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Tharp’s Thoughts
What Is an Efficient Stock?
by Van K. Tharp
A number of times, I’ve looked at efficient stocks and found that buying such stocks long produces a very good trading system. For example, from July 2006 through July 2007, during a quiet up market, 23 such trades produced a System Quality Number ™ of 4.08. That’s a better record than any of the newsletters I tracked in the 2nd Edition of Trade Your Way to Financial Freedom. As a result, we started a series here in which I was looking at trading efficient stocks within the S&P 500. The initial results looked quite good, but the results got much poorer as we began to filter out various errors and assumptions that we were making. The results were acceptable, but not as good as the two times that I’ve publicly traded such stocks through my newsletters, (i.e., see Tharp’s Thoughts July 18, 2007 and in Market Mastery, issue # 111).
However, before we do any more research on the topic of efficient stocks, we needed to know if we were actually trading efficient stocks. I asked for volunteers to find charts and review them to see if these were actually stocks that met my criteria. First, the efficiency was calculated and we only looked at stocks with a composite efficiency over +8 in the S&P 500 on the first trading day of the month. We then looked at two sorting algorithms based upon smoothness and only bought the top 10%, based upon those algorithms. The first was the standard deviation of the daily change in the close (close minus close) over 180 days. This gave us great results, but was biased toward low priced stocks. As a result, we also looked at the standard deviation of the daily close divided by close over the 180 days as a smoothing function.
I’ve now had three volunteers (thank you, guys!) look at nearly 200 stocks from both smoothing functions to tell me whether not they were efficient. One volunteer did 191 of the close minus close smoothing functions and concluded that only 49.2% were efficient. Two volunteers worked on the smoothing function: one concluded that 33% were efficient and the other concluded that 35% of them were efficient. Those results basically told me that we were probably not looking at stocks that I wanted to trade and that I needed to go back to the drawing board with our algorithms.
However, I then started to look at the charts. I’d told my volunteers to look at the price for the six month period prior to the entry to determine whether or not the stocks were efficient or not. But when I started to look at what they were defining as “efficient and not efficient,” it was clear to me that everyone had a slightly different interpretation.
I’ve always thought that my definition of efficiency was fairly subjective – the stock is going up in a fairly smooth line. But this exercise told me that my criteria are a lot more detailed than I thought.
So let me give you some new ideas that typically describe what I thought was a fairly subjective decision.
First, the risk-reward ratio is important to me. Thus, if I’m using a 25% trailing stop, I’d like something that I believe has the potential to go up 75 to 100%. Thus, the first thing I’d like to do is eliminate those stocks that don’t have that potential. I believe I have two criteria here. First, I don’t want to trade something that is approaching a prior high that could provide a strong resistance point. Thus, the stock might have been going up for six months in a straight line, but if it’s right at an old high for say six months or a year ago, I’m not interested in trading it. Figure 1, illustrates this sort of stock, which is approaching some potential resistance at around 39 and 47. Neither support area, with a 25% trailing stop, gives me a good reward to risk ratio.
Figure 1: No Good Reward to Risk Ratio
Next, the stock doesn’t necessarily have to be at an all time high (or at an all time high with a slight retracement), but if it had much higher highs (i.e., say in 1999 to 2000), then I want it to have the potential of at least a 3R move before it reaches those highs. Figure 2 gives a good example of a stock that I’d avoid based upon these criteria. Here QCOM looks very efficient, but it is approaching its 2001 highs.
Figure 2: Avoid These Stocks Because They Are too Close to Old Highs
Next, I believe that something that is starting to become parabolic is probably nearly the end of its potential move. Now that was not necessarily true in 1999 when stocks could easily move 5% each day and have the potential to go up another 100 to 200%, but the stocks that did that also tended to fall 25% or more in a single day when the move was over. As a result, I tend to avoid stocks when the upline gets too steep. Figure 3 is an example of something that I’d probably avoid simply because the line is too steep.
Figure 3: Avoid These Stocks Because They Are Parabolic
With these three criteria as a background, let’s look at the kind of chart I’m looking for. First, although I’m looking for six month efficiencies (i.e., I’d like something that’s been going up for six months), I’m fine with something that’s been going up for three of the last six months as long as it is higher than it was six months ago. In fact, I looked at one example that was up for four months, flat for four months, and then up again for another month (BMS in early 1981). That is illustrated in Figure 4.
Figure 4: Efficient Stocks That is In a 9 Month Uptrend but Only Recently Started to Go Up Again
Stocks I’d trade, however, do not need to be at new six month highs. In fact, I’d generally prefer something that’s done a slight retracement. These stocks are often great buying candidates. And, although I’m using 25% trailing stocks, simply because I want to hold them a long time, others could do well trading these stocks by using the retracement amount (i.e., once the trend resumes) as the potential stop. However, these could produce very short term trades, so I don’t trade them.
However, overriding the retracement is one very important criterion. The current up movement is usually defined by some sort of trendline. I am not interested in buying anything in which the trendline has been broken. Will it keep going down? I have no idea, but I think the chances are much better when the trendline is broken, so I no longer call them efficient stocks.
Figure 5 shows an example of a stock that I’d trade even though it is not making new highs. The overall trendline is still intact and thus I’m fine with it. Figure 6, in contrast, shows something that I’d avoid, at least temporarily.
Figure 5: Efficient Stock with an Intact Trendline
Figure 6: An Efficient Stock That’s Broken Its Trendline
As I said, I’d avoid the stock in figure 6, but it could be a great trading stock if it goes on to make new highs. I also wouldn't trade Figure 7 because it's too volatile.
Figure 7: Going Up But Too Volatile
These criteria pretty much determine what I look for visually in a stock when I do my efficiency trades. As a result, I looked at the charts I’ve been sent based upon these criteria. In some cases, I did not have enough data to determine if the stock was close to old highs. If that was the case, I just assumed that it wasn’t. As a result, I’m being conservative in the amount of stocks that I’m assuming that I’d trade from each of the smoothing algorithms.
Close Divided by Close Algorithm
I’d probably accept about 53% of the trades that the computer took. This is considerably above the 33-35% taken by the reviewers, but it still suggests that the computer algorithm is taking too many trades that I would not normally take. I’d need to see at least a 75 to 80% agreement to even consider using the algorithm.
Close Minus Close Algorithm
With the close minus close smoothing filter, I estimated that I’d take about 62.6% of the trades that our algorithm took. Our volunteer estimated that 49.2% were efficient using his interpretation of efficiency. With these trades, however, I couldn’t see far into the past to see if we were approaching any old highs. With that information added, my guess is that I would have taken less than half of the trades.
Conclusion
Our efficiency algorithm, despite acceptable results, does not resemble the kind of trading that I want to do. As a result, our new plan is to modify the criteria and the repeat some of the research we’ve been doing.
About Van Tharp: Trading coach, and author, Dr. Van K. Tharp is widely recognized for his best-selling book Trade Your Way to Financial Freedom and his outstanding Peak Performance Home Study program - a highly regarded classic that is suitable for all levels of traders and investors.
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