TY - JOUR
T1 - Forecasting stock return volatility
T2 - Realized volatility-type or duration-based estimators
AU - Fei, Tianlun
AU - Liu, Xiaoquan
AU - Wen, Conghua
N1 - Publisher Copyright:
© 2023 John Wiley & Sons Ltd.
PY - 2023/11
Y1 - 2023/11
N2 - In this paper, we study the predictive performance of two kinds of volatility estimators: the realized volatility (RV) type and duration-based ones. This is motivated by the theoretical and empirical support for these distinct estimators. We use intraday data for 218 component stocks of the CSI 300 index in the Chinese equity market from 2010–2019 and perform in- and out-of-sample 1-, 5-, and 22-day ahead volatility forecasts from combinations of volatility models and these estimators. We show that, although empirically more efficient with the US data, the duration-based estimators fail to compete statistically, or in terms of economic value, with RV-type ones in the Chinese market. We perform a comprehensive set of simulations to rationalize these results and show that duration-based estimators underperform as they cannot handle the occasional heightened level of volatility in the Chinese market.
AB - In this paper, we study the predictive performance of two kinds of volatility estimators: the realized volatility (RV) type and duration-based ones. This is motivated by the theoretical and empirical support for these distinct estimators. We use intraday data for 218 component stocks of the CSI 300 index in the Chinese equity market from 2010–2019 and perform in- and out-of-sample 1-, 5-, and 22-day ahead volatility forecasts from combinations of volatility models and these estimators. We show that, although empirically more efficient with the US data, the duration-based estimators fail to compete statistically, or in terms of economic value, with RV-type ones in the Chinese market. We perform a comprehensive set of simulations to rationalize these results and show that duration-based estimators underperform as they cannot handle the occasional heightened level of volatility in the Chinese market.
KW - Chinese stock market
KW - duration-based estimator
KW - intraday data
KW - market microstructure noise
KW - simulation exercises
UR - http://www.scopus.com/inward/record.url?scp=85150352717&partnerID=8YFLogxK
U2 - 10.1002/for.2974
DO - 10.1002/for.2974
M3 - Article
AN - SCOPUS:85150352717
SN - 0277-6693
VL - 42
SP - 1594
EP - 1621
JO - Journal of Forecasting
JF - Journal of Forecasting
IS - 7
ER -