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Crossproduct Effect and Volatility Forecasting
DOI:10.1002/for.3223.png)
摘要
En 中文
This paper explores if the crossproduct of return and realized volatility measure contributes to volatility forecasting. We find there is an asymmetric crossproduct effect in volatility and propose a realized asymmetric GARCH (henceforth RealAGARCH) model. The RealAGARCH model is a generalization to the absolute GARCH and the asymmetric GARCH. Moreover, the RealAGARCH model has a news impact surface instead of a news impact curve, which makes it different from other GARCH-like models. Empirical performance of the RealAGARCH model is evaluated on a variety of stock indices, and the results show dominance of RealAGARCH over the benchmark RealGARCH judging by either in-sample or out-of-sample forecasting performance. A battery of checks confirm the robustness of our findings and thus the importance of incorporating crossproduct effect into volatility forecasting.
Keyword:
crossproduct effect
news impact curve
news impact surface
RealAGARCH
volatility forecasting
期刊
IF:
2.7
论文数:
2.3K
被引数:
3.0K
机构
引用论文
A conditional autoregressive range model with gamma distribution for financial volatility modelling
ECONOMIC MODELLING
IF4.7

