FENÓMENOS BIOLÓGICOS

To start a walk forward run, pull down the menu next to the Optimize button and select Walk-Forward Optimization.

Example 9, Chapter 3, ran a walk forward. Review that example now.

Background and Justification

While there is nothing special about the optimization process - it is just an organized way to look at a lot of alternatives - there is something very special about the walk forward process. The walk forward process is the best tool available to you for trading system validation. While you are developing your trading system, you have access to all the data.

Using your best efforts, you try to develop your system using in-sample data and test it us-ing out-of-sample data. But what will happen when you start actually tradus-ing the system?

The walk forward process can give you an idea of what might happen.

In the development phase, you used the in-sample data and ran optimizations to search for patterns, then tested on out-of-sample data. The walk forward process automates this for you and provides several important things:

• It automates the process of optimizing over a set of in-sample data.

• It automates selection of the best set of values.

• It automates testing over the out-of-sample data.

• For each walk forward step, it gives you a look at what happens when your sys-tem goes from in-sample to out-of-sample.

• It gives you an idea of how long your system remains in synchronization with the market it is modeling.

• It provides a set of out-of-sample results that you can use as a baseline to com-pare the actual results of your own trading.

The walk forward process is the culmination of the steps of:

• Choose your own objective function.

• Optimize in-sample.

• Test out-of-sample.

Note that in the walk forward process, the best set of values for the parameters is chosen, and the out-of-sample results are calculated using those values. At this point, you do not choose which set to use; you have already incorporated the criteria that are important to you into your objective function. For a deeper discussion of objective functions, see Quan-titative Trading Systems.

Mechanics of Walk Forward

By the time you get to the walk forward stage, you have a trading system you like and you know what tradables it models well. You are looking for three things:

• How long is the in-sample period?

• How long is the out-of-sample period?

• What is the out-of-sample performance?

The underlying market is changing as the fundamentals upon which it is based change.

These could be interest rates, the strength of the currency, the phase of the economic cycle, the profitability of the sector and of the specific company, and so forth. Your model is able to identify the important characteristics and identify profitable trading opportunities, but the model and the market drift from being in synchronization to out. The length of the in-sample period must be shorter than the period of synchronization. Your system sets its parameter values in the in-sample period and trades in the out-of-sample period. So, your system must sync-up during the in-sample period, then trade for as long as the synchro-nization remains strong. There is an article on my website that discusses Logic, Data, and Synchronization.

Open Analysis, click the Settings button, and the Walk-Forward tab. Review Chapter 3, Example 9, for screen capture images of these steps.

Chapter 9 - Analysis

Copyright © 2012 Blue Owl Press, Inc. Download a free copy from www.IntroductionToAmiBroker.com

9 - 34 1. Click Easy mode (EOD).

Decide when to begin your walk forward. Of course, you must have data from the starting date to the present. But you may decide not to use all of your historical data. By using your judgement, or by running some tests, decide whether the oldest data you have has the same characteristics as the more recent data. For example, the characteristics of the entire equities market changed after October 1987, so you may not want to use data earlier than 1988. If your preferred markets ran up sharply in the late 1990s and fell off dramatically in the early 2000s, you may want to include that data, or you may want to exclude it.

2. Set your starting date in the Start box.

3. Leave Anchored unchecked.

Each model and market combination has a unique relationship. There is no way to tell in advance what the optimum length of the in-sample period is. You must run tests to deter-mine it. By the time you are running the walk forward tests, you should have a very good idea of what length in-sample period to use.

4. Set that length as your in-sample length on the walk forward tab. That is, set the End date so that the length of time between Start and End is the length of your in-sample pe-riod.

5. Decide what date you want as the last day of the last in-sample period. (You may want to withhold some data from the walk-forward process, just as you withheld some data from the backtesting runs you made earlier.) Enter that date in the Last field.

Alternatively, check Use today. AmiBroker will use the final period that includes today as the final out-of-sample period.

Your system will remain profitable as long as the model and the market remain in sync during the out-of-sample period. The length you set as the step sets both the re-optimiza-tion period and the out-of-sample length. By running tests, you can determine how long, typically, the system remains profitable in the out-of-sample period. That is the longest you can wait between re-optimizations.

6. Set the length you want to use for your out-of-sample and re-optimization in the Step field, and use the pull-down menu to select the time increment.

The dates that will be used for each in-sample run and each out-of sample run will be computed and entered into the table. Scroll up and down and review these dates. Be cer-tain they reflect what you want.

7. Select your optimization target from the pull-down list. You should already have se-lected an objective function and been using it all along during your system development and backtesting. K-Ratio, CAR/MDD, RAR/MDD, RRR, and UPI are all good choices.

8. Click OK. This exits the Walk Forward setup dialog.

Each of the walk forward runs is evaluated as it takes place. After an in-sample optimiza-tion, the best set of parameter values is chosen and a single test run is made using those values and that specific in-sample period. The trade summary and equity curve for that in-sample run are calculated. Next, a single test run is made, using those same values, for the out-of-sample period that immediately follows. The trade summary and equity curve for that out-of-sample run are calculated.

There are two reports you can watch as the walk forward runs take place.

The first is the set of in-sample and out-of-sample summaries. These are produced auto-matically and displayed on the walk forward tab.

The second is the concatenation of the in-sample equity curves and out-of-sample equity curves. These are displayed in a pane of the main chart window. But you must first insert the indicator that will display them. Using the charts tabbed menu, expand the equity category, right-click IS and OOS Equity, then left-click Insert.

As the walk forward progresses, you can click on the main chart tab and watch the equity curves develop.

Use the Report icon’s pull down menu and open Report Explorer. Scroll down to the last entry. It is the consolidation of the out-of-sample results. Open that report. Look at the summary statistics and charts. If they look good, your system is ready for trading.