Realized volatility forecast of financial futures using time-varying HAR latent factor models

IF 5.4 2区 管理学 Q1 BUSINESS, FINANCE
Jiawen Luo , Zhenbiao Chen , Shengquan Wang
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引用次数: 3

Abstract

We forecast realized volatilities by developing a time-varying heterogeneous autoregressive (HAR) latent factor model with dynamic model average (DMA) and dynamic model selection (DMS) approaches. The number of latent factors is determined using Chan and Grant's (2016) deviation information criteria. The predictors in our model include lagged daily, weekly, and monthly volatility variables, the corresponding volatility factors, and a speculation variable. In addition, the time-varying properties of the best-performing DMA(DMS)-HAR-2FX models, including size, inclusion probabilities, and coefficients, are examined. We find that the proposed DMA(DMS)-HAR-2FX model outperforms the competing models for both in-sample and out-of-sample forecasts. Furthermore, the speculation variable displays strong predictability for forecasting the realized volatility of financial futures in China.

利用时变HAR潜因子模型实现金融期货波动性预测
本文采用动态模型平均(DMA)和动态模型选择(DMS)方法建立了一个时变异构自回归(HAR)潜在因素模型来预测已实现的波动率。潜在因素的数量是使用Chan和Grant(2016)的偏差信息标准确定的。我们模型中的预测因子包括滞后的每日、每周和每月波动变量、相应的波动因子和投机变量。此外,还研究了性能最佳的DMA(DMS)-HAR-2FX模型的时变特性,包括大小、包含概率和系数。我们发现所提出的DMA(DMS)-HAR-2FX模型在样本内和样本外预测方面都优于竞争模型。投机变量对预测中国金融期货的已实现波动率具有较强的可预测性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Management Science and Engineering
Journal of Management Science and Engineering Engineering-Engineering (miscellaneous)
CiteScore
9.30
自引率
3.00%
发文量
37
审稿时长
108 days
期刊介绍: The Journal of Engineering and Applied Science (JEAS) is the official journal of the Faculty of Engineering, Cairo University (CUFE), Egypt, established in 1816. The Journal of Engineering and Applied Science publishes fundamental and applied research articles and reviews spanning different areas of engineering disciplines, applications, and interdisciplinary topics.
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