The following system variables can be used to obtain trade statistics separately per asset, algorithm, and long/short trade direction. They can be evaluated in real time while trading, or at the end of a simulation cycle for calculating statistics in [Test] mode. All parameters are read/only. Most come in three flavors:
...Long: Results of all long trades with the current asset and algorithm. Including phantom trades, but not including pool trades.
...Short: Results of all short trades with the current asset and algorithm, including phantom trades, but no pool trades.
...Total: Results of all trades with all assets and algorithms, not including phantom trades.
In [Test] mode the ...Long and ...Short results are from the current sample cycle only, which allows to produce statistics distributions of sample cycles. If the ALLCYCLES flag is set, the ...Long and ...Short results are summed up from the all sample cycles. The ...Total results are always summed up.
A set of overall strategy statistics is available after the end of a simulation, and can be evaluated in the objective or the evaluate function.
For calculating various statistics of the last N trades, use the
Sum of profits of all trades won so far. When using oversampling or phantom trades, WinLong or WinShort can be higher than WinTotal.
Profit of all won trades minus loss of all lost trades, in volume neutral PIP
For converting a component profit to a profit in average PIP units, multiply it
Sum of losses by all trades lost so far. The accumulated balance, i.e. the return of all closed trades is WinTotal - LossTotal. WinTotal or LossTotal can be modified by script for simulating additional wins or losses
in the backtest.
The current profit factor, clipped at 10, is ifelse(LossTotal >
Sum of losses by all trades of all Zorro instances that have set the ScholzBrake
and are trading real accounts on the same PC. This variable
is only available in [Trade] mode. It is increased by
any loss, and updated to the other Zorro instances once per bar and on any trade.
Open profit of all currently winning trades.
Open loss amount of all currently losing trades. The accumulated equity, i.e. the current profit of all open and closed trades is WinTotal - LossTotal + WinValTotal - LossValTotal.
Open profit of all open trades in volume neutral PIP units.
For converting a component open profit to a profit in average PIP units, multiply it
Realized component profit so far; WinLong-LossLong+WinShort-LossShort.
Unrealized component profit so far; WinValLong-LossValLong+WinValShort-LossValShort.
Realized and unrealized total profit so far;
Sum of returns of all closed trades of the current component; WinLong-LossLong or WinShort-LossShort.
Sum of returns of all closed, plus value of all open trades of the current
component; BalanceLong+WinValLong-LossValLong or BalanceShort+WinValShort-LossValShort.
Maximum profit of a trade so far.
Maximum loss of a trade so far.
Number of profitable trades so far. The average return per winning trade is WinTotal/NumWinTotal.
Number of lost trades so far. The average return per trade is (WinTotal-LossTotal)/(NumWinTotal+NumLossTotal).
Current number of losses in a row, or 0 if the last trade was a winner.
Can be reset by script.
Current number of wins in a row, or 0 if the last trade was lost.
Can be reset by script.
Accumulated loss of the current loss streak, or 0 if the last trade was a winner.
Accumulated profit of the current win streak, or 0 if the last trade was lost.
Number of currently open winning trades with the current asset and algorithm, including phantom trades.
Number of currently open losing trades with the current asset and algorithm, including phantom trades.
Number of currently open trades with the current asset and algorithm, including phantom trades.
Numbers of currently open trades with all assets and algorithms.
Number of currently pending trades, i.e. trades that have just been entered, or that have not yet reached their Entry Stop or Limit within their EntryTime period. NumPendingTotal includes pending phantom trades in Virtual Hedging mode, as they also trigger real trades.
Number of rejected open or close orders in live trading, due to lack or market liquidity, broker connection failure, market closures, holidays, or other reasons.
Open position of the current asset, positive when long and negative when short.
The variables hold the difference of long and short open lots of
real trades (LotsPool), virtual trades in virtual hedging
mode (LotsVirtual), and phantom trades (LotsPhantom). Only for the underlying, not for positions of
options and combos.
Open account positions can be read from the broker API with the
int for numbers that count something, otherwise var.
- The parameters are part of the GLOBALS struct and the STATUS structs. They are defined in include\variables.h.
- The parameters are only affected by trades opened with the current Zorro instance. Trades opened manually or with other platforms on the same account do not affect the trade statistics parameters.
- The parameters are updated once per bar. Therefore they can be
inaccurate when trades are opened or closed immediately before reading the
variables, but are correct again at the next bar.
- Every algo and asset call changes the component-dependent ...Long and ...Short statistics variables. They are set to the statistics of the selected asset and algorithm identifier. The ...Total statistics variables are unaffected by algo and asset calls.
- In a TMF or trade loop,
the asset is automatically set to the asset of the trade, but the algo is
not. For evaluating component-dependent statistics of a trade, select the
trade algo by algo(TradeAlgo); (even when no different
algos are used).
- If a backtest or training runs over several bar cycles, the ...Long and ...Short statistics variables are taken from the last bar cycle, while the ...Total statistics variables are taken from the average of all bar cycles.
- Win/loss metrics can be calculated from the above parameters. For
instance, AvgWin = WinValTotal/WinTotal; AvgLoss =
LossValTotal/LossTotal; WinRate = WinTotal/(var)LossTotal (check
divisors for zero!). Trade-dependent metrics can be calculated by enumerating trades with
for(open_trades) or for(all_trades),
or with the results function.
Asset-dependent metrics can be calculated with a
for(assets) loop that enumerates all assets used in the system.
- Trade statistics are reset when the
strategy is restarted. For preventing this, store them at the end of a live session and resume
the next session with setf(SaveMode,SV_STATS).
// suspend trading after 4 losses in a row
if(LossStreakShort >= 4 || LossStreakLong >= 4)
setf(TradeMode,TR_PHANTOM); // phantom trades
resf(TradeMode,TR_PHANTOM); // normal trading
Trade parameters, Balance, Lots, for(trades), strategy statistics, performance report,
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