Portfolio Optimization
Portfolio optimization is a mathematical framework used in finance to select the best combination of assets (e.g., stocks, bonds) to maximize returns for a given level of risk or minimize risk for a target return. It involves techniques like mean-variance optimization, which quantifies risk as variance and uses algorithms to find efficient portfolios. This concept is foundational in quantitative finance, investment management, and algorithmic trading.
Developers should learn portfolio optimization when building financial applications, such as robo-advisors, trading algorithms, or risk management tools, as it enables data-driven investment decisions. It's essential for roles in fintech, hedge funds, or banking where optimizing asset allocation improves performance. Use cases include automated portfolio rebalancing, backtesting strategies, and constructing diversified investment products.