A lot of modern equity theories and research is based on Betas or how individual stock movements relate to the underlying stock index. But much of the data is “dirty” or at best unreliable for basing investment decisions on. As noted in a previous article, betas for individual stocks can diverge quite significantly compared to the index over even the medium-term lengths. This opens the possibility that while individual investors can be basing their decisions on this data, the stocks they are considering can be greatly diverging from the norms. This post highlights some lists of stocks that are high beta stocks, low beta or negative beta, and stocks that have high percentage change in their respective beta.
The betas are derived from closing prices over the last quarter with at least 50 market days of data. Instead of data over the last 5 years assuming monthly returns (as others seem to be using), the analysis below is looking at short-term data and changes over the quarter compared to the last quarter. Betas for individual stocks can vary broadly over the long term (such as 5 years) and thus will not recognize either convergence or divergence from correlation with the market. Thus, any investor relying on outdated data may be greatly disappointed by changes in the betas in their portfolio by either experiencing higher volatility or lower than expected returns compared to the market.
TICKER
Name
beta
Std_Error
The above table shows the lowest betas including negative ones along with the standard errors of the betas derived from the linear regressions. This shows that while there a few negative betas, but none are significantly different than zero. Specifically, that means that the true beta could easily be with-in the range of zero. While that would negate the positive aspects of negative betas, it does provide stocks that are not reacting to the market forces and thus can reduce market risks. But conversely it does reduce idiosyncratic risks of the individual stocks.
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