Example Models

We have created some example models to demonstrate some of the abilities of Adaptive Modeler. The models can be downloaded from the download page. Most of them can be opened with any edition of Adaptive Modeler [1].

This page shows the performance of the example models and explains how they were created. We also explain how to view their historical evolution, verify their "out-of-sample"[2] evolution since creation, and continue model evolution for ongoing performance evaluation. Finally we explain how these models can be used for trading.

The example models were created on the model creation date shown in the tables below (not to be confused with the historical model start date) and are still evolving and generating signals as of today. Because they were created with the Adaptive Modeler version that was current at that time, they do not make use of new features or improvements brought by later versions.

The tables show the Trading Simulator performance of the models[3]. The historical results are the results from model start date until model creation date.

It should be noted that the historical model results may seem less impressive than those reported by many other trading software systems that use some form of optimization. However, as explained here, Adaptive Modeler's incremental walk-forward approach (not optimized) prevents overfitting and leads to more resilient models whose historical results are more reliable and more indicative of future results.

The results since creation are the results from model creation date until now. Since the historical period generally spans several decades while the period since creation is much shorter, relatively less significance should be attributed to the results since creation. Models that have performed well historically, may sometimes undergo periods of poor performance and may therefore (temporarily) show poor returns since creation date[4].

More extensive performance information is available inside the models[9].

How were these models created?

How to verify out-of-sample (walk-forward) performance?

All the downloadable model files are copies made on the model's creation date and were uploaded to the website on that date. The downloadable model files have not been modified since then so they still reflect the situation on creation date. This allows users to observe and verify "out-of-sample" model evolution and performance since model creation date for themselves[2][5].

To download and open a model in  Adaptive Modeler, follow these steps:

  1. Download the corresponding .zip file from the download page.
  2. Extract the .zip file to a folder of your choice. It contains a model file (.aam) and a small quote file (.csv) that contains only the last quote row that was read by the model. 
  3. Open the model in Adaptive Modeler. When asked for the location of the quote file, specify the folder where you extracted the small quote file (.csv) into.

You will then see the model as it was on creation date. The Performance window will show the same historical results as shown on this webpage. (Note: the S&P 500 model will immediately continue evolving through the rest of the included quote file after opening).

To continue model evolution until the present, follow these steps:

  1. Add new quotes to the quote file (use the same formatting as the existing quote row).
  2. If the model is paused, press F3 to resume model evolution or press F4 repeatedly to evolve stepwise bar-by-bar.

The model will then continue its evolution by processing the new quotes from the quote file and generate bar-ahead forecasts and trading signals. Once it reaches the end of the quote file, it simply waits for new quotes to be added.

To see the performance since model creation date:

  1. Go to the Performance window[9]
  2. Click the "Performance Calculation Settings" button
  3. For the "Calculation period", select the radio button "Since" and enter the model creation date
  4. Click "OK"

How to use these models for trading?

To get undelayed forecasts and signals for the future, the Standard or Professional Edition of Adaptive Modeler is needed[1]. Futures, ETFs or other derivatives could be used to trade indices and commodities. Note that the forecasts and signals in these example model are based on daily closing prices. Therefore, orders could be placed shortly after regular market closing in an extended trading session or at the next day's open.


[1] Some models require the Standard or Professional Edition for opening. This is indicated on the download page. Users of the Evaluation Edition will be able to generate forecasts and signals for the future but only after a delay of a few days. This prevents using the Evaluation Edition for actual trading but still makes it possible to evaluate performance on an ongoing basis.
[2] In fact, also the historical model evolution (before model creation date) took place out-of-sample because of the incremental walk-forward nature of Adaptive Modeler.
[3] Returns shown are simulated returns. No representation of actual traded accounts is being made. Also see this Important Information.
[4] These example models should be considered a starting point. Further improvements may result from more (preprocessed) historical data, larger populations, utilizing specific market expertise, new features of later Adaptive Modeler versions, etc.
[5] Model evolution and performance since model creation may vary slightly with different versions of Adaptive Modeler. The results since creation shown on this page have been achieved with the latest released version and are recalculated with every new release (but still using the original model configuration and not using any new features). The historical results were achieved with the version that was current at model creation date and are not recalculated with new releases. Results may possibly also vary slightly across different computers because of small floating point calculation differences between different CPU types, Operating System versions and settings and Microsoft .Net runtime versions. Over time, initially small differences can blow up in the agent-based model, sometimes leading to different forecasts and signals.
[6] Return values are annualized for periods of at least 9 months. For periods shorter than 9 months, the cumulative return (not annualized) is shown.
[7] Annualized Sharpe ratios are shown for periods of at least 9 months.
[8] All returns shown in Adaptive Modeler are after all transaction costs (broker commissions, spread and slippage) but exclude dividends and interest payments.
[9] In these example models, the trades statistics on the Performance Overview (near bottom) are incomplete and only include trades since 11/30/2013 when this feature was introduced.