Beta | Linear Regression
Hi @all,
this might seem like an odd question, but during my internship I had the task to derive the beta of a stock. As learned in college, I plotted the stock return and the market return and did a linear regression.
Now my question: How can one be sure that the movement of the stock return is actually driven by market risk. How can we say that the relation between stock return and rm is actually causal? Even though it might be highly unrealistic, the stock could always been driven by firm-related events or am I thinking wrong?
Would be happy to discuss & get some replies!
Not 100% positive but I would imagine that doing it for enough years say 10+ and trying different weekly increments (Mon.-Mon, Wed-Wed) would cut out the majority of any possible outside noise. Another way to calculate beta is to find comparable companies and their beta (use Bloomberg or yahoo finance). Unlever the beta and find the median of that set and then re-lever the beta to your company's beta. Hope that helps.
Thank you!
You're 100% right you don't know if it's market beta or company-related news. However, this method is an easy way to show the relationship from a high level. The step would be to fundamentally understand business and market drivers then check for similarities. However, this is difficult to do for thousands of stocks.
Thanks a lot!
One thing I like doing is using a group of comparable companies as the market when calculating a regression beta. I always note the change in assumption, but I think it’s very helpful. For example, when evaluating an airline I might use the return data of an airline ETF. This shows the company’s historic out/underperformance relative to a list of its peers.
The beta coefficient of a stock is a measure of the assets covariance in relation to the overall market. The regression measures the slope within the data points and represents the assets volatility. Basically, If an asset has a beta of 2 it means that when the market swings, it will swing 2x (in whatever given direction) compared to the market. You can attribute the additional volatility as idiosyncratic risk.
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