Currency and Index Futures Markets Dynamics: Asymmetric Volatility, Leverage Effects and Long-memory Characteristics

Abstract

This research examines the performance of return and volatility models on the long-memory, asymmetric volatility, and leverage effects by comparing the two most active futures markets globally, Currency and Index Futures. The study uses daily data from the database Quandl.com website, from January 2000 to March 2018. This study utilizes two short-memory models, the autoregressive moving average – exponential generalized autoregressive conditional heteroskedasticity (ARMA-EGARCH); and  autoregressive moving average – asymmetric power autoregressive conditional heteroskedasticity (ARMA-APARCH); and two long-memory models, autoregressive fractionally-integrated moving average – fractionally-integrated exponential generalized autoregressive conditional heteroskedasticity (ARFIMA-FIEGARCH); and autoregressive fractionally-integrated moving average – fractionally-integrated asymmetric power autoregressive conditional heteroskedasticity (ARFIMA-FIAPARCH). The paper shows that portfolio managers and traders can benefit in holding Index futures, because of their steady returns, but with a relatively higher risk for the whole sample period. The study also finds that Currency futures has better safe-haven properties during crisis period, but Index futures performs better after crisis period. Findings suggest that both long-memory models are capable of accurate forecast, especially on the volatility of Currency and Index futures. The proper modelling of Currency and Index futures time-series data can provide traders, fund managers and investors in creating well-defined trading strategies, especially in high volatility regimes.