The importance of timing in estimating beta

The holy grail for scholars and practitioners of finance is to comprehend the behavior of equity returns. This research extends that comprehension by integrating methods from the field of bioinformatics into the capital asset pricing model. We examine 198,499 firm-year observations for stocks traded on the NYSE, the NASDAQ, and the AMEX from July 1963 to June 2014. Whereas the conventional models invoke beta as the measure of variability in equity returns, our model adopts the dynamic programming algorithm of (Needleman and Wunsch in J Mol Biol 48(3):443–53, 1970). It allows the incorporation of sporadic gaps in the daily returns to obtain the best fit between the returns of individual stocks and a broader equity index. In doing so, it demonstrates the importance of timing in estimating beta.