Market Beta/Beta Coefficient for CAPM [Loxx]

14 Okt 2022

Market Beta/Beta Coefficient for CAPM [Loxx] is not so much an indicator as it is a value to be used in future indicators to forecast stock prices using the Capital Asset Pricing Model, CAPM. CAPM is used by the likes of value investors such as Warren Buffet and valuation/accounting/investment banking firms. More specifically, CAPM is typically used in Discounted Cashflow Analysis to value revenue generating assets.

What is Beta?
In finance, the beta (β or market beta or beta coefficient) is a measure of how an individual asset moves (on average) when the overall stock market increases or decreases. Thus, beta is a useful measure of the contribution of an individual asset to the risk of the market portfolio when it is added in small quantity. Thus, beta is referred to as an asset's non-diversifiable risk, its systematic risk, market risk, or hedge ratio. Beta is not a measure of idiosyncratic risk.

By definition, the value-weighted average of all market-betas of all investable assets with respect to the value-weighted market index is 1. If an asset has a beta above (below) 1, it indicates that its return moves more (less) than 1-to-1 with the return of the market-portfolio, on average. In practice, few stocks have negative betas (tending to go up when the market goes down). Most stocks have betas between 0 and 3.

How to calculate Beta

• To calculate beta you typically choose 5 years of monthly data; typically SPY is used here
  
• Calculate log returns of both the asset for which you are calculating Beta and the benchmark market data
  
• Calculation the covariance between the asset and benchmark
  
• Calculate the variance of the benchmark returns
  
• Divide the covariance by the variance
  

Read more here:
https://en.wikipedia.org/wiki/Beta_(finance)
https://en.wikipedia.org/wiki/Capital_asset_pricing_model
https://einvestingforbeginners.com/capm-assumptions-dcf/?doing_wp_cron=1665701111.7182419300079345703125

14 Okt 2022

Catatan Rilis

Simplified calculation by removing arrays. Also added another method that yields the same result.