Strategy Optimization Report Fitness Function Fields
There are a number of different fields that you can choose to display in the Strategy Optimization Report. Some are also used in StrategyHound Optimization Results. You can customize which fields are displayed and the order in which they are displayed. For details, see Customizing Strategy Optimization Report Fields.
Each field name in the Optimization Report prefix specifies which trades are being reported on. "Long" indicates that the results are based on long trades, "Short" indicates the results are based on short trades, and "All" combines the results for both long and short trades.
The following fields below are the default fields displayed in the Optimization Report and represent short, long, and all trades:
| Field Name | Description |
|---|---|
| [strategy name] Input Values | The column that appears for each input tested; the column name is the same as the name of the input. |
| Test | The number identifying sequence of tests - this column is located on the far left of the report. |
| In-Sample Fitness | The fitness value being calculated chart's underlying In-Sample data as set on the Advanced Settings dialog. |
| Net Profit | How much a strategy made or lost. |
| Gross Profit | The gross profits that would have been earned trading this strategy. |
| Gross Loss | The gross loss that would have been sustained trading this strategy. |
| Total Trades | The total number of trades that were generated by the strategy. |
| % Profitable | The percentage of profitable trades. |
| Winning Trades | The number of trades that are profitable. |
| Losing Trades | The number of trades in which money is lost. |
| Max Winning Trade | The profit generated by the largest winning trade. |
| Max Losing Trade | The loss generated by the largest losing trade. |
| Avg Winning Trade | The amount of the average winning trade. |
| Avg Losing Trade | The amount of the average losing trade. |
| Win/Loss Ratio | The ratio of average winning trades to average losing trades. |
| Avg Trade | The amount of money won or lost in the average trade. |
| Max Consecutive Winners | The largest number of consecutive winning trades. |
| Max Consecutive Losers | The largest number of consecutive losing trades. |
| Avg Bars in Winner | The average number of bars for winning trades. |
| Avg Bars in Loser | The average number of bars for losing trades. |
| Max Intraday Drawdown | The amount of money required on account to survive the largest equity dip during the test period. |
| Profit Factor | The ratio of the amount made (profit) to the amount lost. |
| Max Contracts Held | The maximum number of contracts held during the best optimization test. |
| Required Account Size | The number of contracts/shares of the account needed for the test selected as the best result. |
| Return on Account | The percent of profit on the investment. This is calculated by dividing Net Profit by the Account size required - maximum intraday drawdown plus (+) Margin multiplied by (x) the maximum number of contracts held. Margin is a deposit an investor must make when buying and selling futures con tracts. For stock traders, margin should always be set to zero. |
| TS (TradeStation) Index | A fitness function that maximizes the Net Profit and Winners while minimizing Intraday Drawdown. It calculates the Net Profit * NumWinTrades / AbsValue (Max. Intraday Drawdown). |
| Expectancy Score (Van Tharp) |
A fitness function that measures Expectancy x Opportunity. Based on a calculation by Van K. Tharp. Expectancy = (AW x PW + AL x PL) / |AL| Opportunity = NST / StudyDays |
| Pessimistic Return on Capital (PROC) | A fitness function that represents a very conservative value for Return on Capital (ROC). It calculates the AvgWin*(NumWinTrades) - SquareRoot(NumWinTrades))+AvgLoss*(NumLossTrades + SquareRoot (NumLossTrades))) / Capital.
NumWinTrades = number of winning trades, NumLossTrades = number of losing trades, AvgWin = GrossProf/NumWinTrades, and AvgLoss = GrossLoss/NumLossTrades. |
| Perfect Profit Correlation (PPC) | Calculates the correlation of the actual equity curve vs. a "perfect" curve as if the strategy was able to buy every bottom and sell every top. The genetic optimizer will target an equity curve, that closely matches a "perfect" equity curve. |