Working Paper: NBER ID: w10913
Authors: Eric Ghysels; Pedro Santa Clara; Rossen Valkanov
Abstract: This paper studies the ICAPM intertemporal relation between the conditional mean and the conditional variance of the aggregate stock market return. We introduce a new estimator that forecasts monthly variance with past daily squared returns -- the Mixed Data Sampling (or MIDAS) approach. Using MIDAS, we find that there is a significantly positive relation between risk and return in the stock market. This finding is robust in subsamples, to asymmetric specifications of the variance process, and to controlling for variables associated with the business cycle. We compare the MIDAS results with tests of the ICAPM based on alternative conditional variance specifications and explain the conflicting results in the literature. Finally, we offer new insights about the dynamics of conditional variance.
Keywords: Risk-Return Tradeoff; Conditional Variance; MIDAS Estimator; ICAPM
JEL Codes: G1
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| conditional variance of stock market returns (G17) | expected excess return (G17) |
| MIDAS estimated conditional variance (C51) | future stock market returns (G17) |
| business cycle variables (E32) | expected excess return (G17) |