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Supremacy of realized variance MIDAS egression in volatility forecasting of mutual funds: empirical evidence from Malaysia

Combining the strength of both Mixed Data Sampling (MIDAS) Regression and realized variance measures, this paper seeks to investigate two objectives: (1) evaluate the post-sample performance of the proposed weekly Realized Variance-MIDAS (RVar-MIDAS) in one-week ahead volatility forecasting against...

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Main Authors: Wan, Cheong Kin, Choo, Wei Chong, Ho, Jen Sim
Format: Article
Published: Korea Institute of Science and Technology Information 2022
Online Access:http://psasir.upm.edu.my/id/eprint/103363/
https://koreascience.kr/article/JAKO202220659765413.page
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spelling my.upm.eprints.1033632023-06-26T06:58:04Z http://psasir.upm.edu.my/id/eprint/103363/ Supremacy of realized variance MIDAS egression in volatility forecasting of mutual funds: empirical evidence from Malaysia Wan, Cheong Kin Choo, Wei Chong Ho, Jen Sim Combining the strength of both Mixed Data Sampling (MIDAS) Regression and realized variance measures, this paper seeks to investigate two objectives: (1) evaluate the post-sample performance of the proposed weekly Realized Variance-MIDAS (RVar-MIDAS) in one-week ahead volatility forecasting against the established Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and the less explored but robust STES (Smooth Transition Exponential Smoothing) methods. (2) comparing forecast error performance between realized variance and squared residuals measures as a proxy for actual volatility. Data of seven private equity mutual fund indices (generated from 57 individual funds) from two different time periods (with and without financial crisis) are applied to 21 models. Robustness of the post-sample volatility forecasting of all models is validated by the Model Confidence Set (MCS) Procedures and revealed: (1) The weekly RVar-MIDAS model emerged as the best model, outperformed the robust DAILY-STES methods, and the weekly DAILY-GARCH models, particularly during a volatile period. (2) models with realized variance measured in estimation and as a proxy for actual volatility outperformed those using squared residual. This study contributes an empirical approach to one-week ahead volatility forecasting of mutual funds return, which is less explored in past literature on financial volatility forecasting compared to stocks volatility. Korea Institute of Science and Technology Information 2022 Article PeerReviewed Wan, Cheong Kin and Choo, Wei Chong and Ho, Jen Sim (2022) Supremacy of realized variance MIDAS egression in volatility forecasting of mutual funds: empirical evidence from Malaysia. Journal of Asian Finance, Economics and Business, 9 (7). pp. 1-15. ISSN 2288-4637; ESSN: 2288-4645 https://koreascience.kr/article/JAKO202220659765413.page 10.13106/jafeb.2022.vol9.no7.0001
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Combining the strength of both Mixed Data Sampling (MIDAS) Regression and realized variance measures, this paper seeks to investigate two objectives: (1) evaluate the post-sample performance of the proposed weekly Realized Variance-MIDAS (RVar-MIDAS) in one-week ahead volatility forecasting against the established Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and the less explored but robust STES (Smooth Transition Exponential Smoothing) methods. (2) comparing forecast error performance between realized variance and squared residuals measures as a proxy for actual volatility. Data of seven private equity mutual fund indices (generated from 57 individual funds) from two different time periods (with and without financial crisis) are applied to 21 models. Robustness of the post-sample volatility forecasting of all models is validated by the Model Confidence Set (MCS) Procedures and revealed: (1) The weekly RVar-MIDAS model emerged as the best model, outperformed the robust DAILY-STES methods, and the weekly DAILY-GARCH models, particularly during a volatile period. (2) models with realized variance measured in estimation and as a proxy for actual volatility outperformed those using squared residual. This study contributes an empirical approach to one-week ahead volatility forecasting of mutual funds return, which is less explored in past literature on financial volatility forecasting compared to stocks volatility.
format Article
author Wan, Cheong Kin
Choo, Wei Chong
Ho, Jen Sim
spellingShingle Wan, Cheong Kin
Choo, Wei Chong
Ho, Jen Sim
Supremacy of realized variance MIDAS egression in volatility forecasting of mutual funds: empirical evidence from Malaysia
author_facet Wan, Cheong Kin
Choo, Wei Chong
Ho, Jen Sim
author_sort Wan, Cheong Kin
title Supremacy of realized variance MIDAS egression in volatility forecasting of mutual funds: empirical evidence from Malaysia
title_short Supremacy of realized variance MIDAS egression in volatility forecasting of mutual funds: empirical evidence from Malaysia
title_full Supremacy of realized variance MIDAS egression in volatility forecasting of mutual funds: empirical evidence from Malaysia
title_fullStr Supremacy of realized variance MIDAS egression in volatility forecasting of mutual funds: empirical evidence from Malaysia
title_full_unstemmed Supremacy of realized variance MIDAS egression in volatility forecasting of mutual funds: empirical evidence from Malaysia
title_sort supremacy of realized variance midas egression in volatility forecasting of mutual funds: empirical evidence from malaysia
publisher Korea Institute of Science and Technology Information
publishDate 2022
url http://psasir.upm.edu.my/id/eprint/103363/
https://koreascience.kr/article/JAKO202220659765413.page
_version_ 1770553011588825088
score 13.223943

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