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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)

Filed by Tomasz Janeczko at 3:16 pm under Custom Backtest
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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).

Filed by Tomasz Janeczko at 5:16 pm under Custom Backtest
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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:

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:

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.

Filed by Tomasz Janeczko at 3:38 pm under Custom Backtest
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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.

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

Filed by Tomasz Janeczko at 12:18 am under Custom Backtest
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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:

Filed by Tomasz Janeczko at 6:22 am under Custom Backtest
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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.

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.

Filed by Tomasz Janeczko at 4:16 am under Custom Backtest
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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.

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

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

Filed by Tomasz Janeczko at 5:12 pm under Custom Backtest
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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:

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:

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.

Filed by Tomasz Janeczko at 4:22 am under Custom Backtest
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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).

This is done by changing Buy array values from “true” to sigScaleIn (this prevents redundant signals from being removed because scale-in marks are kept untouched) and modifying standard procedure to treat scale-in signals as normal buys (no scaling).

Note that there are many ways to achieve the same effect. The technique presented here was choosen because it is easy-to-use (does not require changes in your core trading system code – all it needs is to plug-in the custom backtest part). Longer implementation would be required if you do not want to (ab)use scaling signals.

One thing worth mentioning is the fact that since scaling-in signals do not store position score this example formula does not support ranking of signals according to user-defined scores.

Filed by Tomasz Janeczko at 5:50 am under Custom Backtest
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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…)

Filed by Tomasz Janeczko at 3:20 pm under Custom Backtest
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