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Number of stopped-out trades as a custom metric

For the purpose of counting trades closed by particular stop we can refer to ExitReason property of the trade object in the custom backtester. The custom backtest formula presented below iterates through the list of closed trades, then counts the trades, which indicate exit reason = 2, that is stop-loss.

The following values are used for indication of the particular exit reason:

  1. normal exit
  2. maximum loss stop
  3. profit target stop
  4. trailing stop
  5. n-bar stop
  6. ruin stop (losing 99.96% of entry value)
SetCustomBacktestProc"" );

/* Now custom-backtest procedure follows */
if( Status"action" ) == actionPortfolio )
{
    
bo GetBacktesterObject();

    
bo.Backtest(); // run default backtest procedure

    // initialize counter
    
stoplossCountLong stoplossCountShort 0;

    
// iterate through closed trades
    
for( trade bo.GetFirstTrade(); tradetrade bo.GetNextTrade() )
    {
        
      
// check for stop-loss exit reason
        
if( trade.ExitReason == )
        {
         
// increase long or short counter respectively
            
if( trade.IsLong() )
                
stoplossCountLong++;
            else
                
stoplossCountShort++;
        }
    }

   
// add the custom metric
    
bo.AddCustomMetric"Stoploss trades"stoplossCountLong stoplossCountShort
                         
stoplossCountLongstoplossCountShort);

}

Buy CrossMACD(), Signal() );
Sell CrossSignal(), MACD() );
Short Sell;
Cover Buy;
ApplyStopstopTypeLossstopModePercent2);

How to add MAE / MFE dates to the backtest report

If we want to identify dates, when MAE and MFE levels have been reached during the trade lifetime – we can use the code example presented below.

The formula will process the trades one-by-one, read BarsInTrade property to know how many bars it took since trade entry till exit, then use HHVBars / LLVBars functions to identify how many bars have passed since lowest low or highest high within trade length.

With the information that highest or lowest value was observed N-bars ago – it will shift Date/Time array accordingly – so with use of Lookup() function pointing at the exitbar – we can read the date when HHV/LLV was observed within trade lifetime (BarsInTrade).

SetCustomBacktestProc"" );

function 
processTradetrade )
{
    
dt DateTime();

    
SetForeigntrade.Symbol );

    
llvDate LookupRefdt, - LLVBarsLowtrade.BarsInTrade ) ), trade.ExitDateTime );
    
hhvDate LookupRefdt, - HHVBarsHightrade.BarsInTrade ) ), trade.ExitDateTime );

    if ( 
trade.IsLong() )
    {
        
maeDate llvDate;
        
mfeDate hhvDate;
    }
    else
    {
        
maeDate hhvDate;
        
mfeDate llvDate;
    }

    
RestorePriceArrays();

    
trade.AddCustomMetric"MFE Date"DateTimeToStrmfeDate ) );
    
trade.AddCustomMetric"MAE Date"DateTimeToStrmaeDate ) );
}

if ( 
Status"action" ) == actionPortfolio )
{
    
bo GetBacktesterObject();

    
bo.Backtest); // run default backtest procedure

    
for ( trade bo.GetFirstTrade(); tradetrade bo.GetNextTrade() )
    {
      
processTradetrade );

    }

    for ( 
trade bo.GetFirstOpenPos(); tradetrade bo.GetNextOpenPos() )
    {
      
processTradetrade );
    }

    
bo.ListTrades();
}

Buy CrossMACD(), Signal() );
Sell CrossSignal(), MACD() );

How to use custom backtest metric as an optimization target

In Optimization and Walk Forward testing AmiBroker allows us to choose the optimization target that determines optimum values of optimized parameters. This can be done in Analysis->Settings->Walk Forward tab and the drop down list contains a list of built-in statistics to choose from:

Walk forward settings

However, we are not limited to built-in metrics only. Custom Backtester Interface allows us to add any custom statistics to the backtest/optimization reports and we can use these metrics for optimization too.

To do that, we first need to add a custom metric (this article explains how to do it: http://www.amibroker.com/guide/a_custommetrics.html). Then – we need to type-in our metric name into the Optimization Target box:

Walk forward settings - custom metric

The name we enter must be an exact match of the metric name we have defined in AddCustomMetric() method. If entered name can not be found in the Optimization result table, then Net Profit will be used instead.

How to display interest gains in the backtest report

The default backtest report shows total Net Profit figure, which includes both trading profits and interest earnings. With Custom Backtest procedure we can easily isolate these components by summing up profits and loses from individual trades, then subtracting trading gains from the Net Profit and report them as separate metrics.

SetCustomBacktestProc"" );

if ( 
Status"action" ) == actionPortfolio )
{
    
bo GetBacktesterObject();
    
bo.Backtest(); // run default backtest procedure

    // read Net Profit, Winners and Losers profits from the report
    
st bo.GetPerformanceStats);
    
netProfit st.GetValue"NetProfit" );
    
tradeProfits st.GetValue("WinnersTotalProfit") + st.GetValue("LosersTotalLoss");

    
bo.AddCustomMetric"Trading profits"tradeProfits ); 
    
bo.AddCustomMetric"Interest earnings"netProfit tradeProfits );

}

// trading rules here
Buy CrossMACD(), Signal() );
Sell CrossSignal(), MACD() );

After backtest is run, we can see our custom metrics in the backtest report.

More information about creating custom metrics can be found in the manual:
http://www.amibroker.com/guide/a_custommetrics.html

How to display indicator values in the backtest trade list

Backtesting engine in AmiBroker allows to add custom metrics to the report, both in the summary report and in the trade list. This is possible with Custom Backtester Interface, which allows to modify the execution of portfolio-level phase of the test and (among many other features) adjust report generation.

Due to the fact that the report generation occurs in 2nd phase of the test, when the backtester works on ~~~EQUITY ticker, we can not refer directly to given indicators. For example, to display ATR values – calling ATR() function directly is not enough, because we want to see ATR values of the traded symbol, while in portfolio-phase of the test we are no longer working on that symbol’s quotes.

So, we need to:

  1. store the values of indicators in static variables in the 1st phase of the test (when individual symbols are processed). This can be done with static variables, creating separate static variable for each symbol
  2. read stored values once the backtester reaches the portfolio phase of the test.

The following formula shows how this can be coded. The formula below displays the value of ATR indicator for the entry bar of given trade:

SetCustomBacktestProc"" );

if ( 
Status"action" ) == actionPortfolio )
{
    
bo GetBacktesterObject();
    
// run default backtest procedure without generating the trade list
    
bo.BacktestTrue );

    
// iterate through closed trades
    
for ( trade bo.GetFirstTrade( ); tradetrade bo.GetNextTrade( ) )
    {
        
// read ATR values and display as custom metric
        
symbolATR StaticVarGettrade.Symbol "ATR" );
        
trade.AddCustomMetric"Entry ATR"LookupsymbolATRtrade.EntryDateTime ) );
    }

    
// iterate through open positions
    
for ( trade bo.GetFirstOpenPos( ); tradetrade bo.GetNextOpenPos( ) )
    {
        
// read ATR values and display as custom metric
        
symbolATR StaticVarGettrade.Symbol "ATR" );
        
trade.AddCustomMetric"Entry ATR"LookupsymbolATRtrade.EntryDateTime ) );
    }

    
// generate trade list
    
bo.ListTrades( );
}

// your trading system here
Buy CrossMACD(), Signal() );
Sell CrossSignal(), MACD() );

// assign indicator values to ticker-specific variables
StaticVarSetName() + "ATR"ATR15 ) );

How to exclude top ranked symbol(s) in rotational backtest

Rotational trading is based on scoring and ranking of multiple symbols based on user-defined criteria. For each symbol a user-definable “score” is assigned on bar by bar basis. Then, each bar, symbols are sorted according to that score and N top ranked symbols are bought, while existing positions that don’t appear in top N rank are closed.

Sometimes however, we may want to exclude the highest ranking symbol (or a couple of them) from trading. The code below shows how to do that using custom backtester.

ExcludeTopN 1// how many top positions to exclude
SetCustomBacktestProc("");

if ( 
Status"action" ) == actionPortfolio )
{
    
bo GetBacktesterObject();
    
bo.PreProcess();

    for ( 
bar 0bar BarCountbar++ )
    {
        
Cnt 0;
        for ( 
sig bo.GetFirstSignalbar ); sigsig bo.GetNextSignalbar ) )
        {
            if ( 
Cnt ExcludeTopN )
                
sig.Price = -1// exclude

            
Cnt++;
        }

        
bo.ProcessTradeSignalsbar );
    }

    
bo.PostProcess();
}

EnableRotationalTradingTrue );

SetOption"MaxOpenPositions");
SetOption"WorstRankHeld"10 );
SetPositionSize20spsPercentOfEquity );
PositionScore RSI14 );

The code is pretty straightforward mid-level custom backtest loop but it uses one trick – setting signal price to -1 tells AmiBroker to exclude given signal from further processing. Note also that signals retrieved by GetFirstSignal / GetNextSignal are already sorted, so the highest ranked signal appears first in the list.

Per-symbol profit/loss in a portfolio backtest

Backtesting engine in AmiBroker allows to add custom metrics to the report, both in the summary report and in the trade list. This is possible with Custom Backtester Interface, which allows to modify the execution of portfolio-level phase of the test and (among many other features) adjust report generation.

The example presented below shows how to retrieve individual profit/loss figures for each traded symbol in a portfolio test and add the results as custom metrics to the report. The code performs backtest, then iterates through the list of trades and stores each symbol profit in separate variables. Variables are created with VarSet function, which allows to build variable names dynamically, based on the symbol name. There are 2 variables generated per symbol, one holding profit for long trades and one for short trades. In the last part the code reads the created variables and adds input into the backtest report.

function ProcessTradetrade )
{
  global 
tradedSymbols;
  
symbol trade.Symbol;
  
//
  
if( ! StrFindtradedSymbols"," symbol "," ) )
  {
    
tradedSymbols += symbol ",";
  }
  
//
  // HINT: you may replace it with GetPercentProfit if you wish
  
profit trade.GetProfit(); 
  
//
  
if( trade.IsLong() )
  {
      
varname "long_" symbol;
      
VarSetvarnameNzVarGetvarname ) ) + profit );
  }
  else
  {
      
varname "short_" symbol;
      
VarSetvarnameNzVarGetvarname ) ) + profit );
  }

//  
SetCustomBacktestProc"" );
//
/* Now custom-backtest procedure follows */
//
if ( Status"action" ) == actionPortfolio )
{
    
bo GetBacktesterObject();
    
//
    
bo.Backtest(); // run default backtest procedure
    //
    
tradedSymbols ",";
    
//
    //iterate through closed trades
    
for ( trade bo.GetFirstTrade( ); tradetrade bo.GetNextTrade( ) )
    {
        
ProcessTradetrade );
    }
    
//
    //iterate through open positions
    
for ( trade bo.GetFirstOpenPos( ); tradetrade bo.GetNextOpenPos( ) )
    {
        
ProcessTradetrade );
    }
    
//
    //iterate through the list of traded symbols and generate custom metrics
    
for ( 1; ( sym StrExtracttradedSymbols) ) != ""i++ )
    {
        
longprofit VarGet"long_" sym );
        
shortprofit VarGet"short_" sym );
        
allprofit Nzlongprofit ) + Nzshortprofit );
        
// metric uses 2 decimal points and
        // 3 (calculate sum) as a "combine method" for walk forward out-of-sample
        
bo.AddCustomMetric"Profit for " symallprofitlongprofitshortprofit2);
    }
}
//
SetOption"MaxOpenPositions"10 );
//
Buy CrossMACD(), Signal() );
Sell CrossSignal(), MACD() );
Short Sell;
Cover Buy;
SetPositionSize10spsPercentOfEquity ) ; 

Once we run the Backtest, we will get the following output in the report, showing individual profit/loss figures for each symbol in test.

Per-symbol profit

If you prefer percent profits instead of dollar profits, just replace GetProfit() call with GetPercentProfit().

Historical portfolio backtest metrics

Recently on the AmiBroker mailing list some users expressed wish to have access to some of portfolio backtest metrics available in “historical” form (i.e. as date series, as opposed to scalars), so they can be plotted as an indicator.

Implementing such functionality is actually easy with existing tools and does not require any OLE scripts. Everything you need is small custom-backtester procedure that just reads built-in stats every bar and puts them into composite ticker.
In the accompanying indicator code all you need to do is simply use Foreign() function to access the historical metrics data generated during backtest.

The code below shows the BACKTEST formula with custom backtester part:

// Replace lines below with YOUR TRADING SYSTEM
EnableRotationalTrading(); 
PositionScore 1/RSI(14); 
PositionSize = -25;
SetOption("WorstRankHeld");
SetOption("MaxOpenPositions"); 


////////////////////////////////////////
// BELOW IS ACTUAL CUSTOM BACKTESTER PART
// that can read any built-in metric (in this example UlcerIndex)
// and store it into composite ticker for further
// retrieval as data series

SetOption("UseCustomBacktestProc"True ); 

if( 
Status("action") == actionPortfolio )
{
  
bo GetBacktesterObject();
 
  
bo.PreProcess(); // Initialize backtester
 
  // initialize with null 
  // you can have as many historical metrics as you want 
  // (just duplicate line below for many metrics you want)
  
MyHistStat1 Null
  
MyHistStat2 Null// add your own 


  
for(bar=0bar BarCountbar++)
  {
   
bo.ProcessTradeSignalsbar );
  
   
// recalculate built-in stats on EACH BAR
   
stats bo.GetPerformanceStats); 
 
   
// the line below reads the metric and stores it as array element
   // you can add many lines for each metric of your choice
   
MyHistStat1bar ] = stats.GetValue("UlcerIndex"); // get ulcer index value calculated this bar
   
MyHistStat2bar ] = stats.GetValue("WinnersPercent"); // add your own

  
}

  
bo.PostProcess(); // Finalize backtester

  // now STORE the historical data series representing the metric of your choice
  // duplicate the line below for as many metrics as you want
  
AddToCompositeMyHistStat1"~~~UI_HISTORICAL""X"atcFlagEnableInPortfolio atcFlagDefaults );

  
// you can add your own as shown below
  
AddToCompositeMyHistStat2"~~~WP_HISTORICAL""X"atcFlagEnableInPortfolio atcFlagDefaults ); 
}

In the code above, for illustration purposes, we are exporting UlcerIndex and Winners Percent metrics as data series. They are stored in composite tickers for easy retrieval from indicator level.
You can easily extend code to include ANY number of metrics you want.

Now in order to Plot metrics as indicators, use this simple formula:

PlotForeign("~~~UI_HISTORICAL""UlcerIndex Historical"colorRedstyleLine );
PlotForeign("~~~WP_HISTORICAL""Winners Percent"colorBluestyleLine styleOwnScale );

As you can see with one Foreign function call you can read the historical value of any metric generated by the backtester.

NOTE: when running backtest please setup a filter in AA that EXCLUDES composites (group 253) from backtest set.

Using redundant signals for entries

NOTE: THIS ARTICLE IS NOW OUTDATED AS AMIBROKER SUPPORTS NEW BACKTEST MODE THAT HANDLES THIS NATIVELY http://www.amibroker.com/f?setbacktestmode

The sample code below shows how to use custom portfolio backtester procedure to change the way backtester works. Normally buy is matched against sell and redundant buy signals between initial buy and matching sell are removed as shown in the picture there:
http://www.amibroker.com/gifs/bt_regular.gif

The procedure below changes this behaviour and allows to use redundant signals (they are not removed).

(more…)

Adding custom metric: Average adverse excursion

Here is a sample that shows how to create custom metric based on per-trade statisitics.
In this example we will calculate the average value of MAE (maximum adverse excursion) from all trades.
(more…)

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