StrategyQuant X allows you to choose from 3 different strategy “styles”. By style we mean how the strategy is constructed.
Every trading strategy consists of set of IF – THEN rules, managing IF something happens THEN do some action. There are however some differences in how exactly these rules are constructed.
There are two build modes to choose from:
StrategyQuant first generates initial population of random candidates (using the Random Generation mode) and then uses genetic evolution process to evolve the population and produce better and better candidates with each generation.
The process ends when predefined number of generations is reached or when there’s no further improvement.
Strategies in StrategyQuant are saved in their own proprietary file format (with .SQ X extension) that can be opened only by StrategyQuant.
If you find potentially good strategies you should always save them so that you can work with them later.
When you click for example on Builder you’ll see that the screen is divided into three main columns or sections:
When you’ll first start StrategyQuant you’ll see the main screen as in the picture below.
Databank is a storage place where the generated/tested strategies are stored with their results. Each mode (Build/Test/Improve/Optimize) has its own independent databank table. For memory reasons Databank cannot keep unlimited number of strategies, instead it stores the selected number of top strategies, for example top 100 or top 1000 strategies. The configuration how many strategies […]
StrategyQuant X can be configured to dismiss strategies with “wrong” properties – it is set to dismiss (throw away) these strategies by default. You can control this behavior in Rankings in Builder by clicking on the link Configure automatic dismissal.When you open this dialog you can see that there are 8 different strategy checks, we’ll explain them
There are some special stats computed during Walk-Forward optimization that you can use in filters or display in databank. Standard values computed for Walk-Forward optimization These are all standard stats like Net profit, Number of trades, Sharpe ratio, etc. but computed from Walk-Forward optimization equity, not from main backtest. You can get these values when
Below if an example pseudo code of a strategy generated by StrategyQuant. You can see that strategy consists of entry orders, exit orders and trade management commands – such as trailing stop movements, etc.
Every strategy generated by the program can be viewed in this pseudo code or exported in the form of MetaTrader Expert Advisor (EA), NinjaTrader NinjaScript C# strategy or EasyLanguage for Tradestation/Multicharts.
StrategyQuant is a program, it doesn’t have the brain or experience of a trader, and it doesn’t know how to create a profitable strategy. What it does is that it randomly combines available building blocks (indicators, prices, etc.) to create new trading rules. The resulting strategy is then tested on a history data to see if it is profitable.