Hulbert uses his Hulbert Stock Newsletter Sentiment Index (HSNSI) as a principal quantitative tool in formulating his market outlook, we evaluate the usefulness of that index in predicting stock market returns rather than his qualitative commentary. HSNSI “reflects the average recommended stock market exposure among a subset of short-term market timers tracked by the Hulbert Financial Digest.” Mark Hulbert presents HSNSI as a contrarian signal for future stock returns; when HSNSI is high (low), he views the outlook for stocks as generally bearish (bullish). Using a sample of 262 values of HSNSI over the period 7/22/02-8/18/11 (generated by searching MarketWatch.com for “HSNSI” and its predecessor “HSSI”) and contemporaneous daily closes of the S&P 500 Index, we find that:
The average value of HSNSI for the sample is 23.8%, with standard deviation 25.9% (high volatility). The high for the sample is 67.8% (on 11/20/06), and the low is -36.1% (end of September 2008). Assuming normal variable distributions, the sample is large enough to test predictive power with reasonable reliability for short-term stock returns (a few trading days or weeks), but is not large enough to test HSNSI reliably as a long-term stock market indicator. The sample may be biased due to selection and clustering, because Mark Hulbert may be more likely to cite HSNSI, and cite it frequently, when either HSNSI or stock market behavior is extreme.
The following chart superimposes the HSNSI sample on a plot of the S&P 500 Index. The blue dashed line is the average HSNSI for the sample. As noted, HSNSI has high variability. Visual inspection suggests that HSNSI, like many other sentiment indicators, tends to be high (low) during market advances (declines). It is difficult to discern whether HSNSI reliably leads the stock market.
For precision, we examine how HSNSI relates to future S&P 500 Index returns.
The following scatter plot relates the return on the S&P 500 Index over the next five trading days to HSNSI over the entire sample period. The Pearson correlation for the two series is -0.16, indicating some tendency for the stock market to be relatively weak (strong) when HSNSI is high (low). The R-squared statistic is 0.02, indicating that variation in HSNSI explains 2% of the variation in stock market returns over the next five days.
Using future return intervals of 21 and 63 trading days yields R-squared statistics of 0.00 and 0.00, respectively, for the relationship between HSNSI and future stock market returns. In other words, there is practically no relationship between HSNSI and future monthly or quarterly stock market returns.
Note that the sample may have some selection/clustering biases at this point. Clustering leads to some overlap of future return intervals, effectively reducing sample size and perhaps overweighting extreme values of HSNSI. Clustering could also confound a trading rule that specifies entry/exit based on values of HSNSI. What happens if we alleviate clustering?
Source:
http://www.cxoadvisory.com/3265/sentiment-indicators/mark-hulbert/'via Blog this'
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