Staying in the Game for the Winning Streak

Have you ever quit a strategy only to see the next trade win?

I have.

As humans and traders, most of us will feel less satisfaction from a winning trade than we feel dissatisfaction from a similar sized loss.  This is the well discussed concept of loss aversion, also known as Prospect Theory, introduced by Amos Tversky and Daniel Kahneman in 1979 and elaborated in 1992.  

Traders often quit profitable trading strategies after their first significant loss or string of losses.

Trading systems with the same total return can have a significantly different trading experience.  Take for example, the two back tested hypothetical systems shown below.

In System B, the variation in the equity curve is substantially larger than in System A.  If one can imagine, the feeling on the highlighted date would be different. System A trader is coming off a recent high, whereas System B has been in a drawdown for almost a year.  Quite possibly, you may be doubting System B’s potential just as it is ready for another profitable trade.

What would it feel like in December 2017 if you started trading in December of 2016?   Quite a different experience!

So what is one thing that can be done to before starting to trade a system to make sure as traders we ready to participate in the next winning streak?

Focus on the risk and accept the potential of loss before starting the system.  By knowing the “normal” account drawdowns, one can more easily put drawdowns in perspective.

Risk adjusted returns are metrics which attempt to quantify the return variation, and thus the concern the account owner might feel.   As the name suggests, risk is a major factor in the calculation.

There are many risk adjusted metrics available. Some of the common ones are the Sharpe Ratio, Sortino Ratio, and the standard deviation of return.  Many of these are popular for choosing which mutual funds and ETFs to use for a portfolio.

One of my preferred risk adjusted metrics is simple and uses the maximum peak-to-trough drawdown (MDD) as the denominator over the annualized return (aRet) for a system.   The formula is:

aRet/MDD =  (Total System Return / Years) / Maximum Drawdown

For the examples here are the results (tRet = Total System Return):

aRet/MDD is convenient to work with because it can simplify comparisons between vastly different systems.  If the target is a system which will not drawdown an account more than 10%, an aRet/MDD of 3.2 would provide a 32% return whereas an aRet/MDD of 1.0 would provide a 10% return.  

In the example above, the account size for System A would need to be $55,150 and System B would need be $170,390 to not exceed a 10% drawdown in a single year.

The aRet/MDD is sensitive to the evaluation range, as one wants to capture a large enough sample to be representative of the system over time.  When comparing two systems, the same range of data is preferable when using the same underlying.

By examining a systems “normal” risk and accepting that potential account drawdown before trading a system, one has ammunition to combat the inevitable loss aversion thoughts, and is less likely to abandon a good trading system in right before the next winning streak.  

-Andrew Falde

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