What is a primary flaw of using regression betas in stock performance estimation?

Using regression betas in stock performance estimation predominantly relies on historical data to calculate the relationship between the stock's price movements and the overall market's movements. This approach assumes that past behavior is an indicator of future performance. However, market conditions can change dramatically due to various factors such as economic shifts, changes in company management, technological advancements, and other unforeseen events.

Because regression betas are calculated based on historical data, they may not accurately reflect the current or future dynamics of the market or the specific stock being analyzed. In essence, while a stock may have shown a certain level of correlation with the market in the past, there is no guarantee that this relationship will hold in the future, especially if significant changes occur.

Other options like the reliance on future projections, lack of sensitivity to market changes, or accounting for market volatility do not encapsulate the primary issue with regression betas. The core flaw lies in their heavy dependence on historical performance data, which can mislead analysts when trying to predict future stock performance.