Do oil-price shocks predict the realized variance of U.S. REITs?

We examine, using aggregate and sectoral U.S. data for the period 2008–2020, predictive power of disentangled oil-price shocks Real Estate Investment Trusts (REITs) realized market variance via heterogeneous auto-regressive (HAR-RV) model. In-sample tests show that demand financial-market-risk contribute to a larger extent overall fit model than supply shocks, where in-sample transmission impact mainly operates through their significant effects on upward (“good”) variance. Out-of-sample corroborate value its counterpart at short, medium, long forecast horizon, various recursive-estimation windows, volatility (that is, square root variance), shorter sub-sample excludes recent phase exceptionally intense oil-market turbulence, an extended benchmark features higher-order moments, jumps, leverage effect as control variables. also study quantiles-based extension HAR-RV model, we analyze economic benefits realized-variance forecasting.