方法证据记录
GARCH-MIDAS
GARCH-MIDAS decomposes volatility into short-term (GARCH) and long-term (MIDAS) components, allowing low-frequency macroeconomic variables to drive medium-term volatility while high-frequency returns govern daily fluctuations. Introduced by Engle and Ghysels (2012), this framework elegantly separates volatility time scales. The approach is powerful for understanding how macro conditions (growth, inflation) drive risk premia and for improved volatility forecasting.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
GARCH with Mixed Data Sampling
分类方法记录 · regression-model / econometrics
- Engle, R. F., & Ghysels, E. (2012). GARCH for long memory. Journal of Econometrics, 164(2), 385-391. · URL
- Ghysels, E., Santa-Clara, P., & Valkanov, R. (2005). There is a risk-return trade-off after all. Journal of Financial Economics, 76(3), 674-704. · DOI 10.1016/j.jfineco.2004.03.008
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