TY - JOUR
T1 - ‘Risk-return trade-off in the Australian Securities Exchange
T2 - Accounting for overnight effects, realized higher moments, long-run relations, and fractional cointegration
AU - Jayawardena, Nirodha I.
AU - Todorova, Neda
AU - Li, Bin
AU - Su, Jen Je
AU - Gau, Yin Feng
N1 - Publisher Copyright:
© 2022 Elsevier Inc.
PY - 2022/7
Y1 - 2022/7
N2 - This paper examines the risk-return trade-off in the Australian Securities Exchange (ASX) using high-frequency data of related assets traded in other markets, where intra-day data are available while the ASX is closed. We consider the S&P/ASX 200 index and the ASX risk-neutral option-implied volatility (VIX) to highlight the importance of overnight information in predicting future index returns. Further, aside from the well-specified traditional approach of monitoring risk-return regressions using the second moment (volatility), we conjointly account for other higher-order moments such as the third and the fourth moments (skewness and kurtosis) to investigate the impact of overnight information corrected moments on predicting the future returns using the cointegrated fractional VAR (CFVAR) model. We find that the monthly compounded realized volatility and realized skewness adjusted with the fractional integration parameter are significantly negatively and positively related with the subsequent monthly returns, respectively. Moreover, the multivariate setting of our study implies that there exists a cointegrating relationship between the realized volatility and VIX, which can be regarded as the variance risk premium.
AB - This paper examines the risk-return trade-off in the Australian Securities Exchange (ASX) using high-frequency data of related assets traded in other markets, where intra-day data are available while the ASX is closed. We consider the S&P/ASX 200 index and the ASX risk-neutral option-implied volatility (VIX) to highlight the importance of overnight information in predicting future index returns. Further, aside from the well-specified traditional approach of monitoring risk-return regressions using the second moment (volatility), we conjointly account for other higher-order moments such as the third and the fourth moments (skewness and kurtosis) to investigate the impact of overnight information corrected moments on predicting the future returns using the cointegrated fractional VAR (CFVAR) model. We find that the monthly compounded realized volatility and realized skewness adjusted with the fractional integration parameter are significantly negatively and positively related with the subsequent monthly returns, respectively. Moreover, the multivariate setting of our study implies that there exists a cointegrating relationship between the realized volatility and VIX, which can be regarded as the variance risk premium.
KW - Australian Securities Exchange (ASX)
KW - CFVAR model
KW - Forecasting
KW - High frequency
KW - Overnight volatility
UR - http://www.scopus.com/inward/record.url?scp=85125704474&partnerID=8YFLogxK
U2 - 10.1016/j.iref.2022.02.057
DO - 10.1016/j.iref.2022.02.057
M3 - 期刊論文
AN - SCOPUS:85125704474
SN - 1059-0560
VL - 80
SP - 384
EP - 401
JO - International Review of Economics and Finance
JF - International Review of Economics and Finance
ER -