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We examine the forecasting power of a daily newspaper‐based index of uncertainty associated with infectious diseases (EMVID) for real estate investment trusts (REITs) realized market variance of the United States (US) via the heterogeneous autoregressive realized volatility (HAR‐RV) model. Our results show that the EMVID index improves the forecast accuracy of realized variance of REITs at short‐,...
Utilizing a machine learning technique known as random forests, we study whether regional output growth uncertainty helps to improve the accuracy of forecasts of regional output growth for 12 regions of the UK using monthly data for the period from 1970 to 2020. We use a stochastic volatility model to measure regional output growth uncertainty. We document the importance of interregional stochastic...
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