Example Models
The example models listed here demonstrate some of the abilities of Adaptive Modeler. These are actual models and
most of them can be opened with any edition of Adaptive Modeler
to view their historical evolution and to continue model evolution for
ongoing performance evaluation. With the Standard or Professional Edition, these models can be used to generate undelayed forecasts and
signals for the future
[1].
These examples should be considered a starting
point. Further improvements may result from more
(preprocessed) historical data, larger populations, specific
market expertise, etc.
The tables below show the Trading Simulator
performance of the models[2]. The
historical results are the
results from model start date until the day the model was created. The
results since creation are the results from model creation date
until recently. 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.
Good models may also undergo periods of poor performance sometimes and may
therefore show negative returns since creation date.
More extensive performance information is available inside
the models. Because the downloadable model files on this website were saved
on model creation date, users can verify "out-of-sample" model
evolution and performance since model creation by themselves[3]
[4].
How were these models created?
- Security selection
In general, securities were selected based on availability of sufficient
historical data.
Stock indices were selected among major global stock
markets.
US stocks were selected from a short list of 16
well known stocks that were chosen out of all US stocks with a stock
price history dating back to 1985 or earlier and a market
capitalization between 5 and 50 billion USD.
- Historical data used
Most models use historical prices going back to 1985 or earlier. Daily
closing prices or open, high, low, close bars were used. For some
models, volume data was also used. For stock indices,
cash prices were used. For commodity ETFs, cash prices were used for
historical data before the ETF inception. For other commodities, futures prices were
used. Historical prices before model creation date were adjusted for
splits and dividends.
- Model parameters
Most models were made with the Evaluation Edition using the default
model parameter settings. Models made with the Standard or Professional Edition
used 10,000 or 20,000 agents and some other modified settings. The
specific parameter settings for all models can be seen inside the models.
- Performance calculation
All returns are unleveraged and after all transaction costs but exclude dividend and interest
payments[7].
For every model, historical performance is calculated since the start of
the Trading Simulator. For the S&P500 index model, this is at model
start date. For most other models this is 2,500 bars (about 10
years) after the model start date.
The risk free rates used for calculating the Sharpe ratio for each
model is obtained by taking the
average rate during the calculation period of 3-month treasury bills
of the relevant country. For commodities, US rates are used. The exact
risk free rate values can be seen inside the models (in the
Performance Overview).
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 or shortly
afterwards. 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 model evolution and performance since model creation date for
themselves[4].
To download and open a model in Adaptive Modeler, follow these
steps:
- Download the corresponding .zip file from the download page.
- 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.
- 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:
- Add new quotes to the
quote file (use
the same formatting as the existing quote row).
- 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:
- Go to the Performance window
- Click the "Performance Calculation Settings" button
- For the "Calculation period", select the radio button "Since" and
enter the model creation date
- 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.