This Algo Strategy Has Only 3 rules and 62% Win Rate — backtested on Indian market data | FakeTrades
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This Algo Strategy Has Only 3 rules and 62% Win Rate

Critical Trading · watch on YouTube ↗
Analysed 01 Aug 2026, 02:38 PM IST
⏳ Backtest pending — a data-backed verdict will be attached.

Detected components (auto-read from transcript)

Futures SMA/MA

Verdict

Not auto-backtested — too few qualifying signals. AI-decoded: Mean reversion strategy: buy when price closes below 7-day low AND price is above 200-day MA; exit when price closes above 7-day high.

We decoded the rules and ran the engine, but it fired too rarely on Indian market data to score honestly. It was designed for a different market (us) and its filters (float, market-cap, pre-market volume …) don't map onto Indian data. We show no number rather than a fake one. Flagged for a hand-built review.

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Full transcript (1261 words)
hi david here from criticaltrading.com in today's video i'm going to show you one extremely simple systematic strategy that only has three entry and exit rules and generates 62 win rate on top of this this strategy is only invested in a market for about 20 percent of the time which makes it a very low exposure strategy what this means is that in most cases the strategy doesn't actually take any trades and can be therefore combined with other system or systems to increase diversification and the return potential what i'm going to do is i'm going to show you the code of the system as well as the actual setup on the chart then i'll show you the back test results on four different etfs and lastly i'll show you how to increase the net profit of the strategy over four times without making any changes to it whatsoever so let's have a look at the trading setup first the strategy buys when the current closing price on daily time frame closes below the previous seven day low and the market is above its 200-day moving average that's it only two rules to buy on this chart of e-mini s p 500 market closed below its previous seven day low on this particular day the seven-day low is plotted on the chart by the turquoise line with the 200-day moving average shown in yellow i've taken this strategy from book called short-term strategies that work by larry connors highly recommended for anyone interested in algorithmic trading trade is then closed when the market closes above its previous 7 day high i.e the opposite logic again the seven day high is also plotted on the child in turquoise line market broke above it on this day generating an exit signal that's it those are the all trading rules of this strategy the actual code that i wrote in amibroker is shown on the screen two entry rules as i've just described them are here the cell rule is here i'm using stop loss of a size equal to twice the average true range of past 20 bars this ensures that the size of the stop loss takes the current volatility into the account and is my preferred way of using stop losses now let's have a look at the results i've tested the period from beginning of 2007 up to the beginning of october 2020. trading commissions are included and the trades are opened and closed at open rather than close starting capital of 10 000 with four different etfs traded which is spy tlt gld and vnq these etfs are picked to achieve enough diversification as they all cover different markets namely equities treasury notes gold and real estate system holds four maximum positions at the time where it splits the capital equal into four parts fifty percent margin is used in the back test as well average annual return of seven and a half percent with associated maximum drawdown just under 10 sharp ratio of 0.7 the important thing however is the fact that the strategy's exposure is only 20 what this means is that the strategy had um trade open only in about 20 of total time that was tested on taking the annual return figure and put it into context of this exposure the annual return figure is actually very solid annual return adjusted by the 20 exposure arrives at 37 the total number of trades that this strategy made is 360. now bear in mind that i tested a period starting from january 2007 up to beginning of october 2020 which is almost 14 years now this translates to only around 25 to 26 trades per year to achieve an average annual return of seven and a half percent now many people would have scrapped this strategy because the return is too low this is in my opinion and experience a big mistake this is a common mistake among beginners who look for strategies with extremely high returns that obviously go hand in hand with high drawdowns i discuss this in more detail in my free ebook where i talk about how to avoid typical mistakes that beginner traders make and i also give you a recommended portfolio of markets to start trading depending on your initial capital download it for free click the link on the screen or in the comments section now going back to the strategy as i said this is a very passive low exposure strategy that can be easily combined with other strategies to boost its performance when looking at the absolute annual return figure you need to take this into the account if you have a strategy like this that's only invested in the market twenty percent of the time and produces seven and a half return then obviously it's better than the strategy that produces twelve percent return but it's invested eighty percent of the time on top of this its performance can be further improved by trading futures instead of etfs which is what i'm going to show you in just a second strategy's equity curve looks solid so does its monthly profit distributions strategy pass the monte carlo analysis as well which is good but now what if we take this strategy and simply apply to futures instead of etfs the obvious reason for doing so is to increase the performance as futures come with much higher leverage i've tested this by applying this strategy on micro s p 500 micro gold and two year t notes i've simulated started with a capital of ten thousand dollars using the same stop loss calculation the position size however is calculated slightly differently this is because we're working with futures not stocks or etfs position size is based on maximum five percent risk of equity the starting equity is ten thousand so five percent of this is five hundred dollars then the required size of stop-loss is calculated based on two times the average true range of 20 bars if this value arrives at 500 dollars in monetary terms one futures contract is traded if it drives at 250 dollars then strategy opens two contracts and the final equity curve looks as follows the total profit quadrupled it went from 17k to 74k obviously the maximum drawdown increased as well which is logical as we're working with higher leverage when trading futures the average annual return is now at almost 17 and this is despite the fact that a strategy is now applied only on three markets as opposed to four when using etfs the profit table looks much more interesting as well with 2019 showing over 40 percent return once again keep in mind that this is a low exposure strategy with very low frequency of signals due to this i wouldn't recommend to go and start trading it in its current form on its own but rather use it as a great supplementary strategy the key thing i wanted to demonstrate in this video was how can a performance of trading strategy be improved without resorting to changing its rules and making it unnecessarily complex doing so increases the risk of the strategy being over optimized and i personally don't do it myself at all instead what works for me very well is investing time into risk management elements of the strategy combining it with other strategies or simply using different markets as demonstrated in this video thanks for watching david from critical trading signing out

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