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 Thus, any investor relying on outdated data may be greatly disappointed by changes in the betas in their portfolio by either experiencing higher volatility or lower than expected returns compared to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.

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.

The next table shows the highest beta stocks in the sample. A portfolio composed of those stocks would basically be a multiplier of 2 times the market. This is great for up markets, but down markets drive the portfolio 2 times the market loss. Other investors might find value in shorting such stocks as it would take less percentage of the portfolio for the same level of hedging.

The next two tables show the biggest percentage gains and declines in betas respectively. The two time periods have at least 50 market days before December 25th and October 27th for 2017 for each stock. The tables also include the latest values for beta and the standard errors for the betas. As stated earlier, betas can and do change over time, thus it behooves investors to keep a watch on the betas of stocks in their portfolios.

Lists like the ones above could be used to discover stocks that balance market risks or even create portfolios like the single index model or risk budgeting for efficient portfolios. If any of the information and data was useful or interesting, I would love to hear from you. I hope that everyone that finds the information interesting to express what they like or what areas could be expanded and improved upon.

Since investors have different time frames for the investment decisions, a tool like this could provide betas over daily, weekly, monthly, or even quarterly by entering the stocks to watch.