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Feature
 Understanding Market Type
by
Van
K. Tharp
This is the first of a series of articles on
market type. For example, in the update for this month I said that the market type for the S&P 500 index was SIDEWAYS VOLATILE. That prompted someone to ask, “How can you say that we are in a sideways market when the market has gone up so much in the last two months?” And that’s all the more reason for a discussion of
market type. Market type depends upon how you define it. Right now I’m actually looking at three different measures of
market type and they couldn’t be showing more different results. Here are the results for 2009 as of May 15th.
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This is the perfect time to do such an article because all three models are showing a different market type and Methods 2 and 4 are as far apart as two models could be. So let’s look at what each model does and why.
Understanding Method 2
Method 2 is my original market type that I have been publishing in our monthly updates in
Tharp’s Thoughts. It started with The Definitive Guide to Position
Sizing. In that book, I said that market type should be determined quarterly. And that’s an important point: My time frame is three months. That’s why I can say that the market is sideways over three months even when it has been going up over the
past two months—especially if the first month down is much more than the last two months of up
movement.
Anyway, my idea was that if you put a quarterly chart on the market, a bull and bear market should be obvious. And if you couldn’t tell, then the market was sideways. And in my book, that was my first way of doing classifications. However, I wanted something I could do weekly and mechanically and that required a revision. I couldn’t just look at a chart and have it be mechanical. In addition, I had to do 13 week rolling windows.
I then came up with the following idea. What was the average 13 week change over many
13 week windows? That turned out to be useless because the up and down periods cancelled themselves out. The actual change was 1.7% over a 58 year period from 1950 through April 2009. Thus, I went with the absolute value of the 13 week change. This turned out to be 5.58% and I made the arbitrary decision that any change, positive or negative, that was less than 5.58% was a sideways market. This means that a positive change greater than 5.58% was a bull market. And a negative change less than 5.58% was a bear market. And I could now do this with 13 week rolling windows.
Next, I had to decide how to distinguish volatile and quiet markets. My original thinking was to look at the weekly changes as a measure of volatility. What was the average weekly change? Were at least 7 weeks above average? If so, we had a volatile market. If not, we had a quiet market. But the problem with that measurement was that the weekly change could be very small while the price range during the week could be huge. Thus, this idea didn’t work some of the time.
To overcome this limitation, I decided to look at the Average True Range—a much more traditional measure of volatility instead. I’d look at the mean weekly ATR over 13 weeks over many time periods. My first thought was that if the ATR was above average, then we had a volatile market and if the ATR was below average, then we had a quiet market. This was a great idea, but it turned out that for the S&P 500 most markets before 1997 were quiet and most markets from 1997 on were volatile. This was because the price of the index had a major impact on the volatility. Thus, I had to take the 13 week ATR as a percentage of the price of the S&P 500 index. Over 58 years this mean turned out to be 2.95 with a standard deviation of 1.45. Thus a volatile market was defined as one in which the ATR% over 13 weeks was greater than 2.95. A quiet market was defined as one in which the ATR% over 13 weeks was less than 2.95. The chances of getting one at the average was very slim because we went out many decimal places.
So the following is a distribution of 13 week periods falling into each market type with our new definitions, defined as Method 2. The last 3,000 periods are included in the table. Notice that 58.87% of the markets are defined as sideways. Conventional wisdom says that markets trend about 30% to 40% of the time, so my definition is pretty good. 12.37% of the markets are bear and 28.77% are bull. Thus, there are about twice as many bull than bear markets.
In addition, the table shows that 39.87% of the markets are volatile, while 60.13% of the markets are quiet. Again, this seems to fit conventional wisdom.
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Understanding Method 3
Method 3 probably wouldn’t exist except for the fact that
Method 2 was developed and tested under market conditions in which I could get weekly changes in the S&P 500 of 10% or more. My biggest concern, since we were using rolling windows, was that a market type could change, not because of what happened in the most recent week, but because of what was dropped that occurred 14 weeks ago. For example, if the market dropped 14% 14 weeks ago and that change was dropped, then the market type could change from bear to bull even if the latest week’s price change was down 1%—just because the 14% drop was no longer included.
Method 3 made one minor change to the method by substituting a 13 week exponential average for the last week. In other words, the market type was still determined by absolute change over 13 weeks, but the last week was an exponential moving average rather than the exact change that happened 13 weeks ago.
Notice that Method 2 moved to volatile
bull on the week beginning May 4th. But Method 3 has stayed at volatile sideways. Method 3 also produces smoother results. For example, Method 2 had four weeks of volatile sideways in the first two months of 2009 whereas Method 3 remained in a volatile bear mode. Let’s see how our distributions change as a result of what happens in the first week of our 13 week window. These are shown in the next table.
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Notice that while our results are smoother, the distribution of market types is pretty similar. We are 60% sideways and 60% quiet. Bull markets are still twice as prevalent as bear markets.
Understanding Method 4
Now let’s look at a totally different method that comes from Ken Long. Ken started working with a traditional definition of bull and bear. A bull market is when prices are above their 200 day moving average and a bear market is when prices are below their 200 day moving average. Ken, however, also wanted a sideways measure. As a result, he developed a 2% band around the 200 day moving average. When prices are within that band, the market
is sideways. When prices are more than 2% above the 200 day moving average, the market is a bull. And, lastly, when prices are more than 2% below the 200 day moving average, the market is a bear.
Notice that because Method 4 uses a much longer time frame (i.e., 200 days) it still classifies the market as bearish. Even with a two month rally, the market is still more than 2% below the 200 day moving average. And thus, Method 4 still says we are in a bear market. Notice that with this definition, the 200 day moving average could be moving at a sharp angle (up or down) and if price were staying close to it, the market would be considered sideways.
So how does Ken measure volatility? Ken again uses the ATR as a percentage of the price. He looks at the 14 day ATR% windows over 100 days. He finds the mean ATR% over 100 14 day windows and the standard deviation. When the ATR% is within one standard deviation from the mean, the market is considered to be normal. When the ATR% is more than one standard deviation above the mean, he calls the market volatile. And lastly, when the ATR% is more than one standard deviation below the mean, he calls the market quiet.
We used Ken’s model on weekly changes to the S&P 500 (Ken looks at daily changes in the SPY). We used the 40 week moving average instead of the 200 day—almost no difference here. However, we had a major difference in how we calculated the volatility. We used a 13 week ATR, computing the mean and the standard deviation as rolling windows. If the price ATR% for this week was less than one standard deviation below the mean of the last 13 weeks, the market was considered to be quiet. If the price ATR% for this was greater than one standard deviation above the mean of the last 13 weeks, it was considered to be volatile. And if neither of those statements were true, then the market was considered to be quiet.
We are actually taking some strong liberties with Ken’s method by using the weekly data. First, 13 weeks is only 65 days. Ken uses 100 days. He also uses 14 day ATR%, finding the mean and standard deviation over 100 days. We are using 13 week ATR percentages finding both the mean and the standard deviation. There is a huge potential difference here.
Thus, Ken has nine market types. The next table shows the distribution of market types over the last 58 years using Ken Long’s market types.
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I’m not at all happy with these distributions, so we’ll need to recalculate those using daily data. With over 3,000 13 week windows, we are getting 38%
normal markets, 29% volatile, and 33% quiet markets. Even more amazing (and this should be accurate according to Ken’s method) is that 58% of the markets are considered to be bullish, 25% are bearish and only 18% are sideways. This is probably because prices are only within the 2% 200 day moving average only about 18% of the time. This does not fit the conventional wisdom that markets are sideways 60-70% of the time.
Conclusions
First, the time frame of the market type makes a huge difference in your conclusion. Thus, a 13 week method can show the market as bullish whereas a method based upon the 200 day moving average can show the market as
bearish.
Second, market type is very individualized based
on how you trade. Day traders and swing traders will have an entirely different view of market type than longer term traders or investors.
Third, minor assumptions in how you calculate market type can make a huge difference in the conclusions you make. I plan to start using Method 3.
In my next article on market type, I’ll include daily calculations so that we can accurately represent market type and we’ll look at the daily, and weekly predictive value of the various market types.
About
Van Tharp: Trading coach, and author, Dr. Van K. Tharp is
widely recognized for his best-selling books and his outstanding
Peak Performance Home Study program - a highly regarded classic
that is suitable for all levels of traders and investors. You can
learn more about Van Tharp at www.iitm.com.
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Because Size Really Does Matter in the
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