We are running a linear regression to predict cross-sectional returns using 500 factors, but we only have 3 years of monthly data. The out-of-sample performance is terrible. What specific techniques would you use to adjust this model?

我们在用线性回归跑500个因子的截面收益预测，但样本量只有三年的月频数据。模型在样本外表现很惨，你会用什么具体的技术来调整这个模型？