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System Description​

DifferenceEngine uses similar strategies as SuperSystem, but with narrower parameters resulting in fewer trades, but a higher average trade profit. DF includes one system, whereas SuperSystem contains 2 different systems.


Real time performance metrics for the DifferenceEngine MultiSystem can be found at this AlgoLab House account: AlgoLabHouse2

Based on our extensive analysis, we believe that DifferenceEngine is a better trading system than SuperSystem, although there have been, and will be periods of time where SuperSystem will outperform DifferentEngine.

Using $100,000 of capital and the lowest risk level of .05, the average annual hypothetical return according to backtesting is about 80% with an average annual maximum drawdown of 17%.

The minimum recommended amount of capital to trade DifferenceEngine using the entire symbol set is $100,000. With the risk set to the lowest level of .05, the maximum theoretical drawdown is $35,000 which might be expected to happen at least once every 10 years or so. This would imply that there is a 1 in 10 chance that the first year of trading DF could see a 70% drawdown with a $100,000 account. If that drawdown does not occur in the first year, and you don't increase the capital after the first year, then profit generated from the first year should cover any serious drawdown loss from subsequent years.

Trading DifferenceEngine with a risk level comparable to the stock market

The long term average annual maximum drawdown of the S&P 500 index over the last 35 years is 14.2% in exchange for an average annual return of around 7%. The recent maximum drawdown of the stock market was the financial crisis of 2008 where the S&P 500 index dropped 55%.

The default DifferenceEngine average annual drawdown using a​n account of $100,000 and the lowest risk possible of .05 yields an average annual maximum drawdown of around 17% with an average annual return of around 80%.

Comparing "apples to apples", with both investment categories generating a similar average drawdown of 14% to 17% for the $100,000 capital invested, the S&P500 returned an average of 7%, whereas AlgoLab returned an average of 80% - almost 12 times more profit for every dollar lost in drawdown!

Run the AlgoLab Performance Viewer web application to review various backtesting result scenarios with your capital, risk settings, futures markets, and filters selections.

Real trading is never nearly as profitable as backtesting, so these values are just rough estimates on the optimistic side.