With the year 2016 well behind us, it’s time to look at the very popular 2-period RSI trading method by Larry Connors and Cesar Alvarez. We all know there are no magic indicators but there is an indicator that certainly acted like magic over several decades. What indicator is it? Our reliable RSI indicator.
Over the past few years the standard 2-period trading model as defined in the book, “Short Term Trading Strategies That Work” has been making new equity highs.
The trading model as originally proposed by Larry Connors is very simple and it consist of long-only trades. As a reminder, the rules are as follows:
Furthermore, I just want to state that all the tests within this article are going to use the following assumptions:
During 2011 the market experienced a sudden and sustained drop which put the trading model into loss. Recall, the trading model had no stops. Since this drop the model has been slow and is now making new equity highs. Below is an equity graph depicting the trading model’s equity curve trading the SPX index from 1980. You can easily see the large drop around trade number 135.
Here is a closeup view of the last 28 trades, which covers about the last six years.
Below is the annual performance of this trading model over the past few years. We can see that years 2013 and 2014 in particular have seen a drastic reduction in the net profit. Is the strong bullish market which we have been experiencing over the past few years a temporary phenomena that is harming this trading model’s performance? Could be. Or is simply this trading model slowly losing its edge? Yet, the last two years (2015 and 2016) have seen a return to more “normal” performance.
Back in the year 2013 I explored the robustness of the trading parameters used by the 2-period RSI trading model. That article can be found here. Within that article a slightly modified version of the original trading rules was proposed. In short, I doubled the value of the RSI threshold value (from 5 to 10) and doubled the look-back period for the simple moving average exit rule (from 5 to 10). Finally, a stop value of $2,000 was added. I picked this value because it represents our risk value when scaling the number of shares to trade. Notice we are only risking 2% of our $100,000 account on each trade. Here is a summary of the rule changes.
Below is a table showing the difference between the original Connors’ rules and the modified Connors’ rules.
Our increase in net profit comes at the cost of more trades which is due to the fact of lowering the stand on what we consider a viable pullback. By increasing the RSI threshold from 5 to 10 more setups qualify as a valid entry, thus we take more trades. We also increased our look-back period for our exit calculation. Thus, we should be holding some of the trades a little longer in an attempt to make more profit. The stop value does hurt the performance of our model. For example, removing the stop value will result in $181,620 in profit with a profit factor of 3.06. However, we’re going to keep the stop in place because trading without a stop is something most people will not be doing! It will also help protect us from massive losing trades as seen in 2011.
The RSI indicator still appears to be a robust indicator at locating high probability entry points within the major market indices. You can modify the trigger threshold and holding period over a large range of values and still produce positive trading results. I hope this article will give you lots of ideas to explore on your own. Another idea with regards to testing parameters is to independently optimize the parameters over the “portfolio” of market ETFs instead of using just $SPX. There is no doubt in my mind the RSI indicator can be used as a basis for a profitable trading system.