Information Content of Continuous and Jump Decomposition of Variances

連續及躍動變異部份之訊息內涵

10.6545/JFS.201809_26(3).0004

曾祺峰(Chi-Feng Tzeng)；蔡子晧(Jeffrey Tzuhao Tsai)

Volatility prediction ； model free implied volatility ； realized variance ； conditional jump intensity ； 波動度預測 ； 無模型隱含波動度 ； 已實現變異值 ； 條件式躍動頻率

財務金融學刊

26卷3期（2018 / 09 / 30）

117 - 139

英文

The GARCH models and heterogeneous autoregressive (HAR) model are used to evaluate the information about the continuous/jump compositions of variances. The continuous/jump components of the implied variance are extracted from FTSE 100 data. We compare the performance of the GARCH models in terms of sample fit and out-of-sample performance measures. Our results suggest that both the realized variance and model-free implied volatility are important information resources in variance forecasting. Using the HAR model, we find that the realized measurements contain incremental information relative to implied variances. Implied volatilities are improved as the GB2 distribution fitting is applied.

本文利用GARCH模型與HAR模型檢定連續/躍動部份變異之訊息內涵。從FTSE 100資料中取出連續/躍動隱含變異值，並以樣本內配適及樣本外預測力比較GARCH模型。在模型中已實現變異值及無模型隱含波動度皆是重要訊息來源。運用HAR模型，本文發現已實現變異值相對於隱含變異具有增額訊息；透過GB2分配配適能改進隱含波動之訊息內涵。

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