Modern Economics & Management Forum

This paper designs and optimizes a series of quantitative investment strategies for the Shanghai and Shenzhen stock markets (2012-2019), leveraging volatility management and multi-factor models with Wind database data, to boost returns and stabilize portfolios. Using MATLAB, we simulate and visualize strategy returns. The initial strategy selects low-volatility stocks for equal-weighted investment based on historical volatility, outperforming the market but yielding unstable returns. To improve, we propose: 1) allocating weights inversely proportional to volatility, 2) incorporating market return factors into a multi-factor model, and 3) enhancing strategy stability via rolling window analysis. The multi-factor model strategy demonstrates superior risk control and stable returns across time horizons, appealing to long-term investors. The optimized weighting strategy suits short-term, high-risk investors. Lastly, we assess the rolling window's impact on long and short-term investments to analyze its strengths and weaknesses for stock picking.