Trading pullbacks – stunning results
Looking out at the Kuta surf, I can see surfers catching waves. They’re looking for troughs because they know that each trough means a wave is following. This reminds me a lot of trading pullbacks.
After my recent laborious stint in Papua New Guinea I’m currently spending a couple of weeks in Bali reading and relaxing in the sun at the beach. The surfers out beyond the breakers disappear into the troughs as they roll through. The troughs are pullbacks before each new wave, and soon I'll see a surfer re-appear on the crest of a wave and ride it for all it's worth.
This is pretty apt as part of my reading has been the works of trader Larry Connors, who is an advocate of buying pullbacks, not breakouts. His reasoning is that by the time a breakout occurs, a lot of the market knows about it and it’s probably almost out of puff.
Conversely, if a stock is in a long uptrend then it will periodically pull back before resuming.
Connors believes that a pullback is a display that fear has entered the market – thus some selling. His argument is that the fear will generally be exaggerated, the price will snap back and the trend will mostly resume.
I’ve never had trouble with this idea, but I've had trouble trading this idea. It’s psychologically very difficult to buy into a falling market – what if the current sell-off is the beginning of the down trend?
Connors goes further than propose the theory though – he did some qualitative analysis to check it out in about 2008/2009. He found that from 1995-2007 after the S&P had dropped 3 days in a row, it rose more than 4 times its average weekly gain in the next 5 trading days. And, after the S&P 500 had risen 3 days in a row, it had on average lost money over the next 5 trading days.
This sounded pretty intriguing so I coded the pullback rules he used into a test minion to see what happened.
The rules are really simple:
I tested from 1/1/2013 to 1/10/2018, which is Out of Sample with respect to Connors’ original test. I have to say that results are quite impressive. Here's the equity curve:
Here are some of the highlights:
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Also important: This test is somewhat constructed for the S&P500, other indexes work pretty well on these parameters, but not as good as the S&P500. However, it is extraordinarily robust just the same.
The test confirms the theory
This simple test confirms Connors data, and does so quite impressively. The test confirms that:
The data stacks up, but...
Even though the data shows the method is effective, it would take unusual courage to trade this way. Let’s take a real-world example to explore this.
It’s June 1st 2012.
You’ve been watching a log bull run on the S&P500. It peaked a couple of months ago and has been in decline since then. The media is talking about how the markets are falling and experts are talking about bad earnings reports and speculating about other causes for the downturn.
Then, you get this buy signal:
Would you buy?
Could a Trading Minion trade it?
Now let’s say that you have a trading minion in place to trade this kind of system. It doesn’t look at the chart or listen to the media or experts – it only looks at the data that was used to construct the rules.
So at the close of NYSE trade on June 1st, 2012, the minion detects the signal and without fuss, opens a BUY trade.Here’swhat actually happened:
The trade is a win, worth about $250 (with $R=100). Remember that in this test system, 68% of the trades are winners and look something like this.
The point is that trading pullbacks with a trading minion removes the challenging psychological factors from trading, and that is a huge edge to have.
I’m coming around to the opinion that trading pullbacks provide traders with a real edge.
While the data shows that pullbacks can be profitable, most traders don’t trade them because it’s psychologically very difficult; you need to be buying when everyone else is selling (and all the news is spouting doom and gloom), then selling just as thing are starting to look rosy again (when everyone else is buying).One of the adages that I live by is:
If you do what most people do, you get what most people get.
This approach is definitely not what most people do.
The three things I like most about this approach are:
- 1It’s contrarian – it’s doing what most people can't or won't do.
- 2The data shows that it works.
- 3I can use Trading Minions to automate it, thus taking care of the difficult psychological factors.
New Trading Minions on the way...
I’m already well advanced on testing some minions that I’ve developed based on these ideas, and the results are consistent with the test system described above.
Here’s a picture of my ad-hoc test lab, overlooking a pool and a rice paddy in Bali and connected to Daedalus, the big data-crunching computer under my house in Australia.
I’ll follow up in a few days with more info, and hopefully a gentle sun tan.