GAS-SKST-F模型及其在高频多元波动率预测中的应用

doi:10.16381/j.cnki.issn1003-207x.2019.1105

Abstract

Abstract: Modeling conditional dependency structure of financial assets through time-varying covariance is of great significance to capital risk management, option pricing and optimal portfolio. With the advent of high-frequency data, realized multivariate volatility model is widely applied in the financial field in recent years. Among the observation-driven models for time-varying parameters, the clear advantage of the generalized autoregressive score (GAS) model is that it exploits the complete density structure and likelihood information rather than theconditional moments information.

Key words: GAS-SKST-F model, multivariate skewed student t density, multivariate volatility

CLC Number:

F830.9

LU Wan-bo, KANG Jing-hao. GAS-SKST-F Model and Its Application in High Frequency Multivariate Volatility Forecast[J]. Chinese Journal of Management Science, 2022, 30(1): 77-87.

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GAS-SKST-F Model and Its Application in High Frequency Multivariate Volatility Forecast

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