Forex Course

192. Criteria To Carry Trade The Forex Market and Risks Involved


In the previous lesson, we discussed instances when a carry can work, and when it’s bound to fail. But, having this knowledge won’t be of much help if you do not know the best criteria for a currency carry trade and the risks involved.

Criteria to Carry Trade

There are two basic criteria to carry trade the Forex market profitably.

The interest rate differential between two currency pairs needs to be high with no prospects of reducing in the near term.

The currency pair that we choose has to be on a bullish trend in favor of the currency with the higher interest rate. The reason for this is to ensure you can remain bullish on the high yielding currency and profit from the interest rate differential for the longest possible time.

Let’s take the example of the AUD/JPY pair. Japan’s interest rate has remained at -0.1%, while in Australia was held at 0.25%. That means the interest rate differential between the AUD/JPY pair has been 0.35%. Therefore, if you were to borrow and sell the JPY to buy the AUD, you’d expect a pay-out of 0.35%. Note that this is the same as going long on the AUD/JPY pair.

In this scenario, going long on AUD/JPY from March 2020 to October 2020 would have earned you over 900 pips. At the same time, you’d be earning an interest rate differential of 0.35%.

Risks Involved In Carry Trading

So far, a carry trade sounds like a risk-free strategy. But, like any other investment, the carry trade has its fair amount of risks – especially when leverage is involved.

Remember, in the previous lesson, we mentioned two conditions for a carry trade to thrive. First, there had to be low volatility in the market. The reason for this is to ensure that your open position is not wiped out due to currency fluctuations before you reap the profits of interest rate differential. Note that using trailing stop orders can help mitigate the risk of price fluctuations in the forex market.

The second condition for a carry trade to thrive was the stable economic conditions that might encourage the hiking of interest rates. If the economic climate is full of uncertainties, like with the ongoing coronavirus pandemic, central banks are more likely to cut interest rates than hike them. Therefore, if extreme interest rate cuts occur while you are in a currency carry trade, it could result in losses. 

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Forex Daily Topic Forex Risk Management

Position Size Risk and System Analysis


Some authors label this topic as Money Management or Risk Management, but this misses the point. Money Management doesn’t tell much about what it does, and Risk Management seems more related to risk, which has been discussed on the subject of cutting losses short and let profits run.

However, Van K. Tharp has hit the point: He calls it position sizing, and it tells us how much to trade on every trade and how this is related to our goal settings and objectives.

1.    Risk and R

In his well-known book Trade your Way to your Financial Freedom, Van K. Tharp says that a key principle to success in trading is that the investor should always know his initial risk before entering a position.

He suggests that this risk should be normalized, and he calls it R. Your profits must also be normalized to a multiple of R, our initial risk.

The risk on one unit is a direct calculation of the difference in points, ticks, pips, or cents from the entry point to the stop-loss multiplied by the value of the minimum allowed lot or pip.

Consider, for example, the risk of a micro-lot of the EUR/USD pair in the following short entry:

        Size of a micro-lot: 1,000 units
                Entry point: 1.19344
                  Stop loss: 1.19621
Entry to stop-loss distance: 0.00277

Dollar Risk for one micro-lot: 0.00277 * 1,000 = $ 2.77
In this case, if the trader had set his $R risk – the amount he intends to risk on a trade – to be $100, what should be his position size?

Position size: $100/$2.77= -36 micro-lots (it’s a short trade)

Using this concept, we can standardize our position size according to the particular risk. For instance, if the unit risk in the previous example were $5 instead, the position size would be:

$100/5 = 20 micro-lots.

We would enter a position with a standard and controlled risk independent of the distance from entry to stop.

2.    Profit targets as multiples of R

Our profits can be normalized as multiples of the initial risk R. It doesn’t matter if we change our dollar risk from $100 to $150. If you keep our records using R multiples, you’ll get a normalized track record of your system.

With enough results, you’ll be able to understand how your system performs and, also, able to measure its statistical characteristics and its quality.

Values such as Expectancy (E), mean reward to risk ratio(RR), % of gainers, the number of R gains a system delivers (R multiple) in a day, week, month or year.

Knowing these numbers is very critical because it will help us to achieve our objectives.

You already know what Expectancy (E) is. But the beauty of this number is that, together with the average number of trades, it tells you the R multiple your system delivers in a time interval.

For example, let’s say you’ve got a system that takes six trades a day, and its E is 0.45R. This means it makes $0.45 per dollar risked.

 That means that the system also delivers an average of 0.45×6R=2.7R per day and that, on average, you’d expect, monthly, 54R.

Let’s say you wanted to use this system, and your monthly goal is  $6,000. What would your risk per trade be?

To answer this, you need to equate 54R = $6000

So your risk per trade should be set to:

R= 6000/60 = $111.

Now you know, for instance, that you could achieve $12,000/month by doubling our risk to $222 per trade and $24,000 if you can raise your risk to $444 per trade. You have converted a system into an exponential money-making machine, but with a risk-controlled attitude.

3.    Variability of the results 

As traders, we would like to know, also, what to expect from the system concerning drawdowns.

Is it normal to have 6, 10, 15, or 20 consecutive losses? And, what are the chances of a string of them to happen? Is your system misbehaving, or is it on track?
That can be answered, too, using the % of losers (PL).

Let’s consider, as an example, that we have a system with 50% winners and losers.

We know that the probability of an event A and an event B happening together is the probability of A happening times the probability of B happening:

ProbAB = ProbA * ProbB

For a string of losses, we have to multiply the probability of a loss by itself the number of times the streak duration.

So for a n streak:

Prob_Streak_n = PL to the power of n = PLn

As an example, the probability of 2 consecutive losses for the system of our example is:

Prob_Streak_2 = 0.52
= 0.25 or 25%

And the probability of suffering 4 consecutive losses will be:

Prob_Streak_4 = 0.54
= 0.0625 or 6.25%

For a string of six losses is:

Prob_Streak_6 = 0.56
= 0.015625, or 1.5625%

And so on.

This result is in direct relation to the probability of ruin. If your R is such that a string of six losses wipes 100% of your capital, there is a probability of 1.56% for that to happen under this system.

Now we learned that we must set our dollar risk R to an amount such that a string of losses doesn’t bring the account beyond the maximum percent drawdown that is tolerable to the trader.

What happens if the system has 40% winners and 60% losers, as is usual on reward/risk systems? Let’s see:

Prob_Streak_2 = 0.62 = 36%

Prob_Streak_4 = 0.64 = 12.96%

Prob_Streak:6 = 0.66 = 4,66%

Prob_Streak_8 = 0.68 = 1.68% 

We observe that the probability of consecutive streaks of the same magnitude increases, so now the likelihood of eight straight losses in this system has the same probability as six in the former one.

This means that with systems with a lower percentage of winners, we should be more careful and reduce our maximum risk compared to a system with higher winning ratios.

As an example, let’s do an exercise to compute the maximum dollar risk for this system on a $10,000 account and a maximum tolerable drawdown of 30%. And assuming we wanted to withstand eight consecutive losses (a 1.68% probability of it to happen, but with a 100% probability of that to occur throughout a trader’s life).

According to this, we will assume a streak of eight consecutive losses, or 8R.

30% of $10,000 is $3,000

then 8R = $3,000, and

max R allowed is: 3000/8 = $375 or 3.75% of the account balance.

As a final caveat, to get an accurate enough measure of the percentage of losers, we should have more than 100 samples on our system history (forward tested, if possible, since back-tests usually presents unrealistic results). With just 30 points, the data is not representative enough to get any fair result.

You could do the same computations for winning streaks, using the percent of winners instead, and multiplying by the average reward (R multiple).

1.    Key points and conclusions

  • Position sizing is the part of the system that tells us how much to risk on a trade and is directly relevant to fulfilling our goals
  • The unit of risk R is a normalized symbol for dollar risk
  • You should measure, register, and be aware of the main statistical parameters of your systems: Expectancy, Percent winners and losers, reward to risk ratio, and the mean monthly-R (the average number of R your system achieves in one month)
  • You should compute the maximum R allowed by your system and account size for the max drawdown bearable for you, and not bet more than that amount.


Forex Course

166. Introduction To Obscure Currency Crosses & Why It Is Very Risky To Trade Them?


Trading currency crosses an excellent way to make money from forex trading when major currency pairs do not make a good move due to the US economy’s corrective momentum. However, the US dollar is a global reserve currency of every country. Therefore, it can provide enough liquidity to make money where the obscure currency crosses have some risks due to insufficient liquidity.

What is Obscure Currency Cross?

We can find currency crosses when we eliminate the US dollar from major and commodity currencies. However, among the cross currencies, the Euro and the Japanese Yen are mostly traded. Therefore, if you trade any Euro and Yen related cross pair, you might see the price to have adequate liquidity. But, what happens if the currency cross does not have Yen or Euro?

Any cross currency pairs that do not have Japanese Yen or Euro as a first or second currency is called an Obscure currency cross. Examples of obscure currency crosses are GBPCHF, NZDCAD, AUDCHF, CADCHF, NZDCHF, NZDCAD, etc.

Why are Trading Obscure Currency Crosses Risky?

The forex market is run through a decentralized network where no one can dominate any market. Therefore, the movement of a currency pair depends on the supply and demand of that currency pair. When the supply or demand increases, the currency pair starts to move. On the other hand, when there is less volume, the currency pair may move within a correction.

The liquidity remains lower in the obscure currency pair than major, commodity, and EUR/YEN related currency pairs. Therefore, there is a risk of market volatility and correction. In some cases, obscure currency pairs consolidate for a long time, and if we take any trade on that pair, we might have to hold the trade for a considerable time.


In conclusion, we can say that trading obscure currency pairs have some reason to worry due to not having enough liquidity to provide a decent movement. However, it is a great way to make money from obscure currency pairs if we can read the price action well and identify the price is moving within a trend. Overall, maintaining a profitable and robust trading strategy is the key to make a consistent profit from the forex market.

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Forex Videos

Position Sizing IX: Improving the Percent Risk Model-Playing with market’s money


Position Sizing IX: Improving the Percent Risk Model-Playing with market’s money


One way to improve the returns of a position sizing strategy without increasing our capital risk is to play with the market’s money. In this video, we are going to develop this idea as a way to improve the percent-risk model.

The market’s money

We define as “market’s money” the gains resulting from the profits of previous trade or winning streak. This is a mentality shift. Instead of viewing recent profits as your own money, you momentarily consider them as a gift of the market to increase the trading size riskless. This has a slight resemblance to moving your stops to break even and let the trade go on. After that action, the rest of the trade evolution is riskless. The concept of the market’s money is especially attractive when the trading strategy has a high percentage of winners because high probability strategies show a higher likelihood of winning streak versus losing streaks.
There are several ways to use this concept, but in this video, we will focus our attention on its use with the Percent-risk model. Precisely, we will use the money gained in the previous successful trades to increase the size of the next trade without increasing the risk of our base money.

The N-Step up position Sizing Strategy

The N-Step-up method uses the N previous successful trades’ gains to increase the size of the next trade. After N trades, the profit is added to the general wallet, to start a new cycle. If there is a loss, the cycle resets and begins again.

The flowchart of this methodology is shown below.
The key idea is that, even when it ends at a loss in the N step, the risk incurred is the only the risk made in the starting position, But if the N-cycle ends as a win, on a 1R reward/risk situation, it will end up with R+2R+3R+… NR gains. On a 2R reward/risk strategy, it will be 2R+6R+ 14R +…
We will try this methodology using the Live Signals Service performance and 1% basic risk to see how the N-Step Up improves it.

Original 1% Strategy

The graph below shows the equity curve growth using a 1% risk over one year of trading, assuming 2 daily trades on average.

When we use Monte Carlo resampling to get 10,000 different 1-year histories, we get the following information.

Average ending Capital: 75,359.86
Max ending Capital : 219,145.26
Min ending Capital: 26,811.62

Probability of Capital ending above 78,604: 43.98 %
Probability of Capital ending above 26,812: 99.99 %
Probability of Capital ending above 10,000: 100.00 %

In the figure below, we can see the likelihood of max drawdown for the 1% Risk model:

Average Max Drawdown: 8.02 %
Maximum Max Drawdown: 27.46 %
Min Max Drawdown: 3.67 %

Probability of a 10% drawdown: 15.44%
Probability of a 20& drawdown: 0.03%
Probability of a 30% drawdown: 0.00%

We can see that the expected max drawdown is 8.38%, with a one in five years ending at 10% and almost no chance to reach 20 percent. Let’s see how this can be improved with one, two, and three N-Step cycles.

The below chart shows the original, plus 1-, 2- and 3-step up position sizing strategies, using semi-log scales to make them fit together in a single chart.

We can see that the advantage of using the methodology is evident, as the 3-Step-up sizing strategy reaches an ending capital of up to one order of magnitude higher (10X), as compared to the basic 1% Risk method.

Let’s see how they perform regarding returns and drawdowns:

1-Step Up Return Stats:

Average ending Capital: 236,427.55
Max ending Capital : 1,306,952.10
Min ending Capital: 34,015.66

1-Step Up Drawdown figures:

Average Max Drawdown: 13.29 %
Maximum Max Drawdown: 33.94 %
Min Max Drawdown: 5.64 %

Probability of a 10% drawdown: 86.21%
Probability of a 20& drawdown: 4.15%
Probability of a 30% drawdown: 0.00%

2-Step Up Return Stats:

Average ending Capital: 625,846.08
Max ending Capital : 8,601,130.02
Min ending Capital: 53,941.54

2-Step Up Drawdown figures:

Average Max Drawdown: 18.02 %
Maximum Max Drawdown: 43.04 %
Min Max Drawdown: 8.31 %

Probability of a 10% drawdown: 99.59%
Probability of a 20& drawdown: 28.29%
Probability of a 30% drawdown: 0.03%

3-Step Up Return Stats:

Average ending Capital : 1,597,715.25
Max ending Capital : 34,224,341.81
Min ending Capital: 53,439.67

3-Step Up Drawdown figures:

Average Max Drawdown: 22.52 %
Maximum Max Drawdown: 58.01 %
Min Max Drawdown: 9.79 %

Probability of a 10% drawdown: 99.99%
Probability of a 20& drawdown: 64.23%
Probability of a 30% drawdown: 0.63%

A variation of this strategy could be made by re-investing only 50% of the profits. This method will significantly lower the returns, although it will also smooth the equity curve. As an example, let’s see the reward and risk figures of a 3-Step Up with 50% reinvestment:

Average ending Capital: 199,952.02
Max ending Capital : 1,181,977.34
Min ending Capital: 34,950.58


Average Max Drawdown: 12.10 %
Maximum Max Drawdown: 31.89 %
Min Max Drawdown: 5.37 %

Probability of a 10% drawdown: 74.30%
Probability of a 20& drawdown: 1.94%
Probability of a 30% drawdown: 0.00%

We can see that this method is quite similar in performance and drawdown to the 1-Step Up with 100% re-investment, but is not worthwhile, since it reduces the returns to half, while drawdown is only lowered from 13.29% to 12.1%.


We can see that even 1-Step up improves substantially the performance of a strategy (about 4X) with only an increase in the drawdown from 8.% to 13.3%.
We can see also that the best choice for this strategy is 2-Step Up, with a balanced mix returns (average ending equity of $625,846 over an average Max Drawdown of 18%); this is a 10X improvement from the basic 1% sizing strategy with only about 2.2X of drawdown. But, aggressive traders may choose the 3-Step Up strategy, which doubles the 2-Step Up model’s returns with an increase in drawdown from 18% to just 22.5% ( a 25% increment).

Forex Daily Topic Forex Price-Action Strategies

Forex Price Action: A Losing Trade

Forex trading is considered one of the riskiest businesses. The market is volatile and it gets unpredictable from time to time. There is no trading strategy, which can guarantee one hundred per cent success. Thus, Forex traders must be mentally prepared to take losses. In today’s lesson, we are going to demonstrate an example of a losing trade.

The chart shows that the price upon finding its resistance heads towards the South with good bearish momentum. The first candle comes out as a bearish engulfing candle followed by two bearish candles. These suggest that the bear takes control. The sellers are to wait for the price to consolidate and a bearish engulfing candle to go short in the pair. Let us proceed to the next chart to find out what the price does.

The price finds its support. It produces a bullish inside bar followed by two doji candles. It seems that the price has been searching for its resistance. The sellers are to keep their eyes on this chart.

The price finds its resistance. It produces a bearish engulfing candle closing below consolidation resistance. Without any doubt, this is an A+ breakout candle. The sellers may trigger a short entry right after the candle closes by setting stop loss above consolidation resistance and by setting take profit with 1R. Let us find out how the trade goes.

It looks fantastic for the sellers. The next candle comes out as a bearish candle as well. Consecutive two bearish candles suggest that the bear is in a hurry to hit the take profit. The sellers may not have to wait too long to achieve their target as far as the price action in this chart is concerned.

Would you believe it? The next candle comes out as an inverted hammer. The upper shadow hits the stop loss. The sellers are out with their entry with a loss. That was beyond their imagination some might say. However, it happens a lot in the Forex market. Thus, traders must not be overconfident with any entry. Discipline and money management are to be maintained with every single trade.

Some traders, especially at the beginning can’t take losses easily. It bugs them up. Losing money may make them think something is wrong with their strategy. There is nothing wrong if traders want to try to develop new strategies. However, they should not just lose the belief and abandon a long proven strategy all of a sudden.

Crypto Daily Topic Forex Price Action

Calculate Risk-Reward along with Candle’s Attributes

In today’s lesson, we are going to demonstrate an example of the importance of risk-reward. To be successful in price action trading, traders are to calculate risk-reward before every single entry they execute. Let us find out from the charts below the importance of risk-reward.

The price heads towards the South with an average bearish momentum. Ideally, it is the sellers’ territory. However, it has come a long way. The buyers must wait for a strong bullish reversal candle to go long on this chart.

This is an extremely strong bullish reversal candle. The buyers may wait for the price to consolidate and produce a bullish reversal candle. Within a candle, things are very different now.

The chart produces a bearish inside bar. Thus, buyers may get more optimistic. They are to wait for a bullish engulfing candle closing above the last swing high to trigger a long entry. The price may travel towards the drawn level, which is a significant level of resistance on the chart.

The chart produces a bullish engulfing candle closing well above the last resistance. As explained earlier, the buyers are to set their stop loss below the last candle and trigger a short entry right after the candle closes. The question is whether they shall take a long entry here or not. Think about it. The last candle closes within the level of resistance. Technically, there is no space for the price for traveling towards the North unless it makes another breakout here. The reward is zero here.

As anticipated, the price consolidates again and struggles to make another breakout. The last candle comes out as a bearish candle. Thus, things do not look good for the buyers. It may change its direction. If it makes a bullish breakout, that is another ball game, though. Let us proceed to the next chart.

The price does not make a bullish breakout but changes its trend. It is the sellers’ territory again. By looking at the last candle, the sellers may trigger a short entry by setting their take profit at the last swing low.

In this lesson, we have seen that the trend-initiating candle and the signal candle both get 10 on 10. However, the chart does not offer an entry because there is no space for the price for traveling towards the upside. Consequently, the sellers take over and drive the price towards the downside. To sum up, we not only look at the candle’s attributes but also calculate risk-reward.

Forex Videos

Forex Risk VS Sentiment – Bad News For The Pound!

Risk versus Sentiment

Traders interpret technical analysis on their screen charts in many ways, such as price action. But they are always reading between the lines in terms of perceived risk and sentiment, which may have little bearing in the price of a currency pair before an important event.
One such event, as in Example A, is a screenshot of a one hour chart of the GBPUSD pair on the 6th of December 2019. The British people were voting this day on an election, which would have a strong bearing with regard to Britain’s possible exit from the European Union: Brexit.

In the example, we can see that just before exit poll information was released at 10 p.m. GMT, the pair began to fall, was being sold off. This was due to perceived risk That Boris Johnson’s conservative government would not win the election, and therefore allowing labor to potentially win and where their pledges of heavy government borrowing were perceived by the traders as being bad news for the pound.

However, the exit polls indicated that the conservative government would win with a major majority the pound surged to over 1.350. When the dust began to settle, and some profit-taking took place, risk began to unnerve traders, who perceived that although Brexit was likely to happen now, the government might not be able to get all of the necessary laws in place for this to happen within the designated time frame to complete all of these laws and to broker a new trade deal with the European Union by December 2020. Therefore the pound began to fall again.
As a trader, it is imperative that when you see a major political event unfold, such as this one, that you fully understand what is going on at the time of the event, and not just afterwards, because By fully understanding the risks that are involved in such an event it will create an opportunity for you to make money.

However, many traders, in fact, did lose money trading this event because they were not fully appreciative of the risks involved. Not only the GBPUSD pair but also to other currencies, for example, the strength and weakness of the US dollar at the time of the event and also other currencies such as the Yen, Swiss Franc and the Euro, which were also being traded against the pound at this time.

Therefore during technical analysis, while traders depend on technical tools such as the MACD Stochastics and price action, it is imperative that traders are also mindful, and especially when it comes to major political events, with regard to perceived risk and sentiment.

Forex Daily Topic Forex Videos

How To Succeed In Forex – Why Knowing your Strategy parameters makes sense


Why Knowing your Strategy parameters makes sense

Usually, traders’ interest focus on entries. Forecasting seems to them a crucial skill for succeeding in the Forex market, and they think other topics are secondary or even irrelevant. They are deadly wrong. Entries are no more than 10 percent of the success of a trader, while risk management and position sizing are crucial elements that the majority of traders discard as uninteresting. Let us show why risk can be such an exciting topic for people willing to improve in their trading job.

Making sure our strategy is a winner

There are two ways to trade The good one and the bad one. The good one is when the trader fully knows the main parameters of his system or strategy. The bad one is when not.
So, why do we need to know the parameters to be successful? The short answer is that it is
Firstly, to know if the system has an edge (profitable long-term).

Secondly, by knowing the parameters, we will know how much we can risk on each trade.
And thirdly, and no less important, by identifying these parameters, we can more easily define the monetary objectives and overall risk (drawdown).

Good, let’s begin!

The two main parameters of a strategy or system!

To fully identify a strategy, we need just two parameters. The rest of them can be derived from these two with or without the position size. The parameters in question are the percent of winning trades and the Reward-to-risk ratio.
Mathematical Expectancy (ME)
With these two parameters, we can estimate if the system is a winner or a loser using the following simple formula, defining the player’s edge: ME = (1 + A)*P -1

Where P is the probability of winning and A is the amount won. The formula assumes that A is constant since this formula came from gambling. Still, we can very much approximate the results is A is our average winning amount, or even better, the Reward-to Risk Ratio.

As an example let’s assume our system shows 45% winners with a winning amount two times its risk
ME = (1+2)*0.45 -1
ME = 0.35
The mathematical Expectancy (ME) expressed that way, shows the expected return on each trade per dollar risked. In this case, it is 35 cents per dollar risked.

Planning for the monetary objectives
Once we know ME, it is easy to know the daily and weekly returns of the strategy. To do it, another figure we should know, of course, the frequency of trades of the strategy. Let’s assume the strategy is used intraday on four major pairs delivering one trade per pair per day. That means, the system’s daily return (DR) will be 4XME dollars per day per dollar risked, while monthly returns (MR) will be that amount times 20 trading days:

DR = 4 x ME = 4 x 0.35 = 1.4
MR = 20xDR = 20 x 1.4 = 28

Therefore, a trader risking $100 per trade would get $2,800 monthly on average.
That is great! By defining our monthly objectives, once knowing ME and the number of trades the system delivers daily or monthly, we can determine the risk incurred. For example, another bolder trader would like to triple that amount by tripling the risk on each trade. Why not a ten-fold or a hundred-fold risk to aim for 280K monthly income?


That touches the dark side of trading, which is drawdown. Drawdowns are the result of the combination of the probability of losing of the trading system and the amount lost. Drawdowns are unavoidable because a system always shows losing streaks. Therefore, any trader must make sure that streak does not burn his trading account.

The risk of ruin increases as the trade size grows, so there is a rational limit to the size we should trade if we want to keep safe our hard-earned money.
As a basic method to be on the safe side, a trader must first decide how much of his account is willing to accept as drawdown, and from there, use as trade size a percent of the total balance which satisfies that condition of maximum drawdown.

Let’s do an example

Let’s say a trader using the previous strategy will not accept to lose more than 25 percent of his funds. As an approximation to this drawdown, we can think of a losing streak of 10 consecutive trades, an event with 0.35% probability of happening. Which is the trade size suitable to comply with these premises?
Trade Size = MaxDD% / 10
Trade Size = 25% / 10 = 2.5%
That gives us the reasonable trade size for this particular trader. If another trader is not willing to risk more than 10%, then his trade size should be 1%. Once this quantity is known, the trader only has to compute the dollar value by multiplying by the current balance.

Resetting the objectives

Let’s assume the balance is $5,000, then the max risk per trade allowed is $ 125. That means we could expect a monthly return of about $3,500 on the previously discussed strategy for a max drawdown of no more than 25%. If the trader would like to earn $7,000 instead, he should add another $5,000 to the account to guarantee a 25% drawdown or accept a 50% drawdown and risking $250.

Final words

Please, note that this is just an example and that sometimes the trade size is limited by the allowed leverage and other conditions. Also, note that trading the Forex market is risky. Therefore, please start slow. It is better to begin by risking 0.5% and see how your strategy develops and the drawdowns involved.

The first measure you must take is creating a spread-sheet annotating all your trades, including entry, exit, profit/loss, and risk per trade. Then compute your strategy parameters on a weekly basis. This is a serious business, and we should be making our due diligence and keep track of the evolution of our trade system or systems.

Forex Market Forex Risk Management

These Are Some Of The Best Position Sizing Techniques You Should Know!


In our previous article, we addressed the concept of position sizing, drawdown, and techniques. Now we extend this discussion and look at other crucial aspects of position sizing, which are very important. In this article, let’s determine how one can position themselves in the forex market based on three different models. Each of these has its own merits that impose some sort of position sizing discipline in traders.

The three core position sizing techniques in terms of risk are:

  • Fixed lot per amount
  • Percentage margin
  • Degree of volatility

These models can be applied to all the asset classes and are time frame independent.

We suggest you stick to one model to estimate the position size or at most two position sizing techniques. Following every given method will increase complexity, and that is not good for a trader.

Fixed Lot Per Amount

This is a fairly simple model. It requires a trader to simply state how many lots he is willing to trade for a given amount of capital. For example, let us assume a trader is having $2000 in his trading account, and he trades only the major currency pairs like  EUR/USD, GBP/USD, GBP/JPY, USD/JPY, etc.

The trader simply needs to make a thumb rule that he/she will not trade more than one standard lot of futures (of major currency pairs) per $2000 at any given point.

The lot size can also be determined based on their risk appetite and money management principles. This technique of ‘fixed risk’ is based more on the discipline than strategy.

Percentage Margin

This position sizing technique is more structured than the ‘Fixed lot per amount’ technique, especially for intraday traders. It requires a trader to position themself based on the margin. Here, a trader essentially fixes an ‘X’ percentage of their capital as margin amount to any particular trade. Let’s see how this works with the help of an example.

Assume a trader named Tim has a trading capital of $5000; with this, he decides not to expose more than 20% as margin amount on a particular trade. This translates to a capital of $1000 per trade.

Now, if Tim gets an opportunity in another currency pair, he would be forced to let go of this margin as it would double to 40% (20% + 20%). This new opportunity will be out of his trading universe until and unless he increases his trading capital. Hence, one should not randomly increase the margin to accommodate opportunities.

The percentage margin ensures a trader pays roughly the same margin to all positions irrespective of the forex pair and volatility. Otherwise, they would end up in risky bets and therefore altering the entire risk profile of their account.

Degree Of Volatility

The degree of volatility accounts for the volatility of the underlying asset. To measure volatility, we make use of the ATR indicator, as suggested by Van Tharp. This position sizing technique defines the maximum amount of volatility exposure one can assume for the given trading capital.

Below we have plotted the ATR indicator on to the USD/JPY forex chart.

The 14-day ATR has a peak and then a decline, which shows a decrease in volatility. As you know that high volatility conditions are the best times to trade (less slippage, high liquidity, etc.), you can risk up to 5% of your trading capital on the trade while one should not risk more than 1% when the ATR is at the lowest point. Do not forget the risks involved while trading highly volatile markets. Only use this position sizing technique when you completely trust your trading strategy.


A trader should not risk too much on any trade, especially if their trading capital is small. Remember, your odds of making a profit are high when you manage your position size and risk the right amount on each of the trade you take.

Beginners should trade thin to get experience with open positions, so they can assess the stress of a loss and gradually increase the position size as he is comfortable with the strategy results and performance. As a matter of fact, this is also the right way to proceed when trading live a new strategy, be it a beginner or an experienced trader.


Forex Market

Finding The Optimal Risk % In Forex Trading


Calculating risk is one of the most important parts of Money Mangement. Many novice traders or traders with limited experience won’t be aware of the amount of risk they can tolerate. In this article, we shall focus on determining the appropriate risk % that fits your trading style. The goal of risk management is to gain control over three things:

  • Emotions
  • Leverage
  • Sustenance

Furthermore, by limiting the loss per trade, a trader can ensure that his/her trading capital is not wiped out in one single trade. Having this discipline systematically reduces the loss per trade and provides an opportunity for the trader to re-look at the situation.

Calculating the risk

One can determine the risk based on the following factors:

Win rate

Win rate refers to how often a trader takes profitable trades relative to the trades that result in a loss. Win rate is determined by using the risk-to-reward ratio (RRR) and is calculated by the following formula.

Win rate = 1/(1+RRR)

The above-given formula is also referred to as the Minimum win rate. If any trader is trading with an RRR of 1, then his/her minimum win rate will be 50%. So out of 100 trades, we require a minimum of 50 trades to end as winners to compensate for the losing trades.

This will help a trader in deciding their maximum risk based on the win rate. This formula can also determine if a trade can be taken or not. For example, if someone has a win rate of 25%, he/she will not be able to take trades that have a risk-to-reward ratio of less than 3.

Nature of the market

Depending on the market situation, the risk can vary substantially. In a trending market, like the one in the below chart, risk should be reduced as much as possible by using a stop-loss order. We are recommending this idea as you would most probably be trend trading, and there is no point in risking more than the usual (can be lesser).

Trending Market

In a market that is trapped in a range (below image), the risk is always higher. This means anyone who trades the consolidation market is essentially increasing their risk. This would mean increasing the stop-loss, thereby reducing the risk-to-reward ratio (RRR) of the trade.

Ranging Market

Maintaining a risk of 1% constantly, regardless of the market conditions, will help the traders to sustain the loses and stay in the game even after a series of losing trades. This is a conservative method that reaps fewer rewards, but the risk is certain.


The aim is to achieve some level of consistency in trading by allowing yourself and your trading strategy to fight the evil forces of the market. We would say in all circumstances, a max risk of 1% appears to be the winner if you are a conservative trader. When the risk increases, it is said to impact not only the capital of the trading account but also the psychology of a trader. Hence it is better to keep risk at a bare minimum in times of uncertainty.

Forex Market

Understanding Drawdown & Its Relation With Position Size


Do you know that there is a safe way to choose the maximum lot size when you trade? That too while keeping your account safe from blowing when a losing streak of trades occur? To constantly stay in the game and be able to recover from losses requires patience, clarity, and, more importantly – optimal Position sizing. The position size in simple words is how much a trader invests in each trade. There are different models deployed to reach the optimal position sizing depending on the objective of the trade. Before that, let’s first understand what drawdown is and how it is related to position sizing.

What is the maximum drawdown?

The maximum drawdown is the biggest drop in the accumulated profit chart and, consequently, that of the trading capital. Imagine a situation where a trader had 200 pips in profit after a number of trades, and on the following days’ profit dropped to 136 pips before he can make new accumulated high.

So, the drawdown here was 200-136 = 64 pips

When this drawdown increases, it reaches a level (negative drawdown), after which it becomes impossible to trade (due to loss of trading capital). Maximum drawdown is the loss that the trader can take in order to survive in the market and be able to continue trading.

How is drawdown related to position sizing?

Taking the above example, let us assume that the trading capital was $500 and the trader trades with a lot size of 0.01. The drawdown he experienced was 64 pips, which is $6.4 (1 Pip = $0.1). So the amount of money he/she risking in this trade is 6.4/500 x 100 = 1.28% of the account size.

Now let us see how this drawdown increases with a change in position size.

How much drawdown can I handle so that it doesn’t affect the mental state and my trading style?

As you can see below, the drawdown % increase as the lot size increases and the account gets into an unsustainable state (Especially when the Trading Capital is $500). Hence you need to calculate risk based on your risk tolerance drawdown.

The right way to look at drawdown and position size

Typically, the drawdown occurs after a series of consecutive losses. The very first thing a trader needs to do is to analyze and figure out the number of losing trader he/she can endure. Depending on that, the maximum risk percentage should be defined. So essentially, this percentage is the maximum amount of trading capital a trader affords to lose. If the losses cross this percentage, his/her account get unsustainable.

For instance, I can bear a maximum drawdown of 20%. So I should be willing to design a strategy and chose my trading size in such a way that it is very unlikely for me to reach the 20% drawdown. Let’s denote the number of losing streaks as N. I should make sure that my strategy has a winning percentage of at least 50% or more with high RRRs. Let’s assume the maximum number of losing streaks I can afford is 10 (i.e. N=10).

Dividing the maximum drawdown (20%) with N (10) gives 2%. This means that I cannot risk more than 2% of my trading capital on a trade to sustain in the market. If I have more than one open trading position, I should be distributing the risk among all of the open positions. So here, if I have 2 open positions, I shouldn’t be risking more than 1% in each of the trades. This is one of the best ways to look at drawdown and position size.

Different approaches to position sizing

Defined Percentage Risk

In this position sizing strategy, we risk a fixed percentage of the trading capital (e.g., 1%) for each trade. This is followed by most of the traders across the world and it is pretty simple to use as well. Essentially, the trader is required to put the stop-loss more accurately and not randomly to prevent the stop-loss hunt. This might sound pretty easy but it needs a lot of discipline to overcome the greed and not raise the position size when you see a clear profitable trading signal.

The Kelly Criterion Model

John Kelly described this criterion pretty long ago, which computes the optimal position size for a series of trades.

Kelly Percentage = W – [(1-W) / R)

Where, W – Winning probability and R – Profit/Loss ratio

When a trader keeps a record of all their trades, they can calculate their winning probability and profit/loss ratio. Then, they can use them in the above equation to calculate the optimal position size.


You now know the importance of position size and its relation to drawdown. By using this, leverage can also be used appropriately to avoid blowing-up your account because of the drawdown. By doing this, you can maximize your earnings and reduce drawdown to an acceptable value.

Our suggestion for you is to use a trading strategy for a long time. If a strategy hasn’t been tried many times, the big drawdown might not have appeared yet. The bigger the history of using the strategy, the more confidence you will get to increase the lot size. Cheers!

Forex Market

Advantages & Risks Involved With Volatility Trading In The Forex Market


The forex market offers a lot of trading opportunities, but still, many traders find it difficult to make profits consistently. Emotions combined with undue risk and money management are often the main obstacles that new traders face.

In this article, we will discuss the hourly volatility in the forex market and the trading risks involved during these hours. Some traders trade the market based on its volatility. Few traders enjoy volatile markets, while others prefer trading in non-volatile conditions. So let’s get right into the topic.

The volatility of a major currency pair

Hourly volatility is relevant to short term forex traders but is not a significant factor for long term investors. The global trading sessions affect volatility within the 24 hours. A forex pair is typically most volatile when a major trading session opens, or two market sessions overlap with one another. For example, EUR/USD is the most volatile and active when London or New York is open because these markets are associated with the Euro and USD, respectively. The below figure depicts the volatility of EUR/USD in a day.

The average volatility of EUR/USD currency pair on a single day

The bar chart shown above represents the volatility of EUR/USD in a day. It depicts nothing but a candle with lower wick, body, and upper wick. One can see that during the Asia session, the price is not volatile. Whereas during the New York session, the price makes large movements shown by larger wick and body of the bar chart. Even without looking at candlestick charts on the trading platform, these bar charts are sufficient to decide at what time to trade during the day, which is much easier than analyzing candlestick charts.

Low volatile hours – Asia Session and Time b/w NY close & Asia Open  

Traders have a misperception that “More risk equals more return.” There is no doubt that highly volatile pairs deliver impressive returns, but research and data have found that lower-volatility sessions generate risk-adjusted returns over time. This is the reason why traders include the ‘Low volatility factor’ in their portfolio.

Risk of trading in low volatile hours

In times of low volatility, there is increased slippage, which means a trader will hardly get the price they desire for. This would mean eating up of their profits, or even sometimes a complete drain of profits (when trading on a lower time frame). In this way, a trader will not be trading according to the rules of money management. Hence, to manage risk, there is a right way to trade during such times. Some of them are discussed below.

Why is it important?

There are several reasons why trading in lower volatility conditions has the potential to create a lot of money over the long term.

Leverage aversion– In money management theory, we had mentioned earlier that the more leverage a trader use, the more is the risk. In times of lower volatility, traders are restricted from using the leverage from their trading account. As a result, they buy and sell currency pairs that are less risky with good profit potential.

The lottery ticket– Many traders treat the forex market as a “lottery” where they buy and sell currency pairs like they are purchasing lottery tickets. This, in turn, raises the bid of high-risk pairs, which leads to the type of lottery effect and increases volatility. Here, we need to find pairs that are under no one’s attention and buy them (which will be least volatile).

High volatile hours – London & New York Sessions

Many traders live on volatility in the forex market, as volatility is what creates profitable trading opportunities.

Risk of trading in high volatile hours

High volatility hours also has its own disadvantages. During such times, one can see their stop-losses getting triggered frequently. This happens due to the tricks played by more significant players like stop-loss hunting. Another risk is the high leverage provided by forex brokers. So to manage these risks, high volatile hours should be traded in a certain way. Some of them are listed below.

Trend trading– One key opportunity in a volatile market is that trending currency pairs may see the rate of their trend increase. When we are trading with the trend, our risk drastically reduces, which is good for money management.

Short-term strategies– In volatile markets, strategies work the best by booking profits automatically than manually. In this way, we will be eliminating emotions in trading as everything will be done by the system, which is crucial for risk management. Strategies also make use of indicators like RSI and Bollinger bands, which help in identifying overbought and oversold zones.

Bottom line

Every trading session and hour has its own advantages and risks, which a trader needs to evaluate, based on his/her risk appetite. The right time to trade depends on the personality of the trader and style of trading. Volatility on an hourly basis is more complex than how much a forex pair moves each day on an average basis. We see volatility varies drastically across different hours of the day and days of the week. We need to monitor and adapt to these changes. Cheers!

Forex Psychology

Do Not Change Your Demonstrated Strategy Out of the Blue

Forex market is appealing to the traders. It operates 24/5, and it is the most liquidate financial market. It offers numerous trading opportunities to traders of all sorts. Since it has so much to offer, investors love investing in the market. However, these benefits often work against traders. Statistics suggest that 95% of traders lose their money in the Forex market.

A question may be raised here why most of the investors are unsuccessful in this market. There are quite a few to mention. However, today, I am going to talk about a very common factor that makes many traders unsuccessful.

We know winning trade and losing trade go hand by hand in the financial market. In the Forex market, it goes more frequently than other financial markets. Ideally, if a trader wins his 60% trades even with a 1:1 risk-reward ratio, he is considered a good trader. At the end of the day, he is making profit matters. By losing 40% of trades, he is still able to make money. It is simple math. Let us now dig into this simple math and find out how it could make a trader unsuccessful.

Let us assume a trader has learned or found out a strategy that offers 1:1 risk-reward with a 60% winning rate. He takes six entries in a week, and all of them hit Take Profit. In the following week, he takes four entries, and all of them hit Stop Loss (For the sake of statistics). He starts thinking something must be wrong with his strategy. He forgets the whole picture. Psychologically, he is down. Thus, he would have more problems with the strategy. He abandons his proven approach and starts looking for a new one, though, there is not anything wrong with the strategy.

As far as statistics are concerned, if on average a trade strategy gets us 40% losers, it means that 16% of the time (one every three losing streaks) a trader will encounter two losers in a row, 7% of the time he will get 3 consecutive losers, 3% of the occasions he will experience four losers. Are you already pondering? Here is the last data to be presented in front of you; about 1 in 100 trades, he will encounter five losers in a row. A trader needs to accept the fact because it is inherent to the statistical properties of his game.

We know a trader needs to do a lot of back-testing, study, demo trading before using it in live trading. This process consumes time. Moreover, a good strategy does not mean that it would suit every single trader. The new one may not be his cup of tea. Assume what happens next. He starts looking for another one.

Meanwhile, he starts losing his faith in him and this market. The consequence is obvious. He becomes a member of that ‘95% Club’.

The Bottom Line

It does not matter how good a trader someone is; he is to accept losing trades. The entire result is to be calculated. A trader must not worry about one or two losing trades, but must have faith in his strategy (which he uses after hours of back-testing, study) as long as it brings him consistent profit.

Forex Basics Forex Daily Topic

The Babe Ruth Syndrome

In his book More than you know, Michael J. Mauboussin tells the story of a portfolio manager working in an investment company of roughly twenty additional managers. After assessing the poor performance of the group, the company’s treasurer decided to evaluate each manager’s decision methods. So he measured how many of the assets under each manager outperformed the market, as he thought that a simple dart-throwing choice would produce 50% outperformers. This portfolio manager was in a shocking position because he was one of the best performers of the group while keeping the worst percent of outperforming stocks.

When asked why was such a discrepancy between his excellent results and his bad average of outperformers, he answered with a beautiful lesson in probability: The frequency of correctness does not matter; it is the magnitude of correctness that matters. 

Transposed to the trading profession, The frequency of the winners does not matter. What matters is the reward-to-risk ratio of the winners.

Expected-Value A bull Versus Bear Case.

Since a combination of both parameters will produce our results, how should we evaluate a trade situation?

Mauboussin recalls an anecdote taken from Nassim Taleb’s Fooled by Randomness, where Nassim was asked about his views of the markets. He said there was a 70% chance the market had a slight upward movement in the coming week. Someone noted that he was short on a significant position in S&P futures. That was the opposite of what he was telling was his view of the market. So, Taleb explained his position in the expected-value form:

Market events Probability Magnitude Expected Value
Market moves up 70% 1% 0.700%
Market moves down 30% -10% -3.000%
Total 100% -2.300%

  As we see, the most probable outcome is the market goes up, but the expected value of a long bet is negative, the reason being, their magnitude is asymmetric. 

Now, consider the change in perception about the market if we start trading using this kind of decision methodology. On the one hand, we would start looking at both sides of the market. The trader will use a more objective methodology, taking out most of the personal biases from the trading decision. On the other hand, trading will be more focused on the size of the reward than on the frequency of small ego satisfactions.

The use of a system based on the expected value of a move will have another useful side-effect. The system will be much less dependent on the frequency of success and more focused on the potential rewards for its risk.

We Assign to much value to the frequency of success

Consider the following equity graph:


Fig 1 – Game with 90% winners where the player pays 10 dollars on losers and gains 1 dollar on gainers

This is a simulation of a game with 90% winners but with a reward-to-risk ratio of 0.1. Which means a loss wipes the value of ten previous winners.

Then, consider the next equity graph:

Fig 1 – Game with 10% winners where the player pays 1 dollar on losers and gains 10 dollars on gainers

A couple of interesting conclusions from the above graphs. One is that being right is unimportant, and two, that we don’t need to predict to be profitable. What we need is a proper method to assess the odds, and most importantly, define the reward-to-risk situation of the trade, utilizing the Expected Value concept,

By focusing on rewards instead of frequency of gainers, our strategy is protected against a momentary drop in the percent of winners.

The profitability rule

P  > 1 / (1+ R)  [1]

The equation above that tells the minimum percent winners needed for a strategy to be profitable if its average reward-to-risk ratio is R.

Of course, using [1], we could solve the problem of the minimum reward-to-risk ratio R required for a system with percent winners P.

R > (1-P)/P    [2]

We can apply one of these formulas to a spreadsheet and get the following table, which shows the break-even points for reward-to-risk scenarios against the percent winners.

We can see that a high reward-to-risk factor is a terrific way to protect us against a losing streak. The higher the R, the better. Let’s suppose that R = 5xr where r is the risk. Under this scenario, we can be wrong four times for every winner and still be profitable.

Final words

It is tough to keep profitable a low reward-to-risk strategy because it is unlikely to maintain high rates of success over a long period.

If we can create strategies focused on reward-to-risk ratios beyond 2.5, forecasting is not an issue, as it only needs to be right more than 28.6% of the time.

We can build trading systems with Reward ratios as our main parameter, while the rest of them could just be considered improvements.

It is much more sound to build an analysis methodology that weighs both sides of the trade using the Expected value formula.

The real focus of a trader is to search and find low-risk opportunities, with low cost and high reward (showing positive Expected value).


Appendix: The Jupyter Notebook of the Game Simulator

%pylab inline
Populating the interactive namespace from numpy and matplotlib
%load_ext Cython
from scipy import stats
import warnings
The Cython extension is already loaded. To reload it, use:
  %reload_ext Cython
from scipy import stats, integrate
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
import numpy as np
from matplotlib import pyplot as plt

# the computation of the account history. We use cython for faster results
# in the case of thousands of histories it matters.
# win: the amount gained per successful result , 
# Loss: the amount lost on failed results
# a game with reward to risk of 2 would result in win = 2, loss=1.
def pathplay(int nn, double win, double loss,double capital=100, double p=0.5):
    cdef double temp = capital
    a = np.random.binomial(1, p, nn)
    cdef int i=0
    for n in a:
        if temp > capital/4: # definition of ruin as losing 75% of the initial capital.
            if n:
                temp = temp+win
                temp = temp-loss        
    return rut
# The main algorithm. 
arr= []
numpaths=1 # Nr of histories
mynn= 1000 # Number of trades/bets
capital = 1000 # Initial capital

# Creating the game path or paths in the case of several histories
for n in range(0,numpaths):
    pat =  pathplay(mynn, win= 1,loss =11, capital= cap, p = 90/100)

#Code to print the chart
        fig, ax = plt.subplots(1, 1, figsize=(18, 10))
        plt.grid(b = True, which='major', color='0.6', linestyle='-')
        plt.xticks( color='k', size=30)
        plt.yticks( color='k', size=30)
        plt.ylabel('Account Balance ', fontsize=30)
        plt.xlabel('Trades', fontsize=30)
        line, = ax.plot([], [], lw=2)
        for pat in arr:


More than you Know, Michael.J. Mauboussin

Fooled by randomness, Nassim. N. Taleb



Forex Daily Topic Forex Money Management

Things you should Know about Leverage, Drawdown and Risk

Novice traders usually prefer to focus on trade ideas and strategies, believing that the path to success is the knowledge about entries and exits. But in a trading environment with leverage, risk management plays a crucial role. This article tries to show why.

Key points

 In trading, There are two key points a trader must care and make sure:

  1.  That his strategy is good
  2. Risk management trough proper position sizing

Good Strategies and Bad strategies

The first thing to consider is the quality of the trading system or strategy. There are risk management ideas that might convert a losing system into a winner if the problem was that stop-loss settings were wrong, But no position sizing can change a losing strategy into a winning one. Therefore, the first thing a trader should care about is for his system to have a positive edge.

In statistical terms, the strategy should have a positive expectation. If not, the trader should analyze it, find the weak points, and modify it for profitability. Once the system is profitable, it can be traded. Finally, depending on its quality, the system will make grow the trading account fast or slow, and, also, its growth can be optimized through position sizing.

Strategy basic Statistical 

To analyze a trading strategy, we need to normalize its trades to a basic unit and, then extract its four main statistical parameters:

  • Percent winners
  • Mean reward-to-risk Ratio
  • Mathematical expectation
  • Standard Deviation of the expectation.

For example, the system we are going to use as an example in this article shows the following parameters:


  •  Nr. of Trades: 143.00
  •  Percent winners: 58.74%
  •  Mean Reward Ratio: 1.22
  •  Mathematical Expectation: 0.0887
  •  Standard dev: 0.4090

It is not a really good system, but it’s tradeable. The Mathematical expectation says that the system, using a basic unit of risk of one dollar, is able to extract a mean of 8.87 cents per dollar risked on every trade. Therefore, the system has an 8.87 cents edge against the market, which is 8.87%.


You can see that here, we did not show the drawdown as a parameter to consider. That is because drawdown is dependent on position sizing. The parameter we can compute, though, is the losing streak, which is the number of continuous losses we could expect based on the percent of losses. As we know, the percent of losers is 1-percent winners. Therefore, in this case, Percent losers = 41.26%

With that information, we can create a probabilistic curve of a losing streak of size N, such as the one here. But the trade size is what is going to define the drawdown parameter.

Fig 1 – Losing Streak Probability Curve

Leverage and Drawdown

Forex is a leveraged trading environment, and many brokers offer its customers the ability to go up to 500:1, meaning traders can use up to 500x the size of its trading account to open positions. But is it wise to get that leveraged? Let’s do an experiment using the above-mentioned system.

As said above, the system has been taken from a real trader and is a good, although not brilliant system. But it is a real no-hype system that can be traded what we want to test. For this test, we will always start with a balance of $10,000 and will increase the trade size using the same trade segment. 

Leverage = 1

Fig 2 – 0.1 Lots per trade

Using a leverage of one, we see that the system shows a max drawdown of 10.4 percent, and the final equity after 143 trades is a bit more than $11.600, which is 16% growth.

Leverage = 5

Fig 3 – 5X Leverage

Using 5X leverage, we notice that the Max Drawdown went to 39.58%, and the final equity ended up at $18,400.00 for an 84% profit.

Leverage = 10

Fig 4 – 10X Leverage

If the trader dares to go to 10X leverage, he must endure close to 61% drawdown for the opportunity to receive 168% profit and a total equity of $26,800 at the end of a 143-trade cycle.

Leverage = 20

Fig 5 – 20X Leverage

Leverage 20X is even wilder. The trader has to withstand up to 83.4% drawdown for a gain of 336.00 % profit.  The question is when to stop? Will a 40X leverage be even better for the profit-hungry trader?

Leverage = 40

Fig 6 – 40X Leverage

We can see that at some point, the risk is too much, and a profitable system, with the wrong risk and size management, can be converted into a very fast losing system and wipe the entire account.

As we see here, a 40X leverage is wild enough to wipe an entire account using a very profitable trading system. We must understand that up to one point, increasing the leverage will increase risk while decrease profitability.

As a summary, let’s see the plot of several account histories with increasing leverage

Fig 7 – 40X Leverage

This time we have plotted the histories on a semi-log scale to be aware of the enormous scale of the drawdowns. On the graph, we can see that the most critical moment of the histories happens at about trade Nr. five or six, which crashes all accounts above 30X leverage. But, if we take this event aside, we can see that to reach its destination traders must endure four more events when they lose close to 80% of their initial funds. We must take into account that at the moment of these events happening, there is no way to know when will they stop and start recovering the funds back.

A Propper Attitude Towards Risk

Position sizing and risk management are the tools traders have to accomplish their trading objectives, but it has to be done correctly.

We first need to set the daily, weekly, or monthly profitability of the trading strategy. Let keep using the previous example.  We know that the system has a mean of 8.87 cents per dollar risked.  Let’s suppose the system has an average of six daily trades. Then, the profitability of this system is $0.53 daily, and $10.64 monthly per dollar risked.

From the losing streak curve, we see that it is wise to be prepared for a max streak of, at least eight losing trades.  Then, we define our comfort zone for drawdowns. Let say we are bold and wanted to risk up to 40% of the capital. To accomplish this, we divide the max 40% drawdown by our defined max losing streak of 8, and the result will be the maximum percent risked on every trade. In this case, Risk per trade = 5%. (That is a huge of risk, we do not recommend more than 1%, by the way).

Now, if your current account balance were $10,000,  the risk per position should be 5% * 10,000, = $500. With that information, we can see that the system would deliver $5,320 monthly, on average.

If we were to double this amount, we would need to double the account balance or wait roughly two months until the profits reached the $10K mark.

The concept of applying a trade size proportional to the account balance helps traders to apply compounding growth to their accounts, while automatically reducing the trade size while in a losing streak on a dollar basis. More on compound growth will be developed in a future article.


Forex Basics

Even a Combination of Double Top and Engulfing Fails

Double Top/Double Bottom is one of the most robust patterns that price action traders wait to take entries. When the price is rejected twice at a resistance level, it forms a Double Top. As far as the candlestick pattern is concerned, an engulfing candle is the most reliable reversal candle that traders usually love to take an entry from a value area.

A combination of Double Top and a bearish engulfing candle attracts sellers to go short. Since it is an outstanding price action combination, it does not usually go wrong. However, in today’s lesson, we are going to demonstrate that even a great flourishing price action combination can go wrong, as well.

The price consolidates at the marked resistance and heads towards the downside. It then goes back towards the resistance. The sellers are to get ready to get a bearish reversal candle. The red-marked level is the resistance level, where we don’t consider the upper shadows. Since the price has several rejections at the marked level, and it is a valuable area for the sellers, the price most probably may respect the area and produce the bearish reversal candle.

The price does not respect the red-marked level, but it does not make an upside breakout either. Instead, it closes within the upper shadows. Traders are to adjust here. Let us see how it looks now.

The level where the last candle closes has some significance. One of the bullish candles closes within the marked level. This level may work as a resistance level and ends up producing a bearish reversal candle.

Here it comes. The Double Top’s resistance level produces a bearish engulfing candle. We have found the resistance level at last. So all the equations to go short from here seem to match as far as price action trading is concerned.

  1. The price produces a Double Top.
  2. The price produces a bearish engulfing candle right at the resistance of the Double Top.

The swing low is far enough, which offers good Risk-Reward as well. All seems to be okay to trigger a short entry.

After triggering the entry, the next candle comes out as a bearish Doji candle. Things still look good. The sellers are going to grab some green pips!

No! The next candle comes out as a bullish Marubozu candle, which breaches the resistance of the Double Top. It wipes off the Sellers Stop Loss. The buyers may take control once the breakout is confirmed.

The Lesson

It does not matter how good a trade setup looks: it may fail. Thus, there is no reason to be too optimistic about any entry. We must calculate our Risk-Reward and have immaculate risk management with every single entry that we take in the market.

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The Trading Record


Traders want to win. Nothing else matters to them; and they think and believe the most important question is timing the entry. Exits don’t matter at all, because if they time the entry, they could easily get out long before a retracement erases their profit. O so they believe.

That’s the reason there are thousands of books about Technical Analysis, Indicators, Elliott Wave Forecasting, and so on, and just a handful of books on psychology, statistical methods, and trading methodology.

The problem lies within us, not in the market. The truth is not out there. It is in here.

There are a lot of psychological problems that infest most of the traders. One of the most dangerous is the need to be right. They hate to lose, so they let their losses run hoping to cover at a market turn and cut their gains short, afraid to lose that small gain. This behavior, together with improper position sizing is the cause of failure in most of the traders.

The second one is the firm belief in the law of small numbers. This means the majority of unsuccessful traders infer long-term statistical properties based on very short-term data. When his trading system enters in a losing streak, they decide the system doesn’t work, so they look for another system which, again, is rejected when it enters in another losing sequence and so on.

There are two problems with this approach. The first one is that the trading account is constantly consumed because the trader is discarding the system when sits at its worst performance, adding negative bias to his performance every time he or she switches that way. The second one is that the wannabe trader cannot learn from the past nor he can improve it.

This article is a rough approach to the problem of establishing a trading methodology.

1.- Diversification

The first measure a trader should take is:

  1. A portfolio between 3-10 of uncorrelated and risk-adjusted assets; or
  2. A portfolio of 3 to 5 uncorrelated trading systems; or
  3. Both 1 and 2 working together.

What’s the advantage of a diversified portfolio:

The advantage of having a diversified portfolio of assets is that it smooths the equity curve and, and we get a substantial reduction in the total Drawdown. I’ve experienced myself the psychological advantage of having a large portfolio, especially if the volatility is high. Losing 10% on an asset is very hard, but if you have four winners at the same time, then that 10% is just a 2% loss in the overall account, that is compensated with, maybe, 4-6% profits on other securities. That, I can assure you, gave me the strength to follow my system!.

The advantage of three or more trading systems in tandem is twofold. It helps, also improving overall drawdown and smooth the equity curve, because we distribute the risk between the systems. It also helps to raise profits, since every system contributes to profits in good times, filling the hole the underperforming one is doing.

That doesn’t work all the time. There are days when all your assets tank, but overall a diversified portfolio together with a diversified catalog of strategies is a peacemaker for your soul.

2.- Trading Record

As we said, deciding that a Trading System has an edge isn’t a matter of evaluating the last five or ten trades. Even, evaluating the last 30 trades is not conclusive at all. And changing erratically from system to system is worse than random pick, for the reasons already discussed.

No system is perfect. At the same time, the market is dynamic. This week we may have a bull and low volatility market and next one, or next month, we are stuck in a high-volatility choppy market that threatens to deplet our account.

We, as traders need to adapt the system as much as is healthy. But we need to know what to adjust and by how much.

To gather information to make a proper analysis, we need to collect data. As much as possible. Thus, which kind of data do we need?

To answer this, we need to, first look at which kind of information do we really need. As traders, we would like to data about timing our entries, our exits, and our stop-loss levels. As for the entries we’d like to know if we are entering too early or too late. We’d like to know that also for the profit-taking. Finally, we’d like to optimize the distance between entry and stop loss.

To gather data to answer the timing questions and the stop loss optimum distance the data that we need to collect is:

  • Entry type (long or short)
  • Entry Date and time,
  • Entry Price
  • Planned Target price
  • Effective exit price
  • Exit date and time
  • Maximum Adverse Excursion (MAE)
  • Maximum Favourable Excursion(MFE)

All the above concepts are well known to most investors, except, maybe, the two bottom ones. So, let me focus this article a bit on them, since they are quite significant and useful, but not too well known.

MAE is the maximum adverse price movement against the direction of the trend before resuming a positive movement, excluding stops. I mean, We take stops out of this equation. We register the level at which a market turn to the side of our trade.

MFE is the maximum favourable price movement we get on a trade excluding targets. We register the maximum movement a trade delivers in our favour. We observe, also, that the red, losing trades don’t travel too much to the upside.


Having registered all these information, we can get the statistical evidence about how accurate our entry timing is, by analysing the average distance our profitable trades has to move in the red before moving to profitability.

If we pull the trigger too early, we will observe an increase in the magnitude of that mean distance together with a drop in the percent of gainers. If we enter too late, we may experience a very tiny average MAE but we are hurting our average MFE. Therefore, a tiny average MAE together with a lousy average MFE shows we need to reconsider earlier entries.

We can, then, set the invalidation level that defines our stop loss at a statistically significant level instead of at a level that is visible for any smart market participant. We should remember that the market is an adaptive creature. Our actions change it. It’s a typical case of the scientist influencing the results of the experiment by the mere fact of taking measurements.

Let’s have a look at a MAE graph of the same system after setting a proper stop loss:

Now All losing trades are mostly cut at 1.2% loss about the level we set as the optimum in our previous graph (Fig 2).  When this happens, we suffer a slight drop in the percent of gainers, but it should be tiny because most of the trades beyond MAE are losers. In this case, we went from 37.9% winners down to 37.08% but the Reward risk ratio of the system went from results 1.7 to 1.83, and the average trade went from $12.01 to $16.5.

In the same way, we could do an optimization analysis of our targets:

We observed that most of the trades were within a 2% excursion before dropping, so we set that target level. The result overall result was rather tiny. The Reward-to-risk ratio went to 1.84, and the average trade to 16.7

These are a few observations that help us fine-tune our system using the statistical properties of our trades, together with a visual inspection of the latest entries and exits in comparison with the actual price action.

Other statistical data can be extracted from the tracking record to assess the quality of the system and evaluate possible actions to correct its behaviour and assess essential trading parameters. Such as Maximum Drawdown of the system, which is very important to optimize our position size, or the trade statistics over time, which shows of the profitability of the system shrinks, stays stable or grows with time.

This kind of graph can be easily made on a spreadsheet. This case shows 12 years of trading history as I took it from a MACD trading system study as an example.

Of course, we could use the track record to compute derived and valuable information, to estimate the behaviour of the system under several position sizes, and calculate its weekly or monthly results based in the estimation, along with the different drawdown profiles shaped. Then, the trader could decide, based upon his personal tolerance for drawdown, which combination of Returns/drawdown fit his or her style and psychological tastes.

The point is, to get the information we must collect data. And we need information, a lot of it, to avoid falling into the “law of small numbers” fallacy, and also to optimize the system and our risk management.

Note: All images were produced using Multicharts 11 Trading Platform’s backtesting capabilities.

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Risk, Reward, and Profitability

The Nature of Risk and Opportunity

Trading literature is filled with vast amounts of information about market knowledge: fundamentals, Central Banks, events, economic developments and technical analysis. This information is believed necessary to provide the trader with the right information to improve their trading decisions.

On the other hand, the trader believes that success is linked to that knowledge and that a trade is good because the right piece of knowledge has been used, and a bad trade was wrong because the trader made a mistake or didn’t accurately analyse the trading set-up.

The focus in this kind of information leads most traders to think that entries are the most significant aspect of the trading profession, and they use most of their time to get “correct” entries. The other consequence is that novice traders prefer systems with high percent winners over other systems, without more in-depth analysis about other aspects.

The reality is that the market is characterized by its randomness; and that trading, as opposed to gambling, is not a closed game. Trading is open in its entry, length, and exit, which gives room for uncountable ways to define its rules. Therefore, the trader’s final equity is a combination of the probability of a positive outcome – frequency of success- and the outcome’s pay-off, or magnitude.

This latest variable, the reward-to-risk ratio of a system, technically called “the pay-off” but commonly called risk-reward ratio, is only marginally discussed in many trading books, but it deserves a closer in-depth study because it’s critical for the ultimate profitability of any trading system.

To help you see what I mean, Figure 1 shows a game with 10% percent winners that is highly profitable, because it holds a 20:1 risk-reward ratio.

A losing game is also possible to achieve with 90% winners:

So, as we see, just the percentage winners tell us nothing about a trading strategy. We need to specify both parameters to assess the ultimate behaviour of a system.

The equation of profitability

Let’s call Rr the mean risk-reward of a system.  If we call W the average winning trade and L the average losing trade then Rr is computed as follows:

Rr = W/L

If we call minimum P the percent winners needed to achieve profitability, then the equation that defines if a system is profitable in relation to a determined reward-risk ratio Rr is:

P > 1 / (1 +Rr) (1)

Starting from equation (1) we can also get the equation that defines the reward-risk needed to achieve profitability if we define percent winners P:

Rr > (1-P) / P (2)

If we use one of these formulas on a spreadsheet we will get a table like this one:

When we look at this table, we can see that, if the reward is 0.5, a trader would need two out of three winning trades just to break-even, while they would require only one winner every three trades in the case of a 2:1 payoff, and just one winner every four trades if the mean reward is three times its risk.

The lessons learned from analysing these equations are:

Let’s call nxR the opportunity of a trade, where R is the risk and n is the multiplier of R that defines the opportunity. Then we can observe that:

  1. If you spot an nxR opportunity, you could fail, on average, n-1 times and still be profitable.
  2. A higher nxR protects your account against a drop in the percent of gainers
  3. You don’t need to predict the price to make money because you can be profitable with 10% winners or less.
  4. As a corollary to 3, the real money comes from exits, not entries.
  5. The search for higher R-multiples with decent winning chances is the primary goal when designing a trading system.

A high Rr ratio is a kind of protection against a potential decline in the percentage of winning trades. Therefore, we should make sure our strategies acquire this kind of protection. Finally, we must avoid Rr’s under 1.0, since it requires higher than 50% winners, and that’s not easy to attain when we combine the usual entries with stop-loss protection.

One key idea by Dr. Van K. Tharp is the concept of the low-risk idea. As in business, in trading, a low-risk idea is a good opportunity with moderate cost and high reward, with a reasonable probability to succeed. By using this concept, we get rid of one of the main troubles of a trader: the belief that we need to predict the market to be successful.

As we stated in point 3 of lessons learned: we don’t need to predict. You’ll be perfectly well served with 20% winners if your risk reward is high enough. We just need to use our time to find low-risk opportunities with the proper risk-reward.

We can find a low-risk opportunity, just by price location as in figure 3. Here we employ of a triple bottom, inferred by three dojis, as a fair chance of a possible price turn, and we define our entry above the high of the latest doji, to let the market confirm our trade.  Rr is 3.71 from entry to target, so we need just one out of four similar opportunities for our strategy to be profitable.

Finally, we should use Rr as a way to filter out the trades of a system that don’t meet our criteria of what a low-risk trade is.

If, for instance, you’re using a moving average crossover as your trading strategy, by just filtering out the low profitable trades you will stop trading when price enters choppy channels.


  • Risk-reward is the parameter that allows the assessment of the opportunity value of a trade.
  • The higher the opportunity, the less the frequency of winners we need to be profitable.
  • Therefore, we can assess an opportunity just by its intrinsic value, regardless of other factors.
  • That frees us from seeking accurate entries and set the focus on trade setup and follow-up.
  • We just need to use the familiar market concepts, for instance, support and resistance, to design a robust trading system, by filtering out all trades that don’t comply with the risk-reward figure.
  • Trading becomes the search for low-risk opportunities, instead of trying to forecast the market.


Example of Rr Calculation:

As we observe in Fig 3, the risk is defined by the distance between the entry price and the stop loss level, and the reward is the distance between the projected target level defined by the distance from the Take profit level to the entry price:

Risk = Entry price– Stop loss

Reward = Take profit – Entry price.

Rr = Reward / Risk

In this case,

Entry price  = 1.19355

Stop loss = 1.19259

Take profit = 1.19712


Risk = 1.19355 -1.19259 = 0.00096

Reward = 1.19712 – 1.19355 = 0.00357

Rr = 0.00357 / 0.00096

Rr = 3.7187


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Globalization and its Risks


Globalization is an inevitable process that has been accelerated with the current means of communication and transportation, which help to trade more due to better access to foreign products. Globalization is not only economic, it also covers social and cultural aspects. But since globalization is a process that involves several aspects of society many people see it as a threat to local customs and producers, so they prefer to put some barriers to this process. But it is a process already in development that will be almost impossible to stop so the best thing that each country can do is take advantage of this for their benefit by being more competitive.


Globalization is a process that has spread to different areas in all countries, from cultural to economic aspects. For many economists, globalization has allowed the economic development of many countries to be driven by dependence on international trade and technological advances that not only stay in one country but also expand rapidly as well as new knowledge. But beyond the benefits of globalization, there are many people who question the effect that globalization has on different cultures in the world.

For many people, the values of their culture are very important to value and exchange them for more global ones, which is why some people are still reticent to see a total globalization of all aspects. There is a great debate that persists over time about how, and how much, politicians should intervene in this process of globalization and preserve their own identity or how much the economy of foreign goods should be protected.

Globalization has been formally defined as the phenomenon of acceleration and intensification of economic interaction between people around the world, companies, and governments of the countries involved in this effect, although today there is no country that has not been influenced for globalization. But globalization not only involves economic interactions, political and cultural effects have also been evident, which has led to the study of all areas of society and to encourage debate about the positive and negative effects of globalization.

The globalization of the production and distribution of goods and services has been well received by some people who can now access foreign goods of better quality and in some cases at better prices than local production. But the opponents of globalization show their concern about the local producers of each country and their standards of living after the expansion of international trade. In addition to increasing trade and allowing access to new products, globalization allows the exchange of cultural features, customs such as music and other determinants of daily life such as music and literature.

Exposure to the exchange of goods and services brings changes in the customs, values and local traditions of a country. This is also a point of debate since some believe that globalization eliminates the traditions of a country making it universal but at the cost of the loss of knowledge and traditional customs of a country which is not positive for some aboriginal and indigenous communities that can see this change in their traditions as something threatening.

One of the criticisms, in general, is the Americanization of culture and economy. The most powerful companies belong to the United States, as well as the richest people and in turn, many traditions and festivities that come from North America are exported and celebrated in other countries. This has been a high point and a great debate since many people, especially in underdeveloped and poor countries, see this Americanization as a threat, criticizing consumerism and certain values that are handled in that country. But this leader of globalization, as seen in the United States, has several elements that make it the leader of said globalization.

The first element that makes the United States one of the predominant countries in recent decades is the size of its market which represents about 300 million people. This makes it attractive for multinationals as well as generating economies of scale which means that as companies increase their production costs per unit produced are reduced making their operation more profitable. An important aspect of this large market is the wealth of the population since there are countries with similar or larger population sizes such as China and India, but the wealth between these three nations is not compared since the United States has about 25% of global production.

In addition to the importance of the United States market is the element of language because most people in North America speak English and it is a universal language that allows transactions to be made easily. It is not the only country that has contributed to the process of globalization, but it is one of the predominant countries in this process. The following graph shows the magnitude of the US market in urban areas

US market in urban areas

Graph 22. Urban population. Data taken from the World Bank.

The people who are in favor of globalization argue that contrary to what some people think, globalization supports local cultures through technology by allowing better communications through computer telephones and other elements that facilitate the exchange of opinions. In addition, they preach that through television and other visual artifacts, cultural elements can be displayed so that people who see it within each country feel more identified with their culture.

Another positive aspect of globalization is the new awareness of people that are currently being created – better educated with a broader knowledge and a global notion of different cultures. This type of people are the drivers of current economic processes, they have a more cosmopolitan than rational thinking, speak several languages, travel internationally and they have more developed skills with better education standards, so they have better living standards than the people who lived before.

Globalization in the economy is the most known and studied fact by people since it is vital to understand how this effect has an impact on people’s daily lives. Economic globalization involves the reduction or elimination of business and trade barriers between countries, which will encourage exports and imports to increase in each country. Therefore, globalization is the economic unification of different countries including the different types of investments that occur in each country. It is crucial that each country is seen as a piece of a puzzle and that each country will be very important for the good economic development of all countries.

Globalization is not a new phenomenon. It goes back more than  2000 years, during which time trade, traditions, ideas, and other elements have been exchanged between different countries and empires. In the last 200-300 years this unifying process has accelerated, leading to greater specialization in the production of goods and greater interdependence among economies. But what is not clear is that the pace of unification of the economies has not been constant, but has increased rapidly since the end of the Second World War. The following graph shows how trade in goods and services has increased in recent years, where globalization has accelerated.

 Exports of goods and services

Graph 23. Exports of goods and services. Data taken from World Bank.


Some of the consequences that globalization has left are:

  • The relaxation of government controls to let the market act independently thanks to the forces of supply and demand.
  • Efficiency in means of transport and communication which helps to make business faster and easier.
  • New technologies that contribute to the quality of life of people. Technological advances have been achieved thanks to the dynamism of trade and skilled labor which has contributed to the progress being made less and less time.
  • Greater dynamism in investments since resources can be easily moved from one country to another without the need to be in several countries to make such investments.
  • Better quality of life for a large part of the population. A better quality of life is achieved with globalization and international trade, consumers can acquire a greater variety of products of good quality and at better prices due to competition between multinationals and local companies.

In addition, globalization reduces labor costs because companies can be in the country that is most beneficial in terms of costs, where there is specialization depending on production and the intensity of capital used. That is why lower prices can be seen in goods and services since with globalization countries have managed to reduce their costs by specializing in countries with economies of scale and with good competitiveness in terms of costs.

Another consequence of globalization is access to the natural resources of different countries. This is an advantage for countries that do not have access to good resources due to their geographic location that determines the climate and their access to seas or not. In addition, there are countries that have better access to mineral resources such as oil or coal. Globalization intervenes in the fact that the multinationals depending on the location and resources of each country decide to locate themselves in a certain area to extract these resources, but also generating benefits for the local communities. The negative aspect of globalization at this point is to what extent it is positive to extract and exploit natural resources of a foreign country since it can destroy nature and many projects will be made for political interests rather than the possible economic benefits.

At this point in the article, we will analyze a determinant of investments in the globalized world that currently exists. Country risk is one of the most important variables when analyzing how risky investment is in a country given its political and economic factors and its relationship with other countries. The formal definition is the risk of an investment due to specific factors common to a specific country. It can be analyzed as the average risk of investments made in a country.

A country can see its risk increase if a country faces difficulties in paying debt acquired as bonds. The factors that may affect the payment of a country’s debt depend on economic, social, political conditions or in some cases due to natural disasters such as earthquakes. Any assessment of the risk of each country will express the level of probability of suffering a loss in the value invested and depending on the level of that country risk the investors will demand a return on an investment since in the finances if greater risks are incurred, it will be claimed better returns that demonstrate that it is a good idea to invest in that asset. In the following graph, you can see the percentage of country risk that some places had in 2016.

Market Risk Premium

Graph 24. Fernandez P., Fernandez I. and Ortiz A. (2016, May 9). Market Risk Premium Used In 71 Countries In 2016. Retrieved November 17, 2017, from

Country risk analysis is a predominant component of the specialized risk management departments of banks, insurance companies, risk rating agencies, and financial system regulators. In some cases, country risk includes the risk of payment transfers, confiscation and expropriation, and risks of internal and external wars.

The debtors of these investments can be stated sovereigns, or they can be private agents such as banks and companies that issue debt to obtain financing for their commercial operations. In general, any country or private agent can issue debt and be subject to country risk assessment and each agent that issues debt will be analyzed differently because almost no company or state will face the same determinants in the risk of their investment.

The country risk can be materialized to the extent that there may be a payment crisis and the result of this is the non-payment of the debt by the agents, whether private or state. This debt default occurs especially in countries with high debt or without good access to external debt. Also in cases where the debtor is a state agent, it is determined the number of foreign reserves that a country has since these can be used as payment by the creditors at a specific time. In the following graph, you can see the external reserves of different countries.

Total reserves. Data taken from World Bank

Graph 25. Total reserves. Data taken from World Bank.



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The Meaning of Cutting Losses Short


In this article, we deal with the different ways and aspects of the stop-loss setting. A crucial task for a successful trader.


What a price to pay for bad wisdom? Too young to know too much too soon… (Suzanne Vega)

The decision where to cut losses if a trade is not working should be part of the trade selection process for every trade, and should be assessed in connection to the potential profit; so the risk to reward should comply with our trading rules.

One key example of the need for cutting losses short (in other words having high reward to risk trades) was given by trader Glen Ring when interviewed by Bruce Babcock (The Four Cardinal Principles of Trading).

He had a month when he made eight trades, with seven winners and one loser, but the net result was a losing month, just because of a single big loss.

The opposite may hold: you might experience eight trades with seven losers and still be profitable just because your system’s mean reward-to-risk ratio is excellent and that winning trade erased the losses of the seven losers.

The key lesson is: Although psychologically, we need to be right, we must focus on a reward-to-risk ratio, not in the frequency of our gains.

In Glen’s words: “Having those small losses is what keep us in the game, keeps your position for when you do catch a trend or big move. But, it’s a law of numbers to me. If we can make enough controlled-loss trades, even a blind squirrel is going to find a nut once in a while.

The Stop-Loss Concept

The stop-loss concept is related to position size. Trend following’s main idea is to catch the big trend. Its rate of success is reduced -below 35%-, but with potential big reward to risk ratios.

There’s a small chance for a trader to have ten losses in a row. A trader that risk no more than 2% of its equity on a single trade experiences a 20% drawdown at the end of 10 consecutive losses, but may still keep following the rules. A trader risking 5-6% will be 50 or 60% down, and undoubtedly will lose perspective and may stop following the rules, even though the system hasn’t failed.
The main lesson is: Trade thin instead of big at the beginning, analyze your potential drawdowns in losing streaks as a mean to optimize your position size of your system.

Minimizing losses means that we are in control. Being in control is the difference between being a speculator and a gambler. Being a speculator means we can decide on the odds. Be in control about when to enter the market and when to exit. That can’t be done gambling.

We’ll discuss the several methods top traders use in their trading systems. They can be divided into the following categories:

  • Chart-based stops
  • Indicator stops
  • Entry method stops
  • Volatility stops
  • Money management stops
  • Account equity stops
  • Margin-based stops


1.    chart-based stops

Chart-based stops are those stops put near a meaningful point on a chart. This may be related to a chart pattern, trend line or pivot point that represents support or resistance.

Cutting losses short don’t mean unrealistic tight stops, though. It’s important to give latitude enough to let the trade work.

So, cutting losses short means to close a trade if, by our rules, has touched the stop point. But that point shall be placed according to the logic of the price movement.

Also, it’s wise to let a wide margin at the beginning of the trade using a small position, but, as the trade develops in our favor, we should move the stop higher and, optionally, add to the position.

What happens if the chart stop defines a trade that’s too risky? In the futures market, the minimum risk one can take is the one assumed by trading one contract. In the case of currency markets, this isn’t an issue, so the answer is: reduce your position to the level you have set in your trading rules. The number one rule is to protect our capital.

The chart method to set the stop has its detractors. In Babcock’s book already mentioned, Jake Bernstein says that John Granville used to say: “if it’s obvious, it’s obviously wrong.” “Let’s put the stop at the low of the day.” Ten thousand people are thinking the same way. The odds are that approach is not going to work.

How To Set Stop Loss In Options Trading

The Last Day Rule:

Peter Brandt, mentioned in Babcock’s book, has what he calls “the last day rule”. He applies it to breakout trades to reduce losses on failed breakouts.

The rule calls for a stop set at the opposite extreme of the last day of the previous range pattern. If the break is to the upside, he sets the stop to the low of the last day within the pattern. If to the downside, he uses the high of that last day.

The use of retracements, Fibonacci:

Some traders use retracements as places to start a trade using Fibonacci retracements. One way to place entries and stops is, for instance, entries at a 50% retracement and stops at 62%, that way we plan for a 50% potential profit with a 12% risk; more than 4:1 RR.

Moving to break-even:

One method that helps release stress and anxiety from the trader is to move the stop to the break-even point if and when the price has moved to a level that allows to do it.  Then the rest of the trade is a free ride. This has been recommended by many authors focused on trader’s psychology (Alexander Elder, Mark Douglas, Van K. Tharp).

2.    indicator stops

Indicator stop means setting the stop by virtue of an indicator, such as a moving average or momentum.  It’s not a chart-based stop since it’s computationally based.

Indicator stops seek to optimize the relationship between cutting losses short and not getting chopped up at the same time. That’s difficult to achieve without studying past trades for improvement. Indicator stops tries to optimize the relationship between cutting losses short and not getting chopped up at the same time. That’s difficult to achieve without studying past trades for improvement.

To optimize stops we need to back (or forward) test which is the stop distance beyond which there is are more money lost than gained. For more on this, I recommend John Sweeney’s concept of Maximum Adverse Execution. To optimize stops we need to back (or forward) test which is the stop distance beyond which there is are more money lost than gained. For more on this, I recommend John Sweeney’s concept of Maximum Adverse Execution.

The main idea of the MAE using Sweeney’s words is:

 “It turns out that if your trading rules are consistent and can distinguish between good and bad trades, then, over many experiences, you can measure how far good trades go bad and, usually, see at what point a trade is more likely to end badly than profitably. That is the point at which you stop and/or reverse.”


How To Set Stop Loss In Options Trading | Forex Academy

How To Set Stop Loss In trading

(figures taken from John Sweeney’s book)

3.    entry method stops

By entry method stops, it means some stop point that is set by the entry method. It may be a reverse entry signal, or it may occur as a result of the violation of some or all of the trade’s entry conditions.

“The same methodology that says enter the trade has to tell you when the trade is wrong. [..] If a market exceeds the price and time projection windows, then the trade is wrong” (Robert Miner)

Robert Miner has a price and time zone. If price breaks the zone or if the time window is reached without gains, he closes the position.

4.    volatility stops

Volatility stops are stops placed at a distance from the entry calculated as some percentage of recent or historical volatility. In general, volatility is measured as a price range computed over a time-lapse.

Stan Tamulevich, interviewed by Babcock for his book, uses the three to four-day volatility. If the market takes out the distance of the last day, he quits the trade. Usually even less than that. If the market takes out 50% of last day move ¡t enters in a danger zone.

Russell Wasendorf, another trader interviewed, sets his stop outside the range set by historical volatility. Short-term volatility increases don’t change his plan. His method is more concerned with not getting shaken off a potentially winning position rather than improve its short-term risk.

5.    money management stops

Money management stops mean fixed dollar amount stops. It’s a combination of stops and dollar risk management.

The two main advantages the author sees are:

  • If the purpose of stop-loss is to manage risk, a dollar stop is the most direct way to manage it.
  •  That kind of stops don’t go to obvious places, except by coincidence, so the risk to be whipsawed by the market is reduced.

6.    account equity stops

An Equity stop is based on a fixed percentage of the account equity. A variant of money management stop.

It’s a methodology that starts by defining in dollar terms what’s the risk allowed by the account’s rolling balance of the trader. If we assume 1% risk is set,  this leads to a dollar risk amount for that account balance.

Then the risk-dollar amount of the potential trade is computed. If it falls within the 1% risk the trade is taken, opening the number of contracts within the 1% risk rule.

If the loss is not within the 1% rule, the entry point must be adapted to bring it close enough to the exit point, so the risk is no more than 1%.

7.    margin-based stops

A variation of the previous type. Stops are calculated by taking a percentage of the exchange margin. This is specific to futures trading.

8.    main points to remember

  • Cutting losses short is the most important rule in a trading plan
  • The trader should be more concerned with the reward-to-risk ratios than with the percentage of winning trades.
  • Chart-based stops set stop points in the proximity of market bottoms/tops.
  • Indicator-based stops look to optimize the stop point using math and historical analysis of past trades.
  • Volatility stops try to keep stop points away from the volatility cloud.
  • Account-equity stops move the entry point of a trade to a place that complies with the percent risk rules of the account.

9.    conclusions and criticism

Stop-loss definition is a difficult task, but it has to be designed with care, as is the main concept to success in trading.

In Mr. Babcock’s book, the primary focus is the futures market, that presents a very poor atomization of the position. I mean, the minimum size allowed in the futures market is ONE contract so that the minimum risk would be the risk of that single contract from an entry point to a stop point. That makes it difficult to split the concept of “cutting losses” with the concept of “position size.” In the currency markets, this is not the case, as we can do it down to micro-lots, which makes it possible to do independent optimization of the two concepts.

I think a combination of Chart or volatility-based stops is the initial stage towards the definition of this task as part of a trading system. But a second step might be to optimize stops using John Sweeney’s MAE concept. For this, we might need a computerized analysis of our past trades, or a back-test, if the system rules can be automated.

We may design a continuous improvement process, by a careful annotation of the behavior of our current stops for further analysis in search of better places.

Regarding position sizing, this is a subject for another essay, it suffices to say for the moment that we could use the before mentioned rule: don’t to risk more than 1% of our current trading account balance, and if you’re starting trading, don’t risk more than 25% of that. There’s a Spanish popular wisdom sentence: ” En dinero y amistad, la mitad de la mitad” (about money and friendship divide by half and then by half).

We should remember that the primary goal of a trader is to survive.