**Welcome**

Hello and welcome to our tenth article. This issue explains some of the key metrics used to define and assess a strategy’s profitability with reference to backtesting reports in __MetaTrader 4__ (MT4). All articles are saved at our __Medium page__.

Our software plugin for MT4, *Advantage*, has progressed to Beta! With it you can code and execute MQL4 strategies 4x faster. Sign up for *Advantage* at the following link today and you will get free access until the end of 2022: __https://tally.so/r/wzx51g__.

These articles are based on my experience from consulting and product development at __The IQT__. Do let us know if there are topics you would like us to cover, questions you would like to resolve, or if there are insights you would like to share from your own experience.

**Last Time**

In Article 9 — __“Trader Personality Types”__, we explored how a trader’s personality type may give them a natural affinity for a specific trading style.

**Overview**

• The choice of metrics is often shaped by which trading platform you use. MT4’s backtesting reports show metrics in 3 main areas — Profitability, the Equity Curve and Drawdown, and Data Quality. We will discuss the Equity Curve and Drawdown, and Data Quality, in future articles.

• We can combine MT4’s Profitability metrics with our own analysis to obtain 4 main types of measures:

1) Overall Profitability

2) Average Profitability and the Risk-Reward Ratio

3) The Win Rate and Skew

4) The Rate of Profit

**Main Points**

Below is a sample backtesting report from MT4 for an algorithmic trading strategy called “IQT_MA_Crossover EA” which is The IQT’s implementation of the moving average crossover strategy, as discussed in previous articles (__Part 1__, __Part 2__). The strategy has been applied to the AUDUSD exchange rate (Australian Dollar vs US Dollar) at the hourly timeframe.

**A Sample MT4 Backtesting Report**

**1) Overall Profitability**

With respect to our __Fundamental Equation of Trading__, the key information listed in the report is the following:

• “Total net profit” (*Π*) is £159.53. This equals “Gross profit” — “Gross loss”. A value greater than 0 means the strategy is profitable.

• “Profit factor” is related, this equals “Gross profit” / “Gross loss”. A value greater than 1 means the strategy is profitable.

**2) Average Profitability and the Risk-Reward Ratio**

• “total trades” (*N*) is 55.

• “Expected payoff” is £2.90. This is the average profit per trade, which equals *Π* / *N*.

• “Initial deposit” is £10000. This was the total amount in the account before trading began.

• Within the “Parameters” section, there is an assignment of “general_percentage = 0.1”. This sets the position risked per trade as 0.1% of the “Initial deposit” (£10000), so £10 was risked per trade.

• Some traders think in terms of the Risk-Reward Ratio, but confusingly calculate it as Reward / Risk. In our case, it is “Expected payoff” / amount risked per trade, which is 2.9 / 10 = 0.29. Generally traders like the ratio to be greater than 1, but a low positive ratio is acceptable if the probability of a profitable outcome is relatively high, which leads to the expected payoff being positive as is the case here.

**3) The Win Rate and Skew**

• Other traders think in terms of a “win rate” or “hit rate”. This information is listed in “Profit trades (% of total)”. The first number is 10 here, which tells us the absolute number of profitable trades. The number in brackets is what is usually considered as the win rate; it is 18.18% here, which tells us the number of profitable trades as a percentage of the total number of trades, and equals 10 / 55.

• The win rates for short and long positions are also shown just above, in “Short positions (won %)” and “Long positions (won %)”. The win rates are the numbers in brackets, i.e. 18.52% and 17.86% respectively. This implies that the win rate is higher for short trades, although the difference may not be significant.

• The win rate is not especially informative on its own because it does not account for the overall profitability of the strategy, or the distribution of returns. However, it may be important to traders with a “C” personality type (as explained in the __previous article__), as psychologically they like being “right” most of the time so would value a win rate over 50% or even 70%.

• In conjunction with “Total net profit”, the win rate tells us that the strategy has positive skew; since the win rate is less than 50% but the strategy is still profitable, there must be some relatively big but uncommon wins which outweigh many small but more common losses. We will explain skew more in a further article.

• The previous point is further backed up by a “Largest profit trade” of £103.96 and “Average profit trade” of £39.53, which significantly outweigh the “Largest loss trade” of -£12.80 and “Average loss trade” of -£5.24.

**4) The Rate of Profit**

• “Period” (Δ*t*) is August — November 2021 (4 months). The number of trading days within this period = 86 (we calculated this number by omitting weekends).

• This lets us calculate the rate of profit as 𝜋 = *Π*/Δ*t* = £159.53 / 86 = £1.86 per day. This is positive but seems low. Bear in mind that £10 was risked per trade though.

• An alternative way to incorporate Δ*t* is to consider that the Risk-Reward Ratio is effectively the same as the rate of return of the strategy. 29.0% (of account size) accrued over the 86 days, or 0.337% per day. This is possibly a better way of assessing strategies, but arguably we care most about the final balance which the rate of profit relates to better.

**Further Reading**

In the next article, we will discuss the information in the MT4 report which relates to __The Equity Curve and Drawdown__.

Thanks and happy trading!

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