Portfolio Risk Analysis and Optimization of U.S. Technology Stocks: Evidence from Apple, Microsoft, NVIDIA, and Amazon Benchmarked Against the NASDAQ Composite Index

Abstract

With the rapid development of the U.S. technology industry, technology stocks have become a crucial component in investors' asset allocation. This paper examines four U.S. technology firms—Apple, Microsoft, NVIDIA and Amazon—and uses the NASDAQ Composite Index as the market benchmark, and conducts a risk analysis and optimization study on the U.S. technology stock portfolio based on Modern Portfolio Theory. Using daily stock price data from 2020 to 2025, this paper computes asset returns, conducts descriptive statistical analysis and correlation analysis, calculates Sharpe Ratios, and applies the mean-variance optimization model to construct the optimal portfolio. The research findings indicate that NVIDIA achieves the highest level of return while bearing the highest risk; Microsoft's performance is relatively stable; strong correlations exist among technology stocks, but there is still certain room for risk diversification. Compared with the NASDAQ index, the optimized portfolio obtains a superior risk-adjusted return, which verifies the effectiveness of Modern Portfolio Theory in U.S. technology stock investment. The research conclusions of this paper can provide theoretical support and practical reference for technology stock asset allocation decisions.