Feature
Market Type: Hong Kong
by
Van K.
Tharp, Ph.D.
When you have a trading system, you should always know how it performs under various market conditions. In fact, one of the biggest mistakes you can make is to attempt to use a system for a market type for which it was not designed.
Ken Long (who will be teaching our ETF workshop in Germany) recently said that instead of wondering why your system isn’t working in the current market, you should be wondering what kind of system is working really well under these conditions.
We’ve now settled on a market type measure that uses the 20 day ATR (as a percentage of the close), in comparison with its historic mean and standard deviation, to measure volatility. We’re now using the following guidelines:
- Normal: The average ATR% plus or minus 0.5 standard deviations.
- Quiet: Anything less than a 0.5 standard deviation below the mean.
- Volatile: 0.5 standard deviations to three standard deviations above the mean
- Very Volatile: Anything greater than three standard deviations above the mean.
Incidentally, this results in an inverse Gaussian distribution. Thus, in the future I may take steps to normalize it based upon the high and low of the distribution.
So far, I’ve covered the Australian and German markets. This week I’ll be covering the Hong Kong market (in lieu of the Chinese market as I have a lot of data for the Hang Seng Index). Yahoo! has
4,827 days for the Hang Seng Index (^HSI). Thus, for the 200 day market type I
have data going back to October 18th, 1990.
The mean ATR% for those 4,827 days was 1.93 and the standard deviation was 1.02. This is quite similar to our U.S. data for nearly 15,000 days of data in which the mean is 1.30 and the standard deviation is 0.72.
The following table shows the distribution of our 4,627 days in these four categories.
Very Volatile
|
Volatile
|
Normal
|
Quiet
|
Total Days
|
79
|
964
|
1,855
|
1,729
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4,627
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The next table shows the average percent change in the Hang Seng index during each of the four volatility-based market types.
Average Percent Change
|
Very Volatile
|
Volatile
|
Normal
|
Quiet
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-0.12%
|
-0.04%
|
0.05%
|
0.13%
|
Again, we see that the more volatile the market, the more likely the price is to go down, just like the U.S. market. Similarly, the more quiet the market, the more likely the price is to go up (with both normal and quiet days being generally up days).
Let’s look at what happens to the market the next day after a given market classification. Here we are asking the question, “If the markets are highly volatile on March 3rd, what is the average percent gain on the following day (i.e., March 4th), regardless of the market type that day?” This data is shown in the next table.
% Change Next Day
|
Very Volatile
|
Volatile
|
Normal
|
Quiet
|
0.37%
|
-0.02
|
0.02
|
0.10
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And just like the U.S. market, but unlike the Australian market, we can expect the day that follows very volatile markets to be up.
Now let’s combine our five market types (defined in a previous article) with our four volatility types and see what we can expect. In this case we are using the 100 day SQN™ on the daily percent change to determine market direction. By the way, I’m simply looking at the daily percent changes in the index and doing an SQN based upon that (rather than R-multiples).
%
|
Very Volatile
|
Volatile
|
Normal
|
Quiet
|
|
Strong Bull
|
0.000
|
2.096
|
8.947
|
9.358
|
20.40
|
Bull
|
0.000
|
6.549
|
12.146
|
19.321
|
38.02
|
Neutral
|
0.130
|
3.220
|
8.234
|
6.268
|
17.85
|
Bear
|
0.670
|
5.641
|
7.802
|
2.421
|
16.53
|
Strong Bear
|
0.908
|
3.328
|
2.961
|
0.000
|
7.20
|
|
1.71
|
20.83
|
40.09
|
37.37
|
100.00
|
Just like the U.S. Market, we only see bear and strong bear markets when the market is very volatile. 91.7% of the bull and strong bull markets occur under neutral and quiet conditions. But when the market is very volatile, then it is either a bear or strong bear market 92.4% of the time.
Let’s look at our total market type and the average percentage gain/loss that is likely to occur under each market type condition. This is shown in the next table. There are no real surprises here.
Average Change %
|
Days
|
Very Volatile
|
Volatile
|
Normal
|
Quiet
|
Strong Bull
|
0.0000
|
0.1345
|
0.2500
|
0.2393
|
Bull
|
0.0000
|
0.0216
|
0.1192
|
0.1364
|
Neutral
|
-0.6268
|
0.0863
|
-0.0953
|
0.0047
|
Bear
|
1.5051
|
0.0663
|
-0.0446
|
-0.0225
|
Strong Bear
|
-1.2520
|
-0.5781
|
-0.2365
|
0.0000
|
The data are pretty much expected except for the plus percentage for the bear market condition under volatile and very volatile conditions.
Some History
Now let’s look at the last year’s worth of data on market type. I’m going to use the 100 day SQN to determine market type but show you the 200, 50, and 25 days SQNs as well. Remember that I use the following SQN ranges to determine the market direction, so you can translate the other SQN days to market types.
Strong Bull
|
>
|
1.5
|
Bull
|
>=
|
0.3
|
Neutral
|
|
the rest
|
Bear
|
<
|
-0.3
|
Strong Bear
|
<
|
-1
|
The data as of Friday’s close is quite a bit different from the U.S. markets. First, the Hong Kong Market has been volatile for most of the year, but not very volatile. Second, the Hong Kong market moved out of bear territory (at least for the 100 day SQN) on March 16th. And finally all four measures are bullish, with the 100 day average being strongly bullish. The Hong Kong market is much easier to interpret than the U.S. markets. Notice that the high of the last year was on Friday and the low was March 9th. Sound familiar?

Click here to see
a larger image of the chart.
The Hang Seng index is up 38.89% this year compared with 24.66% for the NASDAQ and 8.42% for the S&P 500. Does this really represent China? Well, Hong Kong is controlled by China, but it is almost a separate country. For example, I have to get a visa to go to China in September, but if I were going to Hong Kong, no visa is required. And the Shanghai composite index is up 85.23% so far in 2009.
I’ll be looking at up to ten markets. Next week will be our regular update. Then in two weeks, we’ll be looking at the London FSTE, plus I’ll revisit the three markets we’ve already covered.
My plan is to look at Brazil and then Gold, Oil, Commodities (in general), the U.S. dollar, and the Euro. That will give us the ten markets that I’ll continue to update once each month.
All of this work was done with the XLQ add on to Excel with the help of Leo van Rijswijk, the developer
of XLQ.
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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