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Some trading systems may benefit from attempt to time the broad market. A market-wide valuation, such as moving average, sentiment or some other mechanism may be used to tell if we should be in the market or not.

Flexibility of AFL language allows to create rules or indicators, which are based on more than just one symbol. This enables us to introduce additional filters based on wide-market index performance.

For the purpose of reading quotes of another symbol one can use Foreign or SetForeign functions.

The following formula shows how to generate entry signals in individual stocks when S&P500 index is above its 200-period moving average and exit signals when S&P500 is equal or below 200-period average (^GSPC is a ticker for Yahoo Finance data for S&P500)

A more complex broad-market timing that requires not only closing price of market index can be implemented using SetForeign function. SetForeign replaces all OHLCV data series with that of the “other” security and allows to calculate all kind of indicators that would normally use current security. Broad market timing does not need to be just “all-in” or “all-out” switch. For example one can switch the trading method depending on whenever broad market is trending or sideways.

In this simple example we assume that market timing signals change very infrequently so they change much less often than Trending/Sideways Buy/Sell signals are generated. If that is not the case the switching logic would need to be more complex to decide what to do when we are in the “trending” trade and market switches to sideways mode. In such situation, the code above uses SidewaysSell signal to sell the position, which may or may not be what you are after.

Another example is changing position sizing depending on broad market conditions. We can choose to be fully invested when broead market is up and only 30% invested in down market.

Filed by Tomasz Janeczko at 4:53 am under Backtest
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Some of users may observe that their Profit table is too small, so the numbers get truncated or the text is too small.

First let me tell you that profit table in the backtest report is not really a table, but a bitmap image with fixed dimensions. Profit table, like any other user-definable report chart, is created by running an AFL formula present in the “Report charts” subfolder. The chart is rendered into bitmap image that gets later embedded in the backtest report.

The size of backtest report images depends on Analysis window settings. In order to increase the size of generated images, it is necessary to go to Analysis -> Settings, Report tab and increase the picture dimensions:

Once you change it, newly generated reports will use enlarged image dimensions. Adjusted settings will affect new backtests only, but not the old reports that have already been generated.

Tip: You can create your own report charts by placing your own AFL formula in the “Report charts” subfolder.

Filed by Tomasz Janeczko at 5:30 am under Problems
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From time to time we receive questions about why you can get different results back-testing the same code.

There are many reasons for differences in backtest results:

1. Different data

   For example if past history is updated/changed due to splits for example or backfill or external data update.

2. Different settings / parameters

   May happen if your formula uses Param() functions that output values that may be changed from the Parameter window.

   Note that Parameters in Analysis window use shared ChartID=0, which means that if two formulas use same parameter names they would share parameter values as well.

3. Different formula

   Sometimes even slight change to the formula causes big change in the results, for example if your formula uses #include and included code has changed

4. The formula that self-references its previously generated results.

   Such code produces some data that is later used to produce next run output (for example your code produces composites that are later used – if those composites change – the input data change so the results change, or if your formula uses previous backtest equity or if your formula uses STATIC variables without deleting/clearing them at the beginning)

5. The formula uses random number generator

   This occurs when your formula directly or indirectly calls any function that produces random numbers such as Random or mtRandom

6. The formula reads external files/data that might have changed

   This occurs when your formula directly or indirectly calls any functions that read external files or data that have changed between backtests. It can be as trivial as using current time in your formula.

7. The formula sets global (per-backtest) settings to non-constant value – for example sets global option differently for each symbol.

   This one is subtle and can be easily overlooked by non-experienced users. One has to understand that global (per-backtest) settings are applied to entire portfolio. If one changes those settings on per-symbol basis, then “last write” counts, and it means that result of your backtest will depend on which execution thread ended last. In Windows OS, it is generally unpredicatable which thread ends first because of so many factors that affect execution time. So your backtest may use different settings in different runs as a result of this. Bottom line: never change global settings in your formula to non-constant value.

Filed by Tomasz Janeczko at 6:01 am under Problems
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Zig-zag indicator, as well as other functions using it (Peak/Trough, PeakBars, Troughbars), inherently look into the future. As such they should not be used in trading system formulas without taking precautions. The only way to fix the ‘problem’ is to delay the signal as long as it takes for zig/zag to stabilise last ‘leg’. The delay is variable and depends how much time it takes for defined percentage change to occur in the price series since last peak/trough.

Ready-to-use solution is presented in the Traders’ Tips section of the AmiBroker members area:
http://www.amibroker.com/members/traders/11-2003.html

(NOTE: access to members’ area is limited to licensed users only, if you forgot your password use reminder at http://www.amibroker.com/login.html)

Filed by Tomasz Janeczko at 4:45 am under Backtest
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Some users coming from Metastock ask for “points-only” test.

One needs to know that AmiBroker features way more sophisticated futures mode than MS ever had: http://www.amibroker.com/guide/h_futbacktest.html
It provides full support for futures trading, handling margin deposit, point value, etc.

“Points-only” test is kind of the simplest possible case, but if you want to do just that, it can be implemented using these two lines:

That is all what you need to add to your formula to get point-only test.

Filed by Tomasz Janeczko at 4:37 am under 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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Recently released AmiBroker 5.05 BETA features the automatic Walk-Forward Optimization mode.

The automatic Walk forward optimization is a system design and validation technique in which you optimize the parameter values on a past segment of market data (“in-sample”), then test the system forward in time on data following the optimization segment (“out-of-sample”). You evaluate the system based on how well it performs on the test data (“out-of-sample”), not the data it was optimized on.

To use Walk-Forward optimization please follow these steps:

1. Goto Tools->Automatic Analysis
2. Click Settings button, then switch to “Walk-Forward tab”
3. Here you can see Walk forward settings for In-sample optimization, out-of-sample backtest
   “Start” and “End” dates mark initial period begin / end
   This period will be moved forward by “Step” until the “End” reaches the “Last” date.
   The “Start” date can move forward by “step” too, or can be anchored (constant) if “Anchored” check is on.
   If you mark “Use today” then “Last” date entered will be ignored and TODAY (current date) will be used instead

   By default an “EASY MODE” is selected which simplifies the process of setting up WF parameters.
   It assumes that:
   a) Out-of-sample segment immediatelly follows in-sample segment
   b) the length of out-of-sample segment equals to the walk-forward step

   Based on these two assumptions the “EASY” mode takes in-sample END date and sets
   out-of-sample START date to the following day. Then adds in-sample STEP and this becomes out-of-sample END date.
   In-sample and Out-of-sample step values are set to the same values.

   The “EASY” mode guarantees correctness of WF procedure settings.

   In the “ADVANCED” mode, the user has complete control over all values, to the extent that
   they may not constitute valid WF procedure.
   The interface allows to selectivelly disable in-sample and out-of-sample phases using checkboxes at top
   (for special things like runnign sequential backtests without optimization).

   All settings are immediatelly reflected in the PREVIEW list that shows all generated IS/OOS segments and their dates.

   The “Optimization target” field defines the optimization raport COLUMN NAME that
   will be used for sorting results and finding the BEST one. Any built-in column can be used
   (as appears in the optimization output), or you can use any custom metric that you define
   in custom backtester. The default is CAR/MDD, you can however select any other built-in metric from the combo.
   You can also TYPE-IN any custom metric that you have added via custom backtester interface.

4. Once you defined Walk-Forward settings, please go to Automatic Analysis and
5. press the dropdown ARROW on the Optimize button and select “Walk Forward Optimization”

This will run sequence of optimizaitons and backtest and the results will be displayed in the “Walk Forward” document that is open in the main application frame.
When optimization is running you can click “MINIMIZE” button on the Progress dialog to minimize it – this allows to see the Walk Forward output during the optimization steps.

IN-SAMPLE and OUT-OF-SAMPLE combined equity

Combined in-sample and out-sample equities are available by
~~~ISEQUITY and ~~~OSEQUITY composite tickers (consecutive periods of IS and OOS are concatenated and scaled to
maintain continuity of equity line – this approach assumes that you generally speaking are compounding profits)
To display IS and OOS equity you may use for example this:

Filed by Tomasz Janeczko at 7:54 am under Backtest
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The code below is an little bit more complex example of Low Level Graphics functions (see http://www.amibroker.com/guide/a_lowlevelgfx.html)

It allows to display three kinds of charts:

1. yearly/monthly profit table
2. yearly profit bar chart
3. average monthly profit bar chart

The type of chart is switchable from Parameters dialog.

It should be applied to ~~~EQUITY – portfolio equity symbol (so it only produces output if you run backtest before using it).

Figure 1. Profit chart in table mode

Figure 2. Profit chart in yearly mode

Figure 3. Profit chart in monthly mode

Filed by Tomasz Janeczko at 6:34 pm under Backtest
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If we are backtesting the intraday strategy and we do not want to keep open positions overnight – then it’s necessary to force closing all the open positions before the session end. In order to code it in AFL – the easiest is to use TimeNum() function for that purpose. (more…)

Filed by AmiBroker Support at 5:19 am under Backtest
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The following code shows how to use separate trading rules for several symbols included in the same backtest. (more…)

Filed by AmiBroker Support at 6:55 am under Backtest
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