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This research outlines an advanced investment strategy for a diversified 20-stock U.S. portfolio, leveraging Yahoo Finance data for optimization. Utilizing a momentum strategy, the study refines stock weights based on historical performance, incorporating dual moving averages for precise trading signals. A novel approach introduces Exponential Moving Averages (EMAs) and risk-adjusted scores to enhance decision-making, striking a balance between returns and associated risks. In the past one year period from February 1, 2023 to February 1, 2024, the annual return rate can be achieved according to this method of 36.81%, the strategy showcases the effectiveness of data-driven, technical analysis in financial mathematics. It demonstrates the utility of sophisticated investment techniques for market performance optimization, contributing valuable insights into portfolio management.The study highlights the potential of leveraging advanced algorithms and financial indicators to outperform traditional market strategies. This innovative approach provides a comprehensive framework for achieving superior returns, emphasizing the importance of technical analysis and risk adjustment in modern investment strategies.
Shuhan Guo (Thu,) studied this question.