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Forecasting realized volatility based on the truncated two-scales realized volatility estimator (TTSRV): Evidence from China's stock market

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  • Ping, Yuan
  • Li, Rui

Abstract

In this paper, the TTSRV (truncated two-scale realized volatility estimator), a novel estimator of the continuous part of realized volatility (RV), is used to forecast the RV of the SSEC index. Based on the classic heterogeneous autoregressive model for RV (HAR-RV), our new model, which applies the TTSRV, can describe the continuous and jump processes of RV with higher accuracy. The empirical results obtained by this study suggest that the TTSRV outperforms previous models in both statistical and economic aspects.

Suggested Citation

  • Ping, Yuan & Li, Rui, 2018. "Forecasting realized volatility based on the truncated two-scales realized volatility estimator (TTSRV): Evidence from China's stock market," Finance Research Letters, Elsevier, vol. 25(C), pages 222-229.
    • Handle: RePEc:eee:finlet:v:25:y:2018:i:c:p:222-229
    DOI: 10.1016/j.frl.2017.10.028
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    Cited by:

    1. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2022. "A moving average heterogeneous autoregressive model for forecasting the realized volatility of the US stock market: Evidence from over a century of data," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 384-400, January.
    2. Su, Zhifang & Bao, Haohua & Li, Qifang & Xu, Boyu & Cui, Xin, 2022. "The prediction of price gap anomaly in Chinese stock market: Evidence from the dependent functional logit model," Finance Research Letters, Elsevier, vol. 47(PB).
    3. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.

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    More about this item

    Keywords

    Realized volatility; Truncated two-scale; Forecast;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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