© 2017 by theAlgoLab.com  |  Privacy policy  |  Contact us

AlgoLab by theAlgoLab.com is trade execution assistance software. theAlgoLab.com company, software, or it's principals do not provide trading advice or recommendations. If you require personalized professional trading / investing advice, please consult with a licensed broker/CTM. Actual past performance, or simulated past performance does not guarantee future results. Trading futures assumes a high level of risk. theALgoLab.com and it's principals are not registered as investment advisors. Consult with a CPA or financial advisor, or broker to ensure that your strategy utilized is suitable for your investment profile before trading in an actual funded live brokerage account.

 

Some trading performance results posted at this web site are from back-testing systems during the dates indicated, using specific settings, from a basket of different futures contracts. Some performance results shown here benefit from hind-sight. Some results shown result not from actual funded trading accounts, but from simulated accounts which have certain limitations. Actual results will differ given that simulated results could under, or over compensate the impact of certain market conditions. Actual draw downs could exceed back-testing draw downs when traded on actual trading accounts.  While back-tested results might show profitable returns, once commission, slippage, and fees are considered, actual returns will vary. 


Futures trading has large potential rewards, but also large potential risk. You must be aware of the risks and be willing to accept them in order to invest in the futures markets. Don't trade with money you can't afford to lose. This is neither a solicitation nor an offer to Buy/Sell futures. No representation is being made that any account will or is likely to achieve profits or losses similar to those discussed on this website or on any reports. The past performance of any trading system or methodology is not necessarily indicative of future results. 

View Historical Backtesting Report
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. We recommend setting your AlgoLab account to AutoFollow account "AutoSystemSwitcher" which will automatically set your AlgoLab account to the system which has recently been outperforming.

Navigate to your dashboard web page, then open the "settings" drawer, then find the "addons" section and select "AutoSystemSwitcher" from the pop-up menu. Checking "Symbols, system & dow" will ensure that your account only duplicates the trading system setting, and not risk or other settings.

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 $50,000. 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 $50,000 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.