liveBook · Manning

Beta

Beta is a measure of an asset’s sensitivity to movements in the overall market, conventionally assigning the market portfolio a value of one.

How 2 Manning books explain it

Build a Robo-Advisor with Python (From Scratch)

Beta is a measure of an asset's sensitivity to movements in the overall market, with the market portfolio conventionally assigned a beta of one.

How it is used
Estimates CAPM expected returns for asset-allocation inputs by scaling the market risk premium.
How deep it goes
Defines beta, interprets low and high values, and implements an excess-return OLS regression without detailing regression diagnostics.
Examples
Uses AAPL, FE, and WMT, SPY market data, 3-month T-Bill rates, and an AAPL beta of 1.3187.
What you can do after
Apply it via pandas-datareader, yfinance, and statsmodels to estimate beta and calculate CAPM expected returns.

Read how Build a Robo-Advisor with Python (From Scratch) explains beta →

Investing for Programmers

Beta is a measure of an asset's sensitivity to movements in the overall market.

How it is used
Uses beta to compare market sensitivity and inform risk assessment, portfolio choices, and predefined responses to changing risk levels.
How deep it goes
Defines three beta ranges and illustrates them with companies, but does not derive or calculate beta from price data.
Examples
Compares NVIDIA at 2.12 with Walmart at 0.69 and relates their beta values to technology and supermarket demand.
What you can do after
Evaluate an asset’s relative market sensitivity and distinguish market-linked volatility from company-specific risk.

Read how Investing for Programmers explains beta →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.