TY - JOUR
T1 - Forecasting Realized Volatility of Agricultural Commodity Futures with Infinite Hidden Markov HAR Models
AU - Luo, Jiawen
AU - Klein, Tony
AU - Ji, Qiang
AU - Hou, Chenghan
PY - 2019/11/29
Y1 - 2019/11/29
N2 - We construct a set of HAR models with three types of infinite Hidden Markov regime
switching structures. Particularly, jumps, leverage effects, and speculation effects are
taken into account in realized volatility modeling. We forecast five agricultural commodity
futures (Corn, Cotton, Indica Rice, Palm oil and Soybean) based on high frequency data
from Chinese futures markets and evaluate the forecast performances with both statistical
and economic evaluation measures. The statistical evaluation results suggest that HAR
models with infinite Hidden Markov regime switching structures have better precision
compared the benchmark HAR models based on the MZ-R2
, MAFE, and MCS results.
The economic evaluation results suggest that portfolios constructed with infinite Hidden
Markov regime switching HARs achieve higher portfolio returns for risk averse investors
compared to benchmark HAR model for short-term volatility forecasts.
AB - We construct a set of HAR models with three types of infinite Hidden Markov regime
switching structures. Particularly, jumps, leverage effects, and speculation effects are
taken into account in realized volatility modeling. We forecast five agricultural commodity
futures (Corn, Cotton, Indica Rice, Palm oil and Soybean) based on high frequency data
from Chinese futures markets and evaluate the forecast performances with both statistical
and economic evaluation measures. The statistical evaluation results suggest that HAR
models with infinite Hidden Markov regime switching structures have better precision
compared the benchmark HAR models based on the MZ-R2
, MAFE, and MCS results.
The economic evaluation results suggest that portfolios constructed with infinite Hidden
Markov regime switching HARs achieve higher portfolio returns for risk averse investors
compared to benchmark HAR model for short-term volatility forecasts.
U2 - 10.1016/j.ijforecast.2019.08.007
DO - 10.1016/j.ijforecast.2019.08.007
M3 - Article
SN - 0169-2070
JO - International Journal of Forecasting
JF - International Journal of Forecasting
ER -