Complete Guide to Learning Strategies, Techniques, Tools & What You Need to Know About: Options, Stocks, Forex & Cryptocurrency
Ted Brown

Starblind: Starblind, Book 1
D. T. Dyllin

Akillia's Reign: Puatera Online Series, Book 4
Dawn Chapman

Confessions of a Shanty Irishman
Michael Corrigan

True Crime Stories Boxset: 48 Terrifying True Crime Murder Cases: List of Twelve Collection, Book 1
Ryan Becker

The Sisters
Dervla McTiernan

Body of Proof: An Audible Original
Darrell Brown,
Sophie Ellis

Understudies
Ravi Mangla

Academic Curveball: Braxton Campus Mysteries, Book 1
James J. Cudney

Dead on Instinct: A Dr. Jessica Coran, FBI, Medical Thriller: The Instinct Series, Book 15
Robert W. Walker

Captain
Thomas Block

To My Beloved Heart: The Last Journey of Edgar Allan Poe
James Marchiori

The Cabinet of Curiosities: A Novel
Douglas Preston,
Lincoln Child

Wally Roux, Quantum Mechanic
Nick Carr

Treasure Island: An Audible Original Drama
Robert Louis Stevenson,
Marty Ross - adaptation

Reliquary: Pendergast, Book 2
Douglas Preston,
Lincoln Child

Relic
Douglas Preston,
Lincoln Child

The Life We Bury
Allen Eskens

We Are Legion (We Are Bob): Bobiverse, Book 1
Dennis E. Taylor

The Wife Between Us
Greer Hendricks,
Sarah Pekkanen

The Deep, Deep Snow
Brian Freeman

The Evil of Father: Father Earth, Book 2
Brad W. King

Backlash: The Scot Harvath Series, Book 19
Brad Thor

Leviathan Wakes
James S. A. Corey

Ender's Game Alive: The Full Cast Audioplay
Orson Scott Card

Chainworld
Matt Langley,
Paul Ebbs

The Dead Drink First
Dale Maharidge

Alien III: An Audible Original Drama
William Gibson

The Silver City: A Prequel of the Father Earth Series
Brad W. King

The Echo Killing: A Mystery
Christi Daugherty

Sherlock Holmes
Arthur Conan Doyle,
Stephen Fry - introductions

Evil Has a Name: The Untold of the Golden State Killer Investigation
Paul Holes,
Jim Clemente,
Peter McDonnell

Infernal Devices: Mortal Engines, Book 3
Philip Reeve

A Darkling Plain: Mortal Engines, Book 4
Philip Reeve

The Expectant Father: The Ultimate Guide for Dads-to-Be
Armin A. Brott,
Jennifer Ash

Yeah Baby!: The Modern Mama's Guide to Mastering Pregnancy, Having a Healthy Baby, and Bouncing Back Better Than Ever
Jillian Michaels

Situation Momedy
Jenna Von Oy

Whoa, Baby! What Just Happened?
Kelly Rowland

Predator's Gold: Mortal Engines, Book 2
Philip Reeve

Where the Crawdads Sing
Delia Owens

Sharp Objects: A Novel
Gillian Flynn

Congo
Michael Crichton

Something in the Water: A Novel
Catherine Steadman

Mortal Engines: Mortal Engines, Book 1
Philip Reeve

The Last Mrs. Parrish: A Novel
Liv Constantine

Sometimes I Lie
Alice Feeney

Silent Child: Audible's Thriller of 2017
Sarah A. Denzil

Paradox Bound: A Novel
Peter Clines

Armada
Armada: A Novel

Ernest Cline
Ready Player One

Other Actions
The Alice Network


The Alice Network: A Novel
Kate Quinn

Killman Creek
Rachel Caine

The Woman in the Window: A Novel
A. J. Finn

Murder on Black Swan Lane
Andrea Penrose

Before We Were Yours: A Novel
Lisa Wingate

The Good Samaritan
John Marrs
Children of Time
Adrian Tchaikovsky

The Midnight Line: A Jack Reacher Novel
Lee Child

Bitter Moon: The Huntress/FBI Thrillers, Book 4
Alexandra Sokoloff

Cold Moon: The Huntress/FBI Thrillers, Book 3
Alexandra Sokoloff

Blood Moon
Alexandra Sokoloff

Huntress Moon
Alexandra Sokoloff

The Good Daughter: A Novel
Karin Slaughter

Stillhouse Lake
Rachel Caine

Little Girl Lost: Detective Robyn Carter Crime Thriller Series, Book 1
Carol Wyer

The Likeness
Tana French

In the Woods: A Novel
Tana French

Never Go Back: A Jack Reacher Novel
Lee Child

My Sister's Grave: Tracy Crosswhite, Book 1
Robert Dugoni

Persuader
Lee Child

Sycamore Row
John Grisham

The Trapped Girl: Tracy Crosswhite, Book 4
Robert Dugoni

Midnight
Dean Koontz

Plum Island
Nelson DeMille

Fear Nothing
Dean Koontz

A Perfect Spy: A Novel
John le Carré

It's Superman!
Tom De Haven

The Chemist
Stephenie Meyer

Invisible Man: A Novel
Ralph Ellison

Airborn
Kenneth Oppel
submitted by bradkingbooks to audiobooks [link] [comments]

2020 on Forex: the new forecasts

The coronavirus has changed everything. When analysts gave forecasts for 2020 at the end of last year, no one could foresee that the whole world would be seized by the pandemic. Call it a “black swan” or not, it’s necessary to re-evaluate the situation and adjust the medium- and the long-term outlook. Below you will find the analysis of the main Forex drivers and the overview of the prospects for the key commodities.

US recession

In 2019, economists had some fears of a potential US recession. Well, they were right not only about the USA, but also about the whole world as lockdowns pushed every country to the deep downturn. Now it’s clear that earlier the view was naturally more optimistic. How encouraging the US unemployment rate and NFP were at the end of 2019! We couldn’t imagine at that time that more than 33 million Americans would lose jobs and economic activity would fall to unprecedented lows. The Fed made a dire scenario for the prolonged US recession. All the needed measures have been taken, almost 3 trillion dollars were provided to support the market and additional aids are expected. Anyway, the US dollar gains as a safe-haven currency. The collapse of USD this year remains highly unlikely.

Central banks’ monetary policy

In December, we expected the Federal Reserve to be patient in its monetary policy decisions. At the same time, we didn’t underestimate the power of rate cuts due to recession fears. Coronavirus outbreak flipped the script with the Federal Reserve unveiling outstanding measures to support the suffering economy. The first rate cut from 1.5-1.75% to 1-1.25% happened at the beginning of March and was followed by an even bigger rate cut to the range of 0-0.25% just after a week. At the same time, the regulator announced an unlimited buying of mortgage-backed securities and plans to buy corporate bonds and bonds backed by consumer debt. Moreover, the Fed Chair Jerome Powell didn’t exclude the possibility of negative interest rates. Even though our forecasts were not 100% accurate, the upside for the USD has been indeed limited. As for the stock market, after a shock wave caused by Covid-19, the ultra-loose monetary policy pushed the indices up.
Other major central banks also joined the easing game. The Reserve banks of Australia and New Zealand cut their interest rate to unprecedented lows of 0.25%. The Bank of England and the Bank of Canada lowered their interest rate as well to 0.1% and 0.25% respectively. As for the European Central bank, it keeps the zero interest rate on hold. The supportive tool the ECB presented is the 750 billion euro Pandemic Emergency Purchase Programme (PEPP) aimed to counter the serious risks to the outlook of the Eurozone.
As all major central banks conduct almost similar easing policy, the Forex pairs can fluctuate within certain levels for a long period. That is actually a good news for range-bound traders, as channels are expected to remain quite strong.
ECB
The European Central Bank let the market know that it was aiming to do whatever it takes to save the euro area from the coronavirus damage. However, trouble always brings his brother: Germany was so tired to be the sponsor of the unlimited bond-purchasing ECB program that the German court claimed that it actually violated constitution. Now, the ECB has three months to explain that purchases were "proportionate". The ECB credibility is under threat as Germany may pull out of the next ECB's bond purchases. This situation has made euro quite volatile.

Brexit

Boris Johnson hasn’t kept his promise “to get Brexit done” yet. However, we can forgive him for that as this year brings much worse problems to deal with. Now, when countries are getting over the coronavirus shock, the UK and EU should hold the last round of trade talks and finalize an agreement by the end of December. Some analysts are skeptical about that. They think the deadline could be extended beyond the end of December, leaving the UK subject to tariffs on most goods. This would be devastating for the British pound. The sooner the UK and EU make a deal, the better for GBP.

Oil

Oil prices spent last year between $50 and $70. December was positive with the US and China ceasing fire in the trade war and OPEC extending production cuts. Possibility of a scenario where prices drop to 0 and below was absolutely inconceivable even for the most pessimistic observers, and yet it came true. It marked the beginning of 2020 with historically unseen turbulence, even apart from the coronavirus hit.
In the long term, however, there are all fundamentals for oil prices to get back to where they were. However, that may not happen this year. Observers predict that oil prices will recover to the levels of $55-60 if there is nothing in the way during the year. Otherwise, $30 is seen as the safest baseline level for the commodity during 2020.

Stocks

Just like in 2019, the stock market had a nightmarish beginning of 2020. S&P lost 35%, with some stocks losing more than 50% of value. As the summer season is coming, the market sees 50% of the losses recovered in most sectors. While the shape of recovery is being discussed, most analysts agree that after the worst-performing Q2, the S&P will continue restoring its value.
Notice that the situation is different for different stocks. Locked by the anti-virus restrictions, most of the world population was forced to spend weeks and months at home facing their TVs, laptops, and desktops. That made strong Internet-related companies blossom, so we saw Amazon and Netflix rise to even higher value than before the virus. On the contrary, the healthcare sector struggling to invent the vaccine saw Moderna, BionTech, Inovio, and other new and old pharma companies surge to unexpected heights.
IT and Internet communications companies will likely gain much more attention during the year.
Google, Nvidia, Disney, Apple, and many more around the IT and Internet sectors have the full potential to spearhead the S&P in 2020 and further on.
submitted by FBS_Forex to u/FBS_Forex [link] [comments]

‘’Pirates’’ will save crypto?

Perhaps, why not! However, what stops crypto from bullish growing? To my mind, the main reasons are not the volatility and lack of clear legal regulation, but the lack of new users (new blood), which creates a ‘’narrow’’ market. Why is this not a PR message? A message that can potentially attract the attention of brand new users who cannot take into account other investment tools (because of their complexity or high entry point or just because of the restrictions of policies of accredited investors).
If you invested in bitcoin (or in another functional cryptocurrency) exactly a year ago, then even now despite the market drop caused by the new “black swan” - a recession against the background of coronavirus, you would get more than 35% growth.
Why do we see that the audience of followers is not updated? Why all the projects are fighting for the same fans who entered the crypto before 2018 and continuing to place media uselessly on the same sites? As we all remember, until 2018, each project had access to 2 billion audience through a whole set of tools from advertising on social networks to context advertising. We used LinkedIn, reddit, twitter and of course, the 2 main tools for attracting traffic (google and Facebook). Each crypto project, using these marketing instruments, brought its advertising messages to a new audience, not only carrying out the KPI of the project, but also fueling up interest in the blockchain as a whole industry; thereby increasing the demand for crypto and its liquidity. Like any new financial instrument, crypto is faced with the resistance of the old financial system:
· misinformation on TV and the mass media (crypto is a lie, crypto is a drug and terrorism)
· pressure from regulators (SEC refused, limited, punished)
· And, of course, a decision that has the most “destructive” effect - a ban on the largest advertising platforms in the world.
Unfortunately, the sweet times before the “ban” can no longer come back. Since January 2018, advertising of blockchain and cryptocurrency projects on most of the platforms in the world and social networks has been prohibited. The first to limit the right to advertise were Google AdWords and DoubleClick, introducing a direct ban on advertising content in terms of cryptocurrencies and related materials. A similar situation with context advertising is in Yandex Direct. Social networks also show unfair attitude to the crypto industry. Nonetheless, the crypto industry is approaching a line that it becomes simply impossible to ignore. After all, no matter how the new model is revolutionary and capable of making the world a better place — it is doomed to die if no one knows about it. Of course, if you have a good marketing agency, and you are a large and successful venture blockchain project (from the top of best and most famous), with all the necessary licenses, you can still compete for banning in fb and google. Moreover, although it takes a long time, I know several projects that now have permission for official advertising. Despite the fact that the largest platforms have banned startup blockchain advertising, there are still ways to promote it.
What should everyone else do? What to do for a new comer that is just entering the market. Or for an old project that failed to get into the top of the most recognizable? ‘’Use your existing inventory’’ - it seems like the most important piece of advice that almost every project follows. Now we see how hundreds of projects are simultaneously placing on the same platforms (crypto news, ICO listings, bloggers), squeezing the last attention and investments from the same target groups. What are the results? They are obvious. Fundraising is falling, the number of new users and investors is not increasing, and liquidity is falling. In addition, for these reasons, in the last year, crypto has finally turned out from an instrument that would destroy the hegemony of big money, into an instrument - not very studied and too volatile.
What to do in order to revive the interest to crypto? Right now, to start to search and apply new traffic tools. Sources that can give huge coverage and this will help attract new users to your project, for whom you can become the first successful investment in the blockchain. What to study from? What and how to apply? The easiest way, as always, is to learn the experience of those who live in the world of advertising restrictions for a very long period. For example - casinos, forex, bookmakers, unlicensed video etc. We analyzed the largest representatives of these advertisers and chose the most effective method of placement, which appeared in the top of all advertisers – pirate sites with unlicensed content. It is also not a secret that many well-known offline and online retailers and not only are not ashamed of advertising on such sites along with advertising of the above-discriminated businesses. In addition, the crypto industry can be considered so far as discriminated in its rights.
What makes pirate sites so attractive? The main sense of advertising on resources with unlicensed content is the incredibly large coverage of the audience at relatively low prices. The largest resources provide 10 million unique visitors every month. The cost differs depending on the format – pre roll, branding, banner, and order of display. Price - from $ 10 for 1 thousand unique views. It is also worth considering the possibility of paying with crypto and a simple workflow, which allows you to make placements for very young and unknown companies. Technically, such platforms can track all interested users, so that later they can activate their attention in other campaigns to optimize marketing and advertising costs, which will allow the advertiser to save the customer’s budget in such a financially turbulent time, while generating even more leads. Indeed, traditional media today are still too expensive and do not have such technical capabilities of their platforms. The millionth audience of pirate resources is explained by the fact that the user loves unlicensed content, and such a user has other interests and hobbies, including the crypto, blockchain, venture projects and much more, which is so discriminated in advertising by official media and social networks. The ethical issue in the modern world of capitalist chaos caused by the global crisis can be left aside, as for marketing strategies, such ‘’pirate’’ resources:
· provide an opportunity to build moderate total project costs
· save on advertising, but do not limit yourself in their use
· as much as possible and as soon as possible can reach your target group and collect leads
· despite of discrimination to the dissemination of information about the crypto and blockchain project, to have workarounds to gather your audience
· not depend constantly on the changing policies of official expensive advertiser's platforms and their instructions
That is precisely what projects need in order to be successful during the limitation and expensive media.
If you are interested in the opportunities described above or you can offer services that will help crypto projects gather more audiences - feel free to write me: [[email protected]](mailto:[email protected]) or in telegram - u/golubev_serge
Sergey Golubev (Сергей Голубев)
EU structural funds, ICO/STO/IEO projects, NGO & investment projects, project management, comprehensive support for business
submitted by Golubyev_Sergiy to content_marketing [link] [comments]

‘’Pirates’’ will save crypto?

Perhaps, why not! However, what stops crypto from bullish growing? To my mind, the main reasons are not the volatility and lack of clear legal regulation, but the lack of new users (new blood), which creates a ‘’narrow’’ market. Why is this not a PR message? A message that can potentially attract the attention of brand new users who cannot take into account other investment tools (because of their complexity or high entry point or just because of the restrictions of policies of accredited investors).
If you invested in bitcoin (or in another functional cryptocurrency) exactly a year ago, then even now despite the market drop caused by the new “black swan” - a recession against the background of coronavirus, you would get more than 35% growth.
Why do we see that the audience of followers is not updated? Why all the projects are fighting for the same fans who entered the crypto before 2018 and continuing to place media uselessly on the same sites? As we all remember, until 2018, each project had access to 2 billion audience through a whole set of tools from advertising on social networks to context advertising. We used LinkedIn, reddit, twitter and of course, the 2 main tools for attracting traffic (google and Facebook). Each crypto project, using these marketing instruments, brought its advertising messages to a new audience, not only carrying out the KPI of the project, but also fueling up interest in the blockchain as a whole industry; thereby increasing the demand for crypto and its liquidity. Like any new financial instrument, crypto is faced with the resistance of the old financial system:
· misinformation on TV and the mass media (crypto is a lie, crypto is a drug and terrorism)
· pressure from regulators (SEC refused, limited, punished)
· And, of course, a decision that has the most “destructive” effect - a ban on the largest advertising platforms in the world.
Unfortunately, the sweet times before the “ban” can no longer come back. Since January 2018, advertising of blockchain and cryptocurrency projects on most of the platforms in the world and social networks has been prohibited. The first to limit the right to advertise were Google AdWords and DoubleClick, introducing a direct ban on advertising content in terms of cryptocurrencies and related materials. A similar situation with context advertising is in Yandex Direct. Social networks also show unfair attitude to the crypto industry. Nonetheless, the crypto industry is approaching a line that it becomes simply impossible to ignore. After all, no matter how the new model is revolutionary and capable of making the world a better place — it is doomed to die if no one knows about it. Of course, if you have a good marketing agency, and you are a large and successful venture blockchain project (from the top of best and most famous), with all the necessary licenses, you can still compete for banning in fb and google. Moreover, although it takes a long time, I know several projects that now have permission for official advertising. Despite the fact that the largest platforms have banned startup blockchain advertising, there are still ways to promote it.
What should everyone else do? What to do for a new comer that is just entering the market. Or for an old project that failed to get into the top of the most recognizable? ‘’Use your existing inventory’’ - it seems like the most important piece of advice that almost every project follows. Now we see how hundreds of projects are simultaneously placing on the same platforms (crypto news, ICO listings, bloggers), squeezing the last attention and investments from the same target groups. What are the results? They are obvious. Fundraising is falling, the number of new users and investors is not increasing, and liquidity is falling. In addition, for these reasons, in the last year, crypto has finally turned out from an instrument that would destroy the hegemony of big money, into an instrument - not very studied and too volatile.
What to do in order to revive the interest to crypto? Right now, to start to search and apply new traffic tools. Sources that can give huge coverage and this will help attract new users to your project, for whom you can become the first successful investment in the blockchain. What to study from? What and how to apply? The easiest way, as always, is to learn the experience of those who live in the world of advertising restrictions for a very long period. For example - casinos, forex, bookmakers, unlicensed video etc. We analyzed the largest representatives of these advertisers and chose the most effective method of placement, which appeared in the top of all advertisers – pirate sites with unlicensed content. It is also not a secret that many well-known offline and online retailers and not only are not ashamed of advertising on such sites along with advertising of the above-discriminated businesses. In addition, the crypto industry can be considered so far as discriminated in its rights.
What makes pirate sites so attractive? The main sense of advertising on resources with unlicensed content is the incredibly large coverage of the audience at relatively low prices. The largest resources provide 10 million unique visitors every month. The cost differs depending on the format – pre roll, branding, banner, and order of display. Price - from $ 10 for 1 thousand unique views. It is also worth considering the possibility of paying with crypto and a simple workflow, which allows you to make placements for very young and unknown companies. Technically, such platforms can track all interested users, so that later they can activate their attention in other campaigns to optimize marketing and advertising costs, which will allow the advertiser to save the customer’s budget in such a financially turbulent time, while generating even more leads. Indeed, traditional media today are still too expensive and do not have such technical capabilities of their platforms. The millionth audience of pirate resources is explained by the fact that the user loves unlicensed content, and such a user has other interests and hobbies, including the crypto, blockchain, venture projects and much more, which is so discriminated in advertising by official media and social networks. The ethical issue in the modern world of capitalist chaos caused by the global crisis can be left aside, as for marketing strategies, such ‘’pirate’’ resources:
· provide an opportunity to build moderate total project costs
· save on advertising, but do not limit yourself in their use
· as much as possible and as soon as possible can reach your target group and collect leads
· despite of discrimination to the dissemination of information about the crypto and blockchain project, to have workarounds to gather your audience
· not depend constantly on the changing policies of official expensive advertiser's platforms and their instructions
That is precisely what projects need in order to be successful during the limitation and expensive media.
If you are interested in the opportunities described above or you can offer services that will help crypto projects gather more audiences - feel free to write me: [[email protected]](mailto:[email protected]) or in telegram - u/golubev_serge
Sergey Golubev (Сергей Голубев)
EU structural funds, ICO/STO/IEO projects, NGO & investment projects, project management, comprehensive support for business
submitted by Golubyev_Sergiy to DigitalMarketing [link] [comments]

‘’Pirates’’ will save crypto?

Perhaps, why not! However, what stops crypto from bullish growing? To my mind, the main reasons are not the volatility and lack of clear legal regulation, but the lack of new users (new blood), which creates a ‘’narrow’’ market. Why is this not a PR message? A message that can potentially attract the attention of brand new users who cannot take into account other investment tools (because of their complexity or high entry point or just because of the restrictions of policies of accredited investors).
If you invested in bitcoin (or in another functional cryptocurrency) exactly a year ago, then even now despite the market drop caused by the new “black swan” - a recession against the background of coronavirus, you would get more than 35% growth.
Why do we see that the audience of followers is not updated? Why all the projects are fighting for the same fans who entered the crypto before 2018 and continuing to place media uselessly on the same sites? As we all remember, until 2018, each project had access to 2 billion audience through a whole set of tools from advertising on social networks to context advertising. We used LinkedIn, reddit, twitter and of course, the 2 main tools for attracting traffic (google and Facebook). Each crypto project, using these marketing instruments, brought its advertising messages to a new audience, not only carrying out the KPI of the project, but also fueling up interest in the blockchain as a whole industry; thereby increasing the demand for crypto and its liquidity. Like any new financial instrument, crypto is faced with the resistance of the old financial system:
· misinformation on TV and the mass media (crypto is a lie, crypto is a drug and terrorism)
· pressure from regulators (SEC refused, limited, punished)
· And, of course, a decision that has the most “destructive” effect - a ban on the largest advertising platforms in the world.
Unfortunately, the sweet times before the “ban” can no longer come back. Since January 2018, advertising of blockchain and cryptocurrency projects on most of the platforms in the world and social networks has been prohibited. The first to limit the right to advertise were Google AdWords and DoubleClick, introducing a direct ban on advertising content in terms of cryptocurrencies and related materials. A similar situation with context advertising is in Yandex Direct. Social networks also show unfair attitude to the crypto industry. Nonetheless, the crypto industry is approaching a line that it becomes simply impossible to ignore. After all, no matter how the new model is revolutionary and capable of making the world a better place — it is doomed to die if no one knows about it. Of course, if you have a good marketing agency, and you are a large and successful venture blockchain project (from the top of best and most famous), with all the necessary licenses, you can still compete for banning in fb and google. Moreover, although it takes a long time, I know several projects that now have permission for official advertising. Despite the fact that the largest platforms have banned startup blockchain advertising, there are still ways to promote it.
What should everyone else do? What to do for a new comer that is just entering the market. Or for an old project that failed to get into the top of the most recognizable? ‘’Use your existing inventory’’ - it seems like the most important piece of advice that almost every project follows. Now we see how hundreds of projects are simultaneously placing on the same platforms (crypto news, ICO listings, bloggers), squeezing the last attention and investments from the same target groups. What are the results? They are obvious. Fundraising is falling, the number of new users and investors is not increasing, and liquidity is falling. In addition, for these reasons, in the last year, crypto has finally turned out from an instrument that would destroy the hegemony of big money, into an instrument - not very studied and too volatile.
What to do in order to revive the interest to crypto? Right now, to start to search and apply new traffic tools. Sources that can give huge coverage and this will help attract new users to your project, for whom you can become the first successful investment in the blockchain. What to study from? What and how to apply? The easiest way, as always, is to learn the experience of those who live in the world of advertising restrictions for a very long period. For example - casinos, forex, bookmakers, unlicensed video etc. We analyzed the largest representatives of these advertisers and chose the most effective method of placement, which appeared in the top of all advertisers – pirate sites with unlicensed content. It is also not a secret that many well-known offline and online retailers and not only are not ashamed of advertising on such sites along with advertising of the above-discriminated businesses. In addition, the crypto industry can be considered so far as discriminated in its rights.
What makes pirate sites so attractive? The main sense of advertising on resources with unlicensed content is the incredibly large coverage of the audience at relatively low prices. The largest resources provide 10 million unique visitors every month. The cost differs depending on the format – pre roll, branding, banner, and order of display. Price - from $ 10 for 1 thousand unique views. It is also worth considering the possibility of paying with crypto and a simple workflow, which allows you to make placements for very young and unknown companies. Technically, such platforms can track all interested users, so that later they can activate their attention in other campaigns to optimize marketing and advertising costs, which will allow the advertiser to save the customer’s budget in such a financially turbulent time, while generating even more leads. Indeed, traditional media today are still too expensive and do not have such technical capabilities of their platforms. The millionth audience of pirate resources is explained by the fact that the user loves unlicensed content, and such a user has other interests and hobbies, including the crypto, blockchain, venture projects and much more, which is so discriminated in advertising by official media and social networks. The ethical issue in the modern world of capitalist chaos caused by the global crisis can be left aside, as for marketing strategies, such ‘’pirate’’ resources:
· provide an opportunity to build moderate total project costs
· save on advertising, but do not limit yourself in their use
· as much as possible and as soon as possible can reach your target group and collect leads
· despite of discrimination to the dissemination of information about the crypto and blockchain project, to have workarounds to gather your audience
· not depend constantly on the changing policies of official expensive advertiser's platforms and their instructions
That is precisely what projects need in order to be successful during the limitation and expensive media.
If you are interested in the opportunities described above or you can offer services that will help crypto projects gather more audiences - feel free to write me: [[email protected]](mailto:[email protected]) or in telegram - u/golubev_serge
Sergey Golubev (Сергей Голубев)
EU structural funds, ICO/STO/IEO projects, NGO & investment projects, project management, comprehensive support for business
submitted by Golubyev_Sergiy to digital_marketing [link] [comments]

‘’Pirates’’ will save crypto?

If you invested in bitcoin (or in another functional cryptocurrency) exactly a year ago, then even now despite the market drop caused by the new “black swan” - a recession against the background of coronavirus, you would get more than 35% growth.
Why do we see that the audience of followers is not updated? Why all the projects are fighting for the same fans who entered the crypto before 2018 and continuing to place media uselessly on the same sites? As we all remember, until 2018, each project had access to 2 billion audience through a whole set of tools from advertising on social networks to context advertising. We used LinkedIn, reddit, twitter and of course, the 2 main tools for attracting traffic (google and Facebook). Each crypto project, using these marketing instruments, brought its advertising messages to a new audience, not only carrying out the KPI of the project, but also fueling up interest in the blockchain as a whole industry; thereby increasing the demand for crypto and its liquidity. Like any new financial instrument, crypto is faced with the resistance of the old financial system:
· misinformation on TV and the mass media (crypto is a lie, crypto is a drug and terrorism)
· pressure from regulators (SEC refused, limited, punished)
· And, of course, a decision that has the most “destructive” effect - a ban on the largest advertising platforms in the world.
Unfortunately, the sweet times before the “ban” can no longer come back. Since January 2018, advertising of blockchain and cryptocurrency projects on most of the platforms in the world and social networks has been prohibited. The first to limit the right to advertise were Google AdWords and DoubleClick, introducing a direct ban on advertising content in terms of cryptocurrencies and related materials. A similar situation with context advertising is in Yandex Direct. Social networks also show unfair attitude to the crypto industry. Nonetheless, the crypto industry is approaching a line that it becomes simply impossible to ignore. After all, no matter how the new model is revolutionary and capable of making the world a better place — it is doomed to die if no one knows about it. Of course, if you have a good marketing agency, and you are a large and successful venture blockchain project (from the top of best and most famous), with all the necessary licenses, you can still compete for banning in fb and google. Moreover, although it takes a long time, I know several projects that now have permission for official advertising. Despite the fact that the largest platforms have banned startup blockchain advertising, there are still ways to promote it.
What should everyone else do? What to do for a new comer that is just entering the market. Or for an old project that failed to get into the top of the most recognizable? ‘’Use your existing inventory’’ - it seems like the most important piece of advice that almost every project follows. Now we see how hundreds of projects are simultaneously placing on the same platforms (crypto news, ICO listings, bloggers), squeezing the last attention and investments from the same target groups. What are the results? They are obvious. Fundraising is falling, the number of new users and investors is not increasing, and liquidity is falling. In addition, for these reasons, in the last year, crypto has finally turned out from an instrument that would destroy the hegemony of big money, into an instrument - not very studied and too volatile.
What to do in order to revive the interest to crypto? Right now, to start to search and apply new traffic tools. Sources that can give huge coverage and this will help attract new users to your project, for whom you can become the first successful investment in the blockchain. What to study from? What and how to apply? The easiest way, as always, is to learn the experience of those who live in the world of advertising restrictions for a very long period. For example - casinos, forex, bookmakers, unlicensed video etc. We analyzed the largest representatives of these advertisers and chose the most effective method of placement, which appeared in the top of all advertisers – pirate sites with unlicensed content. It is also not a secret that many well-known offline and online retailers and not only are not ashamed of advertising on such sites along with advertising of the above-discriminated businesses. In addition, the crypto industry can be considered so far as discriminated in its rights.
What makes pirate sites so attractive? The main sense of advertising on resources with unlicensed content is the incredibly large coverage of the audience at relatively low prices. The largest resources provide 10 million unique visitors every month. The cost differs depending on the format – pre roll, branding, banner, and order of display. Price - from $ 10 for 1 thousand unique views. It is also worth considering the possibility of paying with crypto and a simple workflow, which allows you to make placements for very young and unknown companies. Technically, such platforms can track all interested users, so that later they can activate their attention in other campaigns to optimize marketing and advertising costs, which will allow the advertiser to save the customer’s budget in such a financially turbulent time, while generating even more leads. Indeed, traditional media today are still too expensive and do not have such technical capabilities of their platforms. The millionth audience of pirate resources is explained by the fact that the user loves unlicensed content, and such a user has other interests and hobbies, including the crypto, blockchain, venture projects and much more, which is so discriminated in advertising by official media and social networks. The ethical issue in the modern world of capitalist chaos caused by the global crisis can be left aside, as for marketing strategies, such ‘’pirate’’ resources:
· provide an opportunity to build moderate total project costs
· save on advertising, but do not limit yourself in their use
· as much as possible and as soon as possible can reach your target group and collect leads
· despite of discrimination to the dissemination of information about the crypto and blockchain project, to have workarounds to gather your audience
· not depend constantly on the changing policies of official expensive advertiser's platforms and their instructions
That is precisely what projects need in order to be successful during the limitation and expensive media.
If you are interested in the opportunities described above or you can offer services that will help crypto projects gather more audiences - feel free to write me: [[email protected]](mailto:[email protected]) or in telegram - u/golubev_serge
Sergey Golubev (Сергей Голубев)
EU structural funds, ICO/STO/IEO projects, NGO & investment projects, project management, comprehensive support for business
submitted by Golubyev_Sergiy to SocialMediaMarketing [link] [comments]

I have a profitable strategy, how do I make it into a fund? And should I?

I've been experimenting with forex for over 10 years and with crypto for over a year now. About 3 months ago I have created and launched a strategy that is consistently profitable. Now I want to monetize it.
My options are: get a bank loan, create a legal fund for accredited investors, create an anonymous tokenized fund for anyone.
My strategy does involve margin trading and a certain amount of risk so in case of catastrophic events in the market there is a chance of losing all of the capital. That's why I'm hesitant about getting a bank loan, in case of a "black swan" I will be out of money and it would take quite a bit of time to repay it. I only have a certain amount of money to invest and my amount of "play money" is much smaller than many others.
I have spoken with a number of accredited investors and they are interested but they don't want just to make money, the want to make sure they get all tax reporting and even get to write off losses. Apparently having a winning strategy is not enough for them, there has to be a complicated legal structure that costs tens of thousands to set up.
This leaves me with an option of building a tokenized fund where all the capital is divided into crypto tokens and tokens go up in value as the fund value increases. This will allow regular people to invest their money at a reasonable rate, not the 3-5% you get in a savings account or GIC. But because I control the trading account it will still be centralized and raises an issue of trust. There have been so many scams and pyramids that I'm sure most people will be reluctant to invest. I would also like to keep it anonymous not to attract criminals and hackers.
What would you do if you were me?
submitted by _cryptoquest_ to CryptoCurrencyTrading [link] [comments]

"Safe" timeframe?

Hey /forex
I was wondering if you find a specific timeframe "safe" regarding Draghi/Yellen speaches, NFP news and other volatile news.
In my current short term strategy, if there's some volatile news coming out, I stop trading either for the entire day or stop just before the news comes out.
At what timeframe would you feel safe to miss a volatile news event, knowing that the wimeframe will not be that volatile?
And yes I know that no one can predict black swan events.
inb4 - "I never feel safe in the markets, you're stoopid"
submitted by Bjoeschoe to Forex [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

Top Commenters

  1. tuckerbalch (2296 points, 1185 comments)
  2. davebyrd (1033 points, 466 comments)
  3. yokh_cs7646 (320 points, 177 comments)
  4. rgraziano3 (266 points, 147 comments)
  5. j0shj0nes (264 points, 148 comments)
  6. i__want__piazza (236 points, 127 comments)
  7. swamijay (227 points, 116 comments)
  8. _ant0n_ (205 points, 149 comments)
  9. ml4tstudent (204 points, 117 comments)
  10. gatechben (179 points, 107 comments)
  11. BNielson (176 points, 108 comments)
  12. jameschanx (176 points, 94 comments)
  13. Artmageddon (167 points, 83 comments)
  14. htrajan (162 points, 81 comments)
  15. boyko11 (154 points, 99 comments)
  16. alyssa_p_hacker (146 points, 80 comments)
  17. log_base_pi (141 points, 80 comments)
  18. Ran__Ran (139 points, 99 comments)
  19. johnsmarion (136 points, 86 comments)
  20. jgorman30_gatech (135 points, 102 comments)
  21. dyllll (125 points, 91 comments)
  22. MikeLachmayr (123 points, 95 comments)
  23. awhoof (113 points, 72 comments)
  24. SharjeelHanif (106 points, 59 comments)
  25. larrva (101 points, 69 comments)
  26. augustinius (100 points, 52 comments)
  27. oimesbcs (99 points, 67 comments)
  28. vansh21k (98 points, 62 comments)
  29. W1redgh0st (97 points, 70 comments)
  30. ybai67 (96 points, 41 comments)
  31. JuanCarlosKuriPinto (95 points, 54 comments)
  32. acschwabe (93 points, 58 comments)
  33. pharmerino (92 points, 47 comments)
  34. jgeiger (91 points, 28 comments)
  35. Zapurza (88 points, 70 comments)
  36. jyoms (87 points, 55 comments)
  37. omscs_zenan (87 points, 44 comments)
  38. nurobezede (85 points, 64 comments)
  39. BelaZhu (83 points, 50 comments)
  40. jason_gt (82 points, 36 comments)
  41. shuang379 (81 points, 64 comments)
  42. ggatech (81 points, 51 comments)
  43. nitinkodial_gatech (78 points, 59 comments)
  44. harshsikka123 (77 points, 55 comments)
  45. bkeenan7 (76 points, 49 comments)
  46. moxyll (76 points, 32 comments)
  47. nelsongcg (75 points, 53 comments)
  48. nickzelei (75 points, 41 comments)
  49. hunter2omscs (74 points, 29 comments)
  50. pointblank41 (73 points, 36 comments)
  51. zheweisun (66 points, 48 comments)
  52. bs_123 (66 points, 36 comments)
  53. storytimeuva (66 points, 36 comments)
  54. sva6 (66 points, 31 comments)
  55. bhrolenok (66 points, 27 comments)
  56. lingkaizuo (63 points, 46 comments)
  57. Marvel_this (62 points, 36 comments)
  58. agifft3_omscs (62 points, 35 comments)
  59. ssung40 (61 points, 47 comments)
  60. amchang87 (61 points, 32 comments)
  61. joshuak_gatech (61 points, 30 comments)
  62. fall2017_ml4t_cs_god (60 points, 50 comments)
  63. ccrouch8 (60 points, 45 comments)
  64. nick_algorithm (60 points, 29 comments)
  65. JetsonDavis (59 points, 35 comments)
  66. yjacket103 (58 points, 36 comments)
  67. hilo260 (58 points, 29 comments)
  68. coolwhip1234 (58 points, 15 comments)
  69. chvbs2000 (57 points, 49 comments)
  70. suman_paul (57 points, 29 comments)
  71. masterm (57 points, 23 comments)
  72. RolfKwakkelaar (55 points, 32 comments)
  73. rpb3 (55 points, 23 comments)
  74. venkatesh8 (54 points, 30 comments)
  75. omscs_avik (53 points, 37 comments)
  76. bman8810 (52 points, 31 comments)
  77. snladak (51 points, 31 comments)
  78. dfihn3 (50 points, 43 comments)
  79. mlcrypto (50 points, 32 comments)
  80. omscs-student (49 points, 26 comments)
  81. NellVega (48 points, 32 comments)
  82. booglespace (48 points, 23 comments)
  83. ccortner3 (48 points, 23 comments)
  84. caa5042 (47 points, 34 comments)
  85. gcalma3 (47 points, 25 comments)
  86. krushnatmore (44 points, 32 comments)
  87. sn_48 (43 points, 22 comments)
  88. thenewprofessional (43 points, 16 comments)
  89. urider (42 points, 33 comments)
  90. gatech-raleighite (42 points, 30 comments)
  91. chrisong2017 (41 points, 26 comments)
  92. ProudRamblinWreck (41 points, 24 comments)
  93. kramey8 (41 points, 24 comments)
  94. coderafk (40 points, 28 comments)
  95. niufen (40 points, 23 comments)
  96. tholladay3 (40 points, 23 comments)
  97. SaberCrunch (40 points, 22 comments)
  98. gnr11 (40 points, 21 comments)
  99. nadav3 (40 points, 18 comments)
  100. gt7431a (40 points, 16 comments)

Top Submissions

  1. [Project Questions] Unit Tests for assess_portfolio assignment by reyallan (58 points, 52 comments)
  2. [Project Questions] Unit Tests for optimize_something assignment by agifft3_omscs (53 points, 94 comments)
  3. Proper git workflow by jan-laszlo (43 points, 19 comments)
  4. Exam 2 Information by yokh_cs7646 (39 points, 40 comments)
  5. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes by davebyrd (37 points, 10 comments)
  6. Project 1 Megathread (assess_portfolio) by davebyrd (34 points, 466 comments)
  7. defeat_learner test case by swamijay (34 points, 38 comments)
  8. Project 2 Megathread (optimize_something) by tuckerbalch (33 points, 475 comments)
  9. project 3 megathread (assess_learners) by tuckerbalch (27 points, 1130 comments)
  10. Deadline extension? by johannes_92 (26 points, 40 comments)

Top Comments

  1. 34 points: jgeiger's comment in QLearning Robot project megathread
  2. 31 points: coolwhip1234's comment in QLearning Robot project megathread
  3. 30 points: tuckerbalch's comment in Why Professor is usually late for class?
  4. 23 points: davebyrd's comment in Deadline extension?
  5. 20 points: jason_gt's comment in What would be a good quiz question regarding The Big Short?
  6. 19 points: yokh_cs7646's comment in For online students: Participation check #2
  7. 17 points: i__want__piazza's comment in project 3 megathread (assess_learners)
  8. 17 points: nathakhanh2's comment in Project 2 Megathread (optimize_something)
  9. 17 points: pharmerino's comment in Midterm study Megathread
  10. 17 points: tuckerbalch's comment in Midterm grades posted to T-Square
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