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Efficient frontier

As explained in Investing for Programmers

The efficient frontier is the set of portfolios that provide the highest expected return at each level of risk or the lowest risk at each expected return.

The efficient frontier is the set of portfolios offering the highest expected return for a given standard deviation, or the lowest risk for a given return. Diversification combines assets to balance return and variance rather than maximize return alone. section 7.6.1

Illustrative allocation

Using three years of data for seven stocks, the calculated allocation assigns 63.6% to NVDA, 29.3% to PFE, and smaller weights to the remaining assets. Historical estimates can change, so the result is a decision aid rather than a guarantee.

How Investing for Programmers covers it

How deep it goes
Defines frontier efficiency and demonstrates randomized portfolio calculations, stopping short of guaranteeing future performance.
Examples
Uses three years of prices for seven named stocks, randomized portfolios, a frontier plot, and an optimal-weight table.
What you can do after
Build it from scratch with Python, NumPy, pandas, Matplotlib, and yfinance, then inspect candidate allocations and risk metrics.
How it connects
Links modern portfolio theory, diversification, variance, standard deviation, Sharpe ratio, and the risk-free rate.

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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.