Stock Return Forecasting and Investment Choice--Application Based on GARCH Models and CAPM Models
DOI:
https://doi.org/10.54097/61nfje57Keywords:
Risk prediction, GARCH family model, CAPM model, Investment decision.Abstract
Asset price fluctuations are common in financial markets—for example, stock and bond prices change daily. This double-edged sword offers investors high return opportunities while exposing them to substantial risks, and accurate fluctuation prediction is critical for risk measurement and scientific investment.The 2024 State Council’s Opinions on Strengthening Supervision and Preventing Risks to Promote the High-quality Development of Capital Markets emphasizes regulating market behavior, enhancing risk monitoring, and improving the accuracy of risk prediction and investment decisions.Against this backdrop, this paper uses GARCH family models and the CAPM to predict stock risks and optimize investment decisions for investors’ quantitative choices, taking China’s A-share market as the research object. It fits GARCH models to stocks of four cross-sector core enterprises (Yangtze Power, Su Neng Stock, Daqin Railway, China Nengjian), confirming GJR-GARCH as the optimal model via AIC comparison and verifying the prevalence of leverage effects in A-shares—guiding investors to adjust leverage and positions. Additionally, it calculates beta coefficients of 50 cross-industry A-shares using CAPM, determines optimal portfolio weights through market weighting, and helps investors avoid blind following and achieve personalized investment.
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