Now let’s take a quick look at the price of the SPDR S&P 500 ETF (SPY) over the same time period:
Figure 3: SPY Prices
You can see that volatility tended to spike upwards when the market declined sharply. Also, from January through April of 2013, the market rallied steadily, which coincided with a period of particularly low volatility. So how did our short strategy do during this market surge?
To start, let’s look at the strategy variations that produced the highest Average % P/L over our entire backtesting period, which was from January 1, 2001 through April 30, 2013. Variations that produced fewer than 200 trade signals over the 12+ year testing period have been filtered out so as not to skew the results. Also, for simplicity some of the strategy-specific columns have been removed from the table below.
Top 20 Variations Based on Average Gain, January 2001 – April 2013
Notice that over the long haul, the strategy variations that have generated the largest gains are the ones that have strict entry criteria like a ConnorsRSI value above 90 and a relatively large limit order like 10%. Now let’s compare the variations that have performed the best in 2013:
Top 20 Variations Based on Average Gain, January 2013 – April 2013
In this table, we have filtered out variations that produced fewer than 20 trade signals in 2013. You’ll notice that the average gains are somewhat lower than the best performers from the previous table, but are still a very respectable 5% – 7% per trade in one of the strongest bull markets of the past several years!
However, you’ll also see that these are not the same strategy variations that have produced the best 12-year performance. Rather than using strict entry criteria across the board, these recent top performers tend to mix some strict criteria with some more lenient ones, for example an Entry ConnorsRSI value of 90 and a 4% limit order, or conversely, a ConnorsRSI value above 75 with a 10% limit order.
There are a couple of takeaway messages here. First, a robust strategy can often be successful even in market environments that might seem to be counterproductive to that strategy’s goals, for example trying to short stocks in a bull market. Second, to optimize your performance you may have to adjust the strategy parameters to match the current market conditions. The best way to do that is to start with a well-defined quantified strategy, and then to make sure you thoroughly understand how each element of that strategy affects the overall performance so that you can make the appropriate adjustments.
Click here to if you’d like to learn more about how to apply a quantified trading strategy to shorting stocks during a bull market.