submitted by FmzQuant to CryptoCurrencyTrading [link] [comments]
SummaryIn the previous article, we explained the premise of realizing the trading strategy from the aspects of the introduction of the M language , the basic grammar, the model execution method, and the model classification. In this article, we will continue the previous part, from the commonly used strategy modules and technologies. Indicators, step by step to help you achieve a viable intraday quantitative trading strategy.
Stage IncreaseStage increase is calculating the percentage of current K line's closing price compare with previous N periods of closing price's difference. For example: Computing the latest 10 K-lines stage increases, can be written:
CLOSE_0:=CLOSE; //get the current K-line's closing price, and save the results to variable CLOSE_0. CLOSE_10:=REF(CLOSE,10); //get the pervious 10 K-lines' closing price, and save the results to variable CLOSE_10 (CLOSE_0-CLOSE_10)/CLOSE_10*100;//calculating the percentage of current K line's closing price compare with previous N periods of closing price's difference.
New high priceThe new high price is calculated by whether the current K line is greater than N cycles' highest price. For example: calculating whether the current K line is greater than the latest 10 K-lines' highest price, can be written:
HHV_10:=HHV(HIGH,10); //Get the highest price of latest 10 K-lines, which includes the current K-line. HIGH>REF(HHV_10,1); //Judge whether the current K-line's highest price is greater than pervious K-lines' HHV_10 value.
Price raise with massive trading volume increaseFor example: If the current K line's closing price is 1.5 times of the closing price of the previous 10 K-lines, which means in 10 days, the price has risen 50%; and the trading volume also increased more than 5 times of the pervious 10 K-lines. can be written:
CLOSE_10:=REF(CLOSE,10); //get the 10th K-line closing price IS_CLOSE:=CLOSE/CLOSE_10>1.5; //Judging whether the current K Line closing price is 1.5 times greater than the value of CLOSE_10 VOL_MA_10:=MA(VOL,10); //get the latest 10 K-lines' average trading volume IS_VOL:=VOL>VOL_MA_10*5; //Judging whether the current K-line's trading volume is 5 times greater than the value of VOL_MA_10 IS_CLOSE AND IS_VOL; //Judging whether the condition of IS_CLOSE and IS_VOL are both true.
Price narrow-shock marketNarrow-shock market means that the price is maintained within a certain range in the recent period. For example: If the highest price in 10 cycles minus the lowest price in 10 cycles, the result divided by the current K-line's closing price is less than 0.05. can be written:
HHV_10:=HHV(CLOSE,10); //Get the highest price in 10 cycles(including current K-line) LLV_10:=LLV(CLOSE,10); //Get the lowest price in 10 cycles(including current K-line) (HHV_10-LLV_10)/CLOSE<0.05; //Judging whether the difference between HHV_10 and LLV_10 divided by current k-line's closing price is less than 0.05.
Moving average indicates bull marketMoving Average indicates long and short direction, K line supported by or resisted by 5，10，20，30，60 moving average line, Moving average indicates bull market or bear market. can be written:
MA_5:=MA(CLOSE,5); //get the moving average of 5 cycle closing price. MA_10:=MA(CLOSE,10);//get the moving average of 10 cycle closing price. MA_20:=MA(CLOSE,20);//get the moving average of 20 cycle closing price. MA_30:=MA(CLOSE,30);//get the moving average of 30 cycle closing price. MA_5>MA_10 AND MA_10>MA_20 AND MA_20>MA_30; //determine wether the MA_5 is greater than MA_10, and MA_10 is greater than MA_20, and MA_20 is greater than MA_30.
Previous high price and its locationsTo obtain the location of the previous high price and its location, you can use FMZ Quant API directly. can be written:
HHV_20:=HHV(HIGH,20); //get the highest price of 20 cycle(including current K line) HHVBARS_20:=HHVBARS(HIGH,20); //get the number of cycles from the highest price in 20 cycles to current K line HHV_60_40:REF(HHV_20,40); //get the highest price between 60 cycles and 40 cycles.
Price gap jumpingThe price gap is the case where the highest and lowest prices of the two K lines are not connected. It consists of two K lines, and the price gap is the reference price of the support and pressure points in the future price movement. When a price gap occurs, it can be assumed that an acceleration along the trend with original direction has begun. can be written:
HHV_1:=REF(H,1); //get the pervious K line's highest price LLV_1:=REF(L,1); //get the pervious K line's lowest price HH:=L>HHV_1; //judging wether the current K line's lowest price is greater than pervious K line's highest price (jump up) LL:=H
Common technical indicatorsMoving average
From a statistical point of view, the moving average is the arithmetic average of the daily price, which is a trending price trajectory. The moving average system is a common technical tool used by most analysts. From a technical point of view, it is a factor that affects the psychological price of technical analysts. The decision-making factor of thinking trading is a good reference tool for technical analysts. The FMZ Quant tool supports many different types of moving averages, as shown below:
MA_DEMO:MA(CLOSE,5); // get the moving average of 5 cycle MA_DEMO:EMA(CLOSE,15); // get the smooth moving average of 15 cycle MA_DEMO:EMA2(CLOSE,10);// get the linear weighted moving average of 10 cycle MA_DEMO:EMAWH(CLOSE,50); // get the exponentially weighted moving average of 50 cycle MA_DEMO:DMA(CLOSE,100); // get the dynamic moving average of 100 cycle MA_DEMO:SMA(CLOSE,10,3); // get the fixed weight of 3 moving average of closing price in 10 cycle MA_DEMO:ADMA(CLOSE,9,2,30); // get the fast-line 2 and slow-line 30 Kaufman moving average of closing price in 9 cycle.
Bollinger bands is also based on the statistical principle. The middle rail is calculated according to the N-day moving average, and the upper and lower rails are calculated according to the standard deviation. When the BOLL channel starts changing from wide to narrow, which means the price will gradually returns to the mean. When the BOLL channel is changing from narrow to wide, it means that the market will start to change. If the price is up cross the upper rail, it means that the buying power is enhanced. If the price down cross the lower rail, it indicates that the selling power is enhanced.
Among all the technical indicators, Bollinger Bands calculation method is one of the most complicated, which introduces the concept of standard deviation in statistics, involving the middle trajectory ( MB ), the upper trajectory ( UP ) and the lower trajectory ( DN ). luckily, you don't have to know the calculation details, you can use it directly on FMZ Quant platform as follows:
MID:MA(CLOSE,100); //calculating moving average of 100 cycle, call it Bollinger Bands middle trajectory TMP2:=STD(CLOSE,100); //calculating standard deviation of closing price of 100 cycle. TOP:MID+2*TMP2; //calculating middle trajectory plus 2 times of standard deviation, call it upper trajectory BOTTOM:MID-2*TMP2; //calculating middle trajectory plus 2 times of standard deviation, call it lower trajectory
The MACD indicator is a double smoothing operation using fast (short-term) and slow (long-term) moving averages and their aggregation and separation. The MACD developed according to the principle of moving averages removes the defect that the moving average frequently emits false signals, and also retains the effect of the other good aspect. Therefore, the MACD indicator has the trend and stability of the moving average. It was used to study the timing of buying and selling stocks and predicts stock price change. You can use it as follows:
DIFF:EMA(CLOSE,10)-EMA(CLOSE,50); //First calculating the difference between short-term moving average and long-term moving average. DEA:EMA(DIFF,10); //Then calculating average of the difference.The above is the commonly used strategy module in the development of quantitative trading strategies. In addition, there are far more than that. Through the above module examples, you can also implement several trading modules that you use most frequently in subjective trading. The methods are the same. Next, we began to write a viable intraday trading strategy.
Strategy WritingIn the Forex spot market, there is a wellknown strategy called HANS123. Its logic are basically judging wether the price breaks through the highest or lowest price of the number of K lines after the market opening
// Data Calculation Q:=BARSLAST(DATA<>REF(DATA,1))+1; //Calculating the number of period from the first K line of the current trading day to current k line, and assign the results to N HH:=VALUEWHEN(TIME=0930,HHV(H,Q)); //when time is 9:30, get the highest price of N cycles, and assign the results to HH LL:=VALUEWHEN(TIME=0930,LLV(L,Q)); //When time is 9:30, get the lowest price of N cycles, and assign the results to LL //Placing Orders TIME>0930 AND TIME<1445 AND C>HH,BK; //If the time is greater than 9:30 and lesser than 14:45, and the closing price is greater than HH, opening long position. TIME>0930 AND TIME<1445 AND C
To sum upAbove we have learned the concept of the strategy module. Through several commonly used strategy module cases, we had a general idea of the FMZ Quant programming tools, it can be said that learning to write strategy modules and improve programming logic thinking is a key step in advanced quantitative trading. Finally, we used the FMZ Quant tool to implement the trading strategy according a classical Forex trading strategy.
Next section noticeMaybe there are still some confusion for some people, mainly because of the coding part. Don't worry, we have already thought of that for you. On the FMZ Quant platform, there is another even easier programming tool for beginners. It is the visual programming, let's learn it soon!
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Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful.submitted by getmrmarket to Forex [link] [comments]
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.
Letting stops breatheWe 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 stopAs 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 positionsTake 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 ordersThat 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 ratiosBe 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 returnsNot 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 ratioThe Sharpe ratio works like this:
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.
VARVAR 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 IIIAvailable here
Squeezes and other risks
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.
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Greetings! 👋🏻submitted by VS_community to zyxnetwork [link] [comments]
2020 is likely to be the year that interest in cryptocurrencies reaches the end of 2017. Bitcoin is striving again to historic highs, and altcoins are also growing in price. Let's recall the most common ways to make money on cryptocurrencies.
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The need for a trading strategy in Forex markethttps://preview.redd.it/r6u8stdmeaw51.jpg?width=1320&format=pjpg&auto=webp&s=1b0292502d6e68f5c220af5a5851aeb8061b395b
Almost all trading manuals talk about the need to have your own trading strategy. First of all, the process of creating your trading scheme allows you to perfectly understand trading and exclude from it any eventuality that hides additional risk.
Profitable forex strategy: it is a type of instruction for the trader, which helps to follow a clearly verified algorithm and safeguard his deposit from emotional errors and consequences of the unpredictability of the Forex currency market.Thanks to her, you will always know the answer to the question: how to act in certain market conditions. You have the conditions of opening a transaction, the conditions of its closing, likewise, you do not guess if it is time or not. You do what the trading strategy tells you. This does not mean that it cannot be changed. A healthy trading scheme in the forex market must be constantly adjusted, it must comply with the realities of current market trends, but there must be no unfounded arguments in it.
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Profitable Forex Strategy RedditTypes of trading strategies
The forms of a trading strategy can combine a variety of methods. However, several of the most commonly used options can be highlighted.
Three most profitable Forex strategiesImportant! These strategies are the basis for building your own trading system. Indicator settings and recommended pending order levels are for consultation only. If you do not get a satisfactory outcome in the test result or in a live account, that does not mean that the problem is the strategy. It is enough to choose individual parameters of indicators under a separate asset and under the current market situation.
1. “Bali” scalping strategyThis strategy is one of the most popular, at least its description can be found on many websites. However, the recommendations will be different. According to the author's idea, "Bali" refers to scalping tactics, as it facilitates a fairly short stop loss (SL) and take profit (TP). However, the recommended time frame is high, because the signals appear not very often. The authors recommend using the H1 interval and the EUR / USD currency pair.
The weighted linear moving average here acts as an additional filter. Due to the fact that LWMA gives more weight to the values of the last periods, the indicator in the long periods practically excludes delays. In some cases, LWMA can give a signal beforehand, but in this strategy only the moving position relative to price is important. Bearish LWMA is a buy signal, sell bullish.
The indicator is also based on the moving average, but the formula is slightly different for the calculation. Its marking is more precise (the impact of price noise has been eliminated). It allows you to identify the twists of the trend compared to the usual mobile with a slight anticipation. Trend Envelopes has an interesting property: the color of the line and its new location changes when the price penetrates its old trend line, a kind of signal.
The indicator is placed in a separate window below the chart. This is an oscillator whose task is to determine the pivot points of the trend. And it does so much faster than standard oscillators. It has two lines: the signal is dotted, the additional line is solid, but the receiver has 2 kinds of colors (orange and green).
Also Read: Make Money With Trading
Conditions to open a long position:
The arrow indicates a signal candle where a Trend Envelopes color change occurred. Note (purple ovals) that the blue line is below the orange line and goes upwards (in other cases the signal should be ignored). In the signal candle, the green DSS of momentum line is above the dotted line.
Conditions to open a short position:
Some examples where a transaction cannot be opened:
The signals are relatively rare, a signal can be expected for several days. In half the cases, it is better to control the transaction and close in advance, without waiting for profit taking. We do not operate at the time of flat. Try this strategy directly in the browser and see the result.
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2. “Va-Bank” candle strategyThis profitable Forex strategy is weekly and can be used on different currency pairs. It is based on the spring principle of price movement, what went up quickly, sooner or later must fall. To trade you will only need a schedule on any platform and W1 time frame (although the daily interval can be used).
You should estimate the size of the candle bodies of different currency pairs ( AUDCAD , AUDJPY , AUDUSD , EURGBP , EURJPY , GBPUSD , CHFJPY , NZDCHF , EURAUD , AUDCHF , CADCHF , EURUSD , EURCAD , GBPCHF ) and choose the largest distance from the opening to the close of the candle in the framework of the week. In this to open a transaction at the beginning of the following week.Conditions to open a long position:
On this chart it is clearly seen that after each large bearish candle there is necessarily a bullish candle (although smaller). The only question is what period to take where it makes sense to compare the relative length of the candles. Here everything is individual for each currency pair. Note that a rising candle was observed followed by a few small bearish candles. But when it comes to minimizing risks, it is best not to open a long response position, as the relatively small decline from the previous week may continue.
Conditions to open a short position:
The red arrows point to the candles that had a large body around the previous bullish candles. Almost all signals turned out to be profitable, except for the transactions indicated by a blue arrow. The shortcomings of the strategy are rare signs, albeit with a high probability of profit. The best thing is that it can be used in several pairs at the same time.
This strategy has an interesting modification based on similar logic. Investors with little capital opt for intraday strategies, as their money is insufficient to exert radical pressure on the market. Therefore, if there is a strong move on the weekly chart, this may indicate a cluster of large strong traders. In other words, if there are three weekly candles in one direction, it is most likely the fourth. Here you also have to take into account the psychological factor, 4 candles is equal to one month, and those who "push" the market in one direction, within a month will begin to set profits.
Of the 5 patterns, 4 were effective. Lack of strategy, the pattern can be expected 2-3 months. But when launching a multi-currency strategy this expectation is justified. Consider swaps!
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3. Parabolic Profit Based on Moving AverageThis strategy is universal and is usually given as an example for novice traders. It uses classic EMA (Exponential Moving Average) indicators for MT4 and Parabolic SAR, which acts as a confirmatory indicator.
The strategy is trend. Most sources suggest using it in "minutes", but price noise reduces its efficiency. It is better to use M15-M30 intervals. Currency pairs - Any, but you may need to adjust the indicator settings.
Conditions to open a long position:
This screen shows that all three signals (two long and one short) were effective. It would be possible to enter the market on the candle by following the signal (in order to accurately verify the direction of the trend), but you would then miss the right time to enter. It is up to you to decide whether it is worth the risk. For one-hour intervals, these parameters hardly work, so be sure to check the performance of the indicators for each period of time in a minimum span of three years.
And now that you know the theory, a few words about how to put these strategies into practice.
Ready? Then let's get started!
From the theory to the practiceStep 1. Open demo account It's free, requires no deposit, takes up to 15 minutes, and no verification required. On the main page of your broker there is for sures a button "Register", click and follow the instructions. An account can also be opened from other menus (for example, from the top menu, from the commercial conditions of the account, etc.).
Step 2. Familiarize yourself with the functionality of the Personal Area. It won't take long. It is at the most user friendly and intuitive. You just need to understand the instruments of the platform and understand how the trades are opened.
Step 3. Launch the trading platform. The Personal Area has the platform incorporated, but it is impossible to add templates. Hence, the "Bali" and "Parabolic Profit" strategies can only be executed on MT4.
Characteristics of an effective Forex strategy RedditAnd finally, let's see what makes a profitable Forex strategy effective. What properties should it have? Perhaps three of the most important characteristics can be pointed out.
Conclusion. To successfully trade the Forex currency market, create your own trading strategy. Learn what's new, learn out-of-the-box trading schemes, and improve your individual action plan in the market. Only in this case, the trading results will satisfy you to the fullest. Success, dear readers!
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How exactly did the British manage to diddle us and drain our wealth’ ? was the question that Basudev Chatterjee (later editor of a volume in the Towards Freedom project) had posed to me 50 years ago when we were fellow-students abroad.This is begging the question.
After decades of research I find that using India’s commodity export surplus as the measure and applying an interest rate of 5%, the total drain from 1765 to 1938, compounded up to 2016, comes to £9.2 trillion; since $4.86 exchanged for £1 those days, this sum equals about $45 trillion.This is completely meaningless. To understand why it's meaningless consider India's annual coconut exports. These are almost certainly a surplus but the surplus in trade is countered by the other country buying the product (indeed, by definition, trade surpluses contribute to the GDP of a nation which hardly plays into intuitive conceptualisations of drain).
She [Patnaik] consistently adopts statistical assumptions (such as compound interest at a rate of 5% per annum over centuries) that exaggerate the magnitude of the drainMoving on:
The exact mechanism of drain, or transfers from India to Britain was quite simple.Convenient.
Drain theory possessed the political merit of being easily grasped by a nation of peasants. [...] No other idea could arouse people than the thought that they were being taxed so that others in far off lands might live in comfort. [...] It was, therefore, inevitable that the drain theory became the main staple of nationalist political agitation during the Gandhian era.- Chandra et al. (1989)
The key factor was Britain’s control over our taxation revenues combined with control over India’s financial gold and forex earnings from its booming commodity export surplus with the world. Simply put, Britain used locally raised rupee tax revenues to pay for its net import of goods, a highly abnormal use of budgetary funds not seen in any sovereign country.The issue with figures like these is they all make certain methodological assumptions that are impossible to prove. From Roy in Frankema et al. (2019):
the "drain theory" of Indian poverty cannot be tested with evidence, for several reasons. First, it rests on the counterfactual that any money saved on account of factor payments abroad would translate into domestic investment, which can never be proved. Second, it rests on "the primitive notion that all payments to foreigners are "drain"", that is, on the assumption that these payments did not contribute to domestic national income to the equivalent extent (Kumar 1985, 384; see also Chaudhuri 1968). Again, this cannot be tested. [...] Fourth, while British officers serving India did receive salaries that were many times that of the average income in India, a paper using cross-country data shows that colonies with better paid officers were governed better (Jones 2013).Indeed, drain theory rests on some very weak foundations. This, in of itself, should be enough to dismiss any of the other figures that get thrown out. Nonetheless, I felt it would be a useful exercise to continue exploring Patnaik's take on drain theory.
The East India Company from 1765 onwards allocated every year up to one-third of Indian budgetary revenues net of collection costs, to buy a large volume of goods for direct import into Britain, far in excess of that country’s own needs.So what's going on here? Well Roy (2019) explains it better:
Colonial India ran an export surplus, which, together with foreign investment, was used to pay for services purchased from Britain. These payments included interest on public debt, salaries, and pensions paid to government offcers who had come from Britain, salaries of managers and engineers, guaranteed profts paid to railway companies, and repatriated business profts. How do we know that any of these payments involved paying too much? The answer is we do not.So what was really happening is the government was paying its workers for services (as well as guaranteeing profits - to promote investment - something the GoI does today Dalal (2019), and promoting business in India), and those workers were remitting some of that money to Britain. This is hardly a drain (unless, of course, Indian diaspora around the world today are "draining" it). In some cases, the remittances would take the form of goods (as described) see Chaudhuri (1983):
It is obvious that these debit items were financed through the export surplus on merchandise account, and later, when railway construction started on a large scale in India, through capital import. Until 1833 the East India Company followed a cumbersome method in remitting the annual home charges. This was to purchase export commodities in India out of revenue, which were then shipped to London and the proceeds from their sale handed over to the home treasury.While Roy's earlier point argues better paid officers governed better, it is honestly impossible to say what part of the repatriated export surplus was a drain, and what was not. However calling all of it a drain is definitely misguided.
she [Patnaik] consistently ignores research that would tend to cut the economic impact of the drain down to size, such as the work on the sources of investment during the industrial revolution (which shows that industrialisation was financed by the ploughed-back profits of industrialists) or the costs of empire school (which stresses the high price of imperial defence)
Since tropical goods were highly prized in other cold temperate countries which could never produce them, in effect these free goods represented international purchasing power for Britain which kept a part for its own use and re-exported the balance to other countries in Europe and North America against import of food grains, iron and other goods in which it was deficient.Re-exports necessarily adds value to goods when the goods are processed and when the goods are transported. The country with the largest navy at the time would presumably be in very good stead to do the latter.
The British historians Phyllis Deane and WA Cole presented an incorrect estimate of Britain’s 18th-19th century trade volume, by leaving out re-exports completely. I found that by 1800 Britain’s total trade was 62% higher than their estimate, on applying the correct definition of trade including re-exports, that is used by the United Nations and by all other international organisations.While interesting, and certainly expected for such an old book, re-exporting necessarily adds value to goods.
When the Crown took over from the Company, from 1861 a clever system was developed under which all of India’s financial gold and forex earnings from its fast-rising commodity export surplus with the world, was intercepted and appropriated by Britain. As before up to a third of India’s rising budgetary revenues was not spent domestically but was set aside as ‘expenditure abroad’.So, what does this mean? Britain appropriated all of India's earnings, and then spent a third of it aboard? Not exactly. She is describing home charges see Roy (2019) again:
Some of the expenditures on defense and administration were made in sterling and went out of the country. This payment by the government was known as the Home Charges. For example, interest payment on loans raised to finance construction of railways and irrigation works, pensions paid to retired officers, and purchase of stores, were payments in sterling. [...] almost all money that the government paid abroad corresponded to the purchase of a service from abroad. [...] The balance of payments system that emerged after 1800 was based on standard business principles. India bought something and paid for it. State revenues were used to pay for wages of people hired abroad, pay for interest on loans raised abroad, and repatriation of profits on foreign investments coming into India. These were legitimate market transactions.Indeed, if paying for what you buy is drain, then several billions of us are drained every day.
The Secretary of State for India in Council, based in London, invited foreign importers to deposit with him the payment (in gold, sterling and their own currencies) for their net imports from India, and these gold and forex payments disappeared into the yawning maw of the SoS’s account in the Bank of England.It should be noted that India having two heads was beneficial, and encouraged investment per Roy (2019):
The fact that the India Office in London managed a part of the monetary system made India creditworthy, stabilized its currency, and encouraged foreign savers to put money into railways and private enterprise in India. Current research on the history of public debt shows that stable and large colonies found it easier to borrow abroad than independent economies because the investors trusted the guarantee of the colonist powers.
Against India’s net foreign earnings he issued bills, termed Council bills (CBs), to an equivalent rupee value. The rate (between gold-linked sterling and silver rupee) at which the bills were issued, was carefully adjusted to the last farthing, so that foreigners would never find it more profitable to ship financial gold as payment directly to Indians, compared to using the CB route. Foreign importers then sent the CBs by post or by telegraph to the export houses in India, that via the exchange banks were paid out of the budgeted provision of sums under ‘expenditure abroad’, and the exporters in turn paid the producers (peasants and artisans) from whom they sourced the goods.Sunderland (2013) argues CBs had two main roles (and neither were part of a grand plot to keep gold out of India):
Council bills had two roles. They firstly promoted trade by handing the IO some control of the rate of exchange and allowing the exchange banks to remit funds to India and to hedge currency transaction risks. They also enabled the Indian government to transfer cash to England for the payment of its UK commitments.
The United Nations (1962) historical data for 1900 to 1960, show that for three decades up to 1928 (and very likely earlier too) India posted the second highest merchandise export surplus in the world, with USA in the first position. Not only were Indians deprived of every bit of the enormous international purchasing power they had earned over 175 years, even its rupee equivalent was not issued to them since not even the colonial government was credited with any part of India’s net gold and forex earnings against which it could issue rupees. The sleight-of-hand employed, namely ‘paying’ producers out of their own taxes, made India’s export surplus unrequited and constituted a tax-financed drain to the metropolis, as had been correctly pointed out by those highly insightful classical writers, Dadabhai Naoroji and RCDutt.It doesn't appear that others appreciate their insight Roy (2019):
K. N. Chaudhuri rightly calls such practice ‘confused’ economics ‘coloured by political feelings’.
Surplus budgets to effect such heavy tax-financed transfers had a severe employment–reducing and income-deflating effect: mass consumption was squeezed in order to release export goods. Per capita annual foodgrains absorption in British India declined from 210 kg. during the period 1904-09, to 157 kg. during 1937-41, and to only 137 kg by 1946.Dewey (1978) points out reliability issues with Indian agriculutural statistics, however this calorie decline persists to this day. Some of it is attributed to less food being consumed at home Smith (2015), a lower infectious disease burden Duh & Spears (2016) and diversified diets Vankatesh et al. (2016).
If even a part of its enormous foreign earnings had been credited to it and not entirely siphoned off, India could have imported modern technology to build up an industrial structure as Japan was doing.This is, unfortunately, impossible to prove. Had the British not arrived in India, there is no clear indication that India would've united (this is arguably more plausible than the given counterfactual1). Had the British not arrived in India, there is no clear indication India would not have been nuked in WW2, much like Japan. Had the British not arrived in India, there is no clear indication India would not have been invaded by lizard people,
This article starts from the premise that while economic categories - the extent of commodity production, wage labour, monetarisation of the economy, etc - should be the basis for any analysis of the production relations of pre-British India, it is the nature of class struggles arising out of particular class alignments that finally gives the decisive twist to social change. Arguing on this premise, and analysing the available evidence, this article concludes that there was little potential for industrial revolution before the British arrived in India because, whatever might have been the character of economic categories of that period, the class relations had not sufficiently matured to develop productive forces and the required class struggle for a 'revolution' to take place.A view echoed in Raychaudhuri (1983):
Yet all of this did not amount to an economic situation comparable to that of western Europe on the eve of the industrial revolution. Her technology - in agriculture as well as manufacturers - had by and large been stagnant for centuries. [...] The weakness of the Indian economy in the mid-eighteenth century, as compared to pre-industrial Europe was not simply a matter of technology and commercial and industrial organization. No scientific or geographical revolution formed part of the eighteenth-century Indian's historical experience. [...] Spontaneous movement towards industrialisation is unlikely in such a situation.So now we've established India did not have industrial potential, was India similar to Japan just before the Meiji era? The answer, yet again, unsurprisingly, is no. Japan's economic situation was not comparable to India's, which allowed for Japan to finance its revolution. From Yasuba (1986):
All in all, the Japanese standard of living may not have been much below the English standard of living before industrialization, and both of them may have been considerably higher than the Indian standard of living. We can no longer say that Japan started from a pathetically low economic level and achieved a rapid or even "miraculous" economic growth. Japan's per capita income was almost as high as in Western Europe before industrialization, and it was possible for Japan to produce surplus in the Meiji Period to finance private and public capital formation.The circumstances that led to Meiji Japan were extremely unique. See Tomlinson (1985):
Most modern comparisons between India and Japan, written by either Indianists or Japanese specialists, stress instead that industrial growth in Meiji Japan was the product of unique features that were not reproducible elsewhere. [...] it is undoubtably true that Japan's progress to industrialization has been unique and unrepeatableSo there you have it. Unsubstantiated statistical assumptions, calling any number you can a drain & assuming a counterfactual for no good reason gets you this $45 trillion number. Hopefully that's enough to bury it in the ground.
Perhaps the single greatest and most enduring impact of British rule over India is that it created an Indian nation, in the modern political sense. After centuries of rule by different dynasties overparts of the Indian sub-continent, and after about 100 years of British rule, Indians ceased to be merely Bengalis, Maharashtrians,or Tamils, linguistically and culturally.or see Bryant 2000:
But then, it would be anachronistic to condemn eighteenth-century Indians, who served the British, as collaborators, when the notion of 'democratic' nationalism or of an Indian 'nation' did not then exist. [...] Indians who fought for them, differed from the Europeans in having a primary attachment to a non-belligerent religion, family and local chief, which was stronger than any identity they might have with a more remote prince or 'nation'.
submitted by Tokenomy to tokenomyofficial [link] [comments]
Author: Christian Hsieh, CEO of Tokenomy
This paper examines some explanations for the continual global market demand for the U.S. dollar, the rise of stablecoins, and the utility and opportunities that crypto dollars can offer to both the cryptocurrency and traditional markets.
The U.S. dollar, dominant in world trade since the establishment of the 1944 Bretton Woods System, is unequivocally the world’s most demanded reserve currency. Today, more than 61% of foreign bank reserves and nearly 40% of the entire world’s debt is denominated in U.S. dollars1.
However, there is a massive supply and demand imbalance in the U.S. dollar market. On the supply side, central banks throughout the world have implemented more than a decade-long accommodative monetary policy since the 2008 global financial crisis. The COVID-19 pandemic further exacerbated the need for central banks to provide necessary liquidity and keep staggering economies moving. While the Federal Reserve leads the effort of “money printing” and stimulus programs, the current money supply still cannot meet the constant high demand for the U.S. dollar2. Let us review some of the reasons for this constant dollar demand from a few economic fundamentals.
Demand for U.S. DollarsFirstly, most of the world’s trade is denominated in U.S. dollars. Chief Economist of the IMF, Gita Gopinath, has compiled data reflecting that the U.S. dollar’s share of invoicing was 4.7 times larger than America’s share of the value of imports, and 3.1 times its share of world exports3. The U.S. dollar is the dominant “invoicing currency” in most developing countries4.
This U.S. dollar preference also directly impacts the world’s debt. According to the Bank of International Settlements, there is over $67 trillion in U.S. dollar denominated debt globally, and borrowing outside of the U.S. accounted for $12.5 trillion in Q1 20205. There is an immense demand for U.S. dollars every year just to service these dollar debts. The annual U.S. dollar buying demand is easily over $1 trillion assuming the borrowing cost is at 1.5% (1 year LIBOR + 1%) per year, a conservative estimate.
Secondly, since the U.S. has a much stronger economy compared to its global peers, a higher return on investments draws U.S. dollar demand from everywhere in the world, to invest in companies both in the public and private markets. The U.S. hosts the largest stock markets in the world with more than $33 trillion in public market capitalization (combined both NYSE and NASDAQ)6. For the private market, North America’s total share is well over 60% of the $6.5 trillion global assets under management across private equity, real assets, and private debt investments7. The demand for higher quality investments extends to the fixed income market as well. As countries like Japan and Switzerland currently have negative-yielding interest rates8, fixed income investors’ quest for yield in the developed economies leads them back to the U.S. debt market. As of July 2020, there are $15 trillion worth of negative-yielding debt securities globally (see chart). In comparison, the positive, low-yielding U.S. debt remains a sound fixed income strategy for conservative investors in uncertain market conditions.
Last, but not least, there are many developing economies experiencing failing monetary policies, where hyperinflation has become a real national disaster. A classic example is Venezuela, where the currency Bolivar became practically worthless as the inflation rate skyrocketed to 10,000,000% in 20199. The recent Beirut port explosion in Lebanon caused a sudden economic meltdown and compounded its already troubled financial market, where inflation has soared to over 112% year on year10. For citizens living in unstable regions such as these, the only reliable store of value is the U.S. dollar. According to the Chainalysis 2020 Geography of Cryptocurrency Report, Venezuela has become one of the most active cryptocurrency trading countries11. The demand for cryptocurrency surges as a flight to safety mentality drives Venezuelans to acquire U.S. dollars to preserve savings that they might otherwise lose. The growth for cryptocurrency activities in those regions is fueled by these desperate citizens using cryptocurrencies as rails to access the U.S. dollar, on top of acquiring actual Bitcoin or other underlying crypto assets.
The Rise of Crypto DollarsDue to the highly volatile nature of cryptocurrencies, USD stablecoin, a crypto-powered blockchain token that pegs its value to the U.S. dollar, was introduced to provide stable dollar exposure in the crypto trading sphere. Tether is the first of its kind. Issued in 2014 on the bitcoin blockchain (Omni layer protocol), under the token symbol USDT, it attempts to provide crypto traders with a stable settlement currency while they trade in and out of various crypto assets. The reason behind the stablecoin creation was to address the inefficient and burdensome aspects of having to move fiat U.S. dollars between the legacy banking system and crypto exchanges. Because one USDT is theoretically backed by one U.S. dollar, traders can use USDT to trade and settle to fiat dollars. It was not until 2017 that the majority of traders seemed to realize Tether’s intended utility and started using it widely. As of April 2019, USDT trading volume started exceeding the trading volume of bitcoina12, and it now dominates the crypto trading sphere with over $50 billion average daily trading volume13.
An interesting aspect of USDT is that although the claimed 1:1 backing with U.S. dollar collateral is in question, and the Tether company is in reality running fractional reserves through a loose offshore corporate structure, Tether’s trading volume and adoption continues to grow rapidly14. Perhaps in comparison to fiat U.S. dollars, which is not really backed by anything, Tether still has cash equivalents in reserves and crypto traders favor its liquidity and convenience over its lack of legitimacy. For those who are concerned about Tether’s solvency, they can now purchase credit default swaps for downside protection15. On the other hand, USDC, the more compliant contender, takes a distant second spot with total coin circulation of $1.8 billion, versus USDT at $14.5 billion (at the time of publication). It is still too early to tell who is the ultimate leader in the stablecoin arena, as more and more stablecoins are launching to offer various functions and supporting mechanisms. There are three main categories of stablecoin: fiat-backed, crypto-collateralized, and non-collateralized algorithm based stablecoins. Most of these are still at an experimental phase, and readers can learn more about them here. With the continuous innovation of stablecoin development, the utility stablecoins provide in the overall crypto market will become more apparent.
Institutional DevelopmentsIn addition to trade settlement, stablecoins can be applied in many other areas. Cross-border payments and remittances is an inefficient market that desperately needs innovation. In 2020, the average cost of sending money across the world is around 7%16, and it takes days to settle. The World Bank aims to reduce remittance fees to 3% by 2030. With the implementation of blockchain technology, this cost could be further reduced close to zero.
J.P. Morgan, the largest bank in the U.S., has created an Interbank Information Network (IIN) with 416 global Institutions to transform the speed of payment flows through its own JPM Coin, another type of crypto dollar17. Although people argue that JPM Coin is not considered a cryptocurrency as it cannot trade openly on a public blockchain, it is by far the largest scale experiment with all the institutional participants trading within the “permissioned” blockchain. It might be more accurate to refer to it as the use of distributed ledger technology (DLT) instead of “blockchain” in this context. Nevertheless, we should keep in mind that as J.P. Morgan currently moves $6 trillion U.S. dollars per day18, the scale of this experiment would create a considerable impact in the international payment and remittance market if it were successful. Potentially the day will come when regulated crypto exchanges become participants of IIN, and the link between public and private crypto assets can be instantly connected, unlocking greater possibilities in blockchain applications.
Many central banks are also in talks about developing their own central bank digital currency (CBDC). Although this idea was not new, the discussion was brought to the forefront due to Facebook’s aggressive Libra project announcement in June 2019 and the public attention that followed. As of July 2020, at least 36 central banks have published some sort of CBDC framework. While each nation has a slightly different motivation behind its currency digitization initiative, ranging from payment safety, transaction efficiency, easy monetary implementation, or financial inclusion, these central banks are committed to deploying a new digital payment infrastructure. When it comes to the technical architectures, research from BIS indicates that most of the current proofs-of-concept tend to be based upon distributed ledger technology (permissioned blockchain)19.
These institutional experiments are laying an essential foundation for an improved global payment infrastructure, where instant and frictionless cross-border settlements can take place with minimal costs. Of course, the interoperability of private DLT tokens and public blockchain stablecoins has yet to be explored, but the innovation with both public and private blockchain efforts could eventually merge. This was highlighted recently by the Governor of the Bank of England who stated that “stablecoins and CBDC could sit alongside each other20”. One thing for certain is that crypto dollars (or other fiat-linked digital currencies) are going to play a significant role in our future economy.
Future OpportunitiesThere is never a dull moment in the crypto sector. The industry narratives constantly shift as innovation continues to evolve. Twelve years since its inception, Bitcoin has evolved from an abstract subject to a familiar concept. Its role as a secured, scarce, decentralized digital store of value has continued to gain acceptance, and it is well on its way to becoming an investable asset class as a portfolio hedge against asset price inflation and fiat currency depreciation. Stablecoins have proven to be useful as proxy dollars in the crypto world, similar to how dollars are essential in the traditional world. It is only a matter of time before stablecoins or private digital tokens dominate the cross-border payments and global remittances industry.
There are no shortages of hypes and experiments that draw new participants into the crypto space, such as smart contracts, new blockchains, ICOs, tokenization of things, or the most recent trends on DeFi tokens. These projects highlight the possibilities for a much more robust digital future, but the market also needs time to test and adopt. A reliable digital payment infrastructure must be built first in order to allow these experiments to flourish.
In this paper we examined the historical background and economic reasons for the U.S. dollar’s dominance in the world, and the probable conclusion is that the demand for U.S. dollars will likely continue, especially in the middle of a global pandemic, accompanied by a worldwide economic slowdown. The current monetary system is far from perfect, but there are no better alternatives for replacement at least in the near term. Incremental improvements are being made in both the public and private sectors, and stablecoins have a definite role to play in both the traditional and the new crypto world.
 How the US dollar became the world’s reserve currency, Investopedia
 The dollar is in high demand, prone to dangerous appreciation, The Economist
 Dollar dominance in trade and finance, Gita Gopinath
 Global trades dependence on dollars, The Economist & IMF working papers
 Total credit to non-bank borrowers by currency of denomination, BIS
 Biggest stock exchanges in the world, Business Insider
 McKinsey Global Private Market Review 2020, McKinsey & Company
 Central banks current interest rates, Global Rates
 Venezuela hyperinflation hits 10 million percent, CNBC
 Lebanon inflation crisis, Reuters
 Venezuela cryptocurrency market, Chainalysis
 The most used cryptocurrency isn’t Bitcoin, Bloomberg
 Trading volume of all crypto assets, coinmarketcap.com
 Tether US dollar peg is no longer credible, Forbes
 New crypto derivatives let you bet on (or against) Tether’s solvency, Coindesk
 Remittance Price Worldwide, The World Bank
 Interbank Information Network, J.P. Morgan
 Jamie Dimon interview, CBS News
 Rise of the central bank digital currency, BIS
 Speech by Andrew Bailey, 3 September 2020, Bank of England
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