How to Define, Compute and Manage True Volatility of Stocks

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The most widely-used metric to determine the volatility of a given stock is known as the Beta which shows the volatility of a stock relative to the overall market (generally S&P 500). When the stock moves in perfect tandem with the market, the Beta is 1. Likewise, when the stock is more volatile, Beta > 1 and vice versa. In the above example, Cisco (CSCO) an Intel (INTC) are the two most volatile stocks while Procter & Gamble (PG) and Coca-Cola (KO) are the least volatile ones.

While Beta is an external metric, an internal metric in the form of a Coefficient of Variation (COV=Std Dev/Mean) may be computed using the daily closing prices. Then, the combination of the external and internal metrics would help create a more efficient and predictive volatility factor (V-factor). FYI - COV is a better metric than Std Dev as it is normalized.

Here is why the aforesaid V-factor is more efficient and predictive than the Beta: Though CSCO has the highest Beta, it has low internal volatility (daily movement of prices) as reflected in the low COV, thus lowering the overall V-factor significantly (down to 6.21), even lower than GE's which tends to move almost in lockstep with the market.

Of course, there are other methods to capture the volatility including modeling the daily swings. 

Data - The above matrix is compiled off of the aforesaid closing prices between 01-03-2017 and 11-03-2017.

Disclaimer - The author is not advocating any of the stocks listed here; instead, this is promoted as an alternative research in creating a statistically significant and more predictive volatility factor for individual stocks. Consult your Registered Rep, RIA or Financial Planner for an appropriate asset allocation model and the suitability of stocks and other holdings.  

--Sid Som

sidsom1@gmail.com