HAR Model to Examine the Impact of Daily, Weekly, and Monthly Effect

2021 International Conference on Computer, Blockchain and Financial Development (CBFD) Pub Date : 2021-04-01 DOI:10.1109/CBFD52659.2021.00065

Zhaoying Wang, Xinyi Liu

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Abstract

Gold has always been crucial in economy in both ancient and modern societies and people are interested in investing in it all the times, whether in traditional physical gold or modern gold futures. In this paper, we want to use more advanced and scientific modern means to make prediction on the future volatility of gold futures to help investors make decisions and reduce risks. Based on heterogeneous autoregressive (HAR) theory, we establish three heterogeneous autoregressive realized volatility (HAR-RV) models to predict the future volatility of gold futures at three different horizons (daily, weekly, and monthly) utilizing 5-minute-frequency trading data in Chinese gold futures market from 01, 2008 to 02, 2021. The empirical result shows that our HAR-RV models is better at forecasting the future weekly volatility than future daily and monthly volatility, in terms of both statistical significance and level of goodness of fit. Also, the forecasted future volatility in daily, weekly and monthly HAR-RV models has a stronger relation with weekly, weekly and monthly realized volatility separately.

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HAR模型检验日、周、月效应的影响

黄金在古代和现代社会的经济中一直都是至关重要的，人们一直对投资黄金感兴趣，无论是传统的实物黄金还是现代黄金期货。本文希望利用更先进、更科学的现代手段对黄金期货未来的波动率进行预测，帮助投资者进行决策，降低风险。基于异构自回归(HAR)理论，利用2008年1月至2021年2月中国黄金期货市场的5分钟频率交易数据，建立了3个异构自回归已实现波动率(HAR- rv)模型，对日、周、月三个不同视域的黄金期货未来波动率进行了预测。实证结果表明，我们的HAR-RV模型在预测未来周波动率方面优于预测未来日和月波动率，无论是在统计显著性方面还是在拟合优度方面。日、周、月HAR-RV模型预测的未来波动率分别与周、周、月实际波动率有较强的相关性。

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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2021 International Conference on Computer, Blockchain and Financial Development (CBFD)

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