Volatility forecasting using related markets’ information for the Tokyo stock exchange

Nirodha I. Jayawardena, Neda Todorova, Bin Li and Jen-Je Su

Economic Modelling, 2020, vol. 90, issue C, 143-158

Abstract: Due to lack of information, volatility cannot be estimated via a high-frequency approach when markets are non-trading. In this paper, we focus on volatility forecasting for the Tokyo Stock Exchange (TSE) using high-frequency data of related assets traded in international markets when TSE is closed. We use the heterogenous autoregressive model to identify an optimal approach of this additional information for the ten largest TSE-listed stocks, TOPIX and Nikkei 225. The usefulness of harnessing global and neighbour market information in forecasting the TSE market volatility is confirmed through in-depth empirical analysis. Our findings have important implications for investors and policy makers.

Keywords: Tokyo stock exchange; Realised volatility; Overnight volatility; Lunch break; Forecasting; Economic significance (search for similar items in EconPapers)
JEL-codes: C52 C53 C58 G17 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:90:y:2020:i:c:p:143-158

DOI: 10.1016/j.econmod.2020.05.008

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