Recommended optimization parameters

StrategyQuant > Advanced functionality > Optimization

Recommended optimization parameters

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What parameters make sense to be optimized

Simple Optimization

StrategyQuant > Advanced functionality > Optimization

Simple Optimization

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The idea behind an optimization is simple. First you must have a trading system, this may be a simple moving average crossover for example. In almost every system there are some parameters (indicator periods, comparative constants, etc.) that decide how given system behave. The optimization means to test the system with different parameter values to […]

Monte Carlo retest methods

StrategyQuant > Advanced functionality > Cross checks - robustness tests and analysis

Monte Carlo retest methods

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This is another type of Monte Carlo simulations, in this case it simulates random changes in properties that require the strategy to be retested – such as changes in spread, slippage, strategy parameters, or history data. Because every simulation requires a complete backtest this cross check could take long time. It the backtest on main […]

Retest on additional markets

StrategyQuant > Advanced functionality > Cross checks - robustness tests and analysis

Retest on additional markets

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This test for robustness is quite though – it means testing the same strategy on different markets – it means different bol(s) and/or another timeframe(s). Robust strategy should ideally work on multiple symbols/timeframes. In reality, because each market has its own characteristics, daily volatility, etc., it will be not easy to find a strategy that […]

Monte Carlo trades manipulation

StrategyQuant > Advanced functionality > Cross checks - robustness tests and analysis

Monte Carlo trades manipulation

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This cross check run simulations where in each simulation it manipulates the existing trades – shuffles them, misses some and so on. It is very quick, because it doesn’t require running backtests, it works on already existing trades from main backtest. The idea behind this is to verify how much the strategy equity curve depends […]

Retest with higher precision

StrategyQuant > Advanced functionality > Cross checks - robustness tests and analysis

Retest with higher precision

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This test is simple – it backtests the strategy again on the same data, but with higher precision. It is usually best to make the main test on the fastest Selected timeframe precision, because it can very quickly filter out bad strategies – these that produce no trades or whose Net profit is negative. Once […]

Use Cross checks build in Builder and Retester

StrategyQuant > Advanced functionality > Cross checks - robustness tests and analysis

Use Cross checks build in Builder and Retester

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StrategyQuant X allows you to use cross checks (robustness tests) during the strategy build, or when retesting the strategies. There is a number of cross checks that can be used, ranging from simple ones to very complex ones, and they are simple to choose – you can just move the slider in the simple settings: […]

Cross checks – robustness tests and analysis

StrategyQuant > Advanced functionality > Cross checks - robustness tests and analysis

Cross checks – robustness tests and analysis

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Cross checks – robustness tests and analysis Overfitting or curve-fitting strategy to the historical data on which it was build is the biggest danger of strategies generated using any machine learning process. During or after developing new strategy you should make sure your strategy is robust – which should increase the probability that it will […]

Description of advanced Walk-Forward values that can be used in filters / databank

StrategyQuant > Advanced functionality > Optimization

Description of advanced Walk-Forward values that can be used in filters / databank

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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

Optimization Profile and System Parameter Permutation in StrategyQuant

StrategyQuant > Advanced functionality > Cross checks - robustness tests and analysis

Optimization Profile and System Parameter Permutation in StrategyQuant

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This article will be about two important new features that were added to StrategyQuant X Build 114. They are related to each other, and they both are trying to answer the most important questions when creating new trading strategy: Does my new strategy have any real edge? Can I expect it to work on unknown data […]