Parameter Summaries: backtest multiple parameter values in one go

We have just added new functionality to the site that makes it possible to backtest numerous different parameter combinations in one go. We have started with two Parameter Summaries, one focused on relative strength and the other on mean reversion:

Parameter Summaries are available to annual subscribers, both regular and pro, and can be accessed from their respective backtests.

Portfolio RS backtest

Set the weight, min, max and step / increment for each required parameter, then click 'Run Backtests' and the tabulated results will be displayed:

RS Parameter Summary

Backtesting is the only way to know if a strategy works, but it obviously does not guarantee good future performance. Following a solid testing procedure, however, puts the odds in your favor. To that end, we recommend keeping the following in mind when using the Parameter Summaries:

  • Backtest results shouldn't be used to justify a model; it needs to have a sound underlying rationale to begin with.
  • Choose a range of parameter values that make sense for the strategy. i.e., very short lookbacks aren't suited to a strategy targeting longer-term trends and vice versa. Sticking to appropriate parameter values lessens the possibility of being misled by an isolated / lucky result.
  • Larger step / increment values can be used initially to identify the approximate range of parameter values that have produced the best returns. More detailed testing, with smaller step values, can then be done on that range of parameter values..
    i.e., begin with a wider spread between min and max and a larger step value. After identifying a narrower min / max spread, the step value can be reduced.
    Alternatively, when employing 2 or more factors, choose 'Serial' rather than 'All Backtests'. Rather than backtesting every parameter permutation, Serial employs a multi-stage process that reduces the total number of backtests performed, thereby allowing longer periods of time and/or a wider range of parameter values to be tested.
  • When examining the results:
    • A robust model will be moderately sensitive to small differences in parameter value. i.e. performance will vary, but slightly different parameter values should not produce wildly different returns. Larger differences in parameter value, by contrast, should be expected to have a bigger impact on performance. (note: adjacent monthly parameters will exhibit larger performance differences than adjacent daily lookbacks.)
    • If the top performing parameter's returns are far above the rest, then it indicates that its results likely benefited from good luck.
    • The best parameter / lookback values are generally those that show consistency over time. i.e. parameter values that were hugely successful in favorable environments but performed poorly in other conditions, are less desirable than parameter values that produced solid returns across different market environments.
    • The overall backtest should be of sufficient length to include a mix of environments; up, down and sideways markets. Examining shorter periods within that backtest is also worthwhile, as it’s unlikely that the best overall performers were strongest in each and every sub-period. Recognizing that even the best strategies have endured periods of under-performance can help set realistic expectations.
    • The Parameter Summary provides an overview, but it’s important to go beyond the headline statistics once a set of parameter values has been identified. Run a backtest and examine the return and drawdown for each year vs your benchmark. Was it a wild ride? Could you have actually stuck with it (be realistic)? Does huge out-performance in only one or two years mask under-performance the rest of the time? If so, was that because the model does well only in a particular environment, (if so, can you live with that?) or, was it just lucky at certain times?
  • The future is all that matters and it won't be exactly like the past, so there's little point in trying to precisely optimize historic performance.

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Recent Market Action in the Context of ETF Backtesting

Reviewing some recent actual trading from the lens of some of our backtesting applications.  #STUDY

to expand video on screen, click the '4 expanding arrows' icon in the bottom right corner of the video screen. Use the settings icon to change to 1080 quality if it seems at all blurry

Dual Position Backtesting: diversify across rotation days

We have added two new rotation options to the Portfolio Relative Strength and Sequential Relative Strength Backtests:

  • Monthly (Dual Position) 
  • Weekly (Dual Position)

Choosing one of these options allows you to diversify across two rotation days.  For example, select Weekly (Dual Position) and set Position 1 to Tuesday and Position 2 to Friday.  In the chart below the yellow line shows the performance from rotating every Tuesday, the purple line is the Friday rotation, and the green line shows the combined equity curve.


click image to view full size version

Diversifying across two rotation days hedges against going all-in on what could turn out to be the worst performing rotation day in future.  Similarly, though a particular day may have historically performed best, it is not guaranteed to always outperform.  Employing two different rotation days guards against that risk and in doing so, can provide a more realistic assessment of a strategy’s performance.

Reviewing some recent actual trading from the lens of some of ETFreplay backtesting applications

Note: during the launch of our new application called Sequential Relative Strength, we are allowing all accounts to create portfolios using individual stocks. This app module is able to expand on the core Portfolio Relative Strength and add a 2nd stage to help improve entry points.

Reviewing some recent actual trading from the lens of some of our backtesting applications.   This has been a very good market environment for ETF rotation.  #STUDY

to expand video on screen, click the '4 expanding arrows' icon in the bottom right corner of the video screen. Use the settings icon to change to 1080 quality if it seems at all blurry

Using Value ETFs In Sequential Relative Strength

Relative strength is for segments of the market -- it is not for Growth Stocks or Tech ETFs only,  it works for all sorts of things.   Below are some value ETF ideas.  We have found mixing something like Growth or Value with CORE etfs as well will keep it more mainstream.   Up to the user to decide how much deviation from the market indexes they are comfortable with -- below is a starter idea.   Note that while many may not equate IBB with value,  its simply a fact that the large biotech stocks that are in IBB are also in the value indexes and therefore its more of a 'biotech-pharma' value ETF.