How deeply does Investing for Programmers cover Sharpe ratio?

Calculates the ratio inside portfolio simulation and visualization, while distinguishing it from the broader efficient-frontier criterion.

Sharpe ratio

As explained in Investing for Programmers

The Sharpe ratio is a portfolio performance measure that compares excess return over the risk-free rate with the portfolio's volatility.

The Sharpe ratio measures risk-adjusted portfolio performance by comparing excess return over the risk-free rate with portfolio volatility. Higher values indicate more return per unit of risk, but the portfolio with maximum Sharpe ratio need not be the only Markowitz-efficient choice. section 7.6.1

Portfolio screening example

Using three years of prices for AAPL, WMT, GOOGL, KO, PFE, BRK-B, and NVDA, the calculation samples 10,000 portfolios and produces optimal weights, including substantial allocations to NVDA and PFE.

How Investing for Programmers covers it

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Also explained in

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Build a Robo-Advisor with Python (From Scratch)The Sharpe ratio is the expected return above the risk-free rate divided by the investment's volatility, measuring expected reward per unit of risk.

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Related concepts

risk-adjusted returnmeasures · Risk-adjusted return is investment performance evaluated relative to the amount or type of risk taken to achieve it.
information ratioequivalent to · The information ratio is the expected return above a benchmark divided by the volatility of the portfolio's return difference from that benchmark.
alphacontrasts with · Alpha is investment performance beyond a relevant benchmark or the return explained by specified systematic risk factors.
risk-free returnused by · Risk-free return is the theoretical return on an investment assumed to have no default or other relevant uncertainty risk over a specified horizon.
tangent planeequivalent to · A tangent plane is the plane that locally best approximates a smooth surface at a specified point.
slopeproduced by · Slope is the rate at which a dependent quantity changes relative to an independent quantity, often represented by a line’s gradient or a coefficient in a linear relationship.

This explainer was generated by Manning's knowledge graph from the text of Investing for Programmers. The section links point to the parts of the book it draws on.