A1187
Title: Shortages to forecast aggregate and sectoral U.S. stock market realized variance
Authors: Matteo Bonato - IPAG Business School & University of Johannesburg (Switzerland) [presenting]
Abstract: Recent global economic and political events have made clear that shortages are a key factor driving macroeconomic and financial market developments. Against this backdrop, the forecasting value of shortages for U.S. stock market realized variance (RV) is studied at the aggregate and sectoral level using data spanning the period 1885-2024 (market) and 1926-2023 (most sectors). To this end, linear and nonlinear statistical learning estimators are considered. When linear estimators (OLS and shrinkage estimators) are used, there is no evidence that aggregate and disaggregate shortage indexes have predictive value for subsequent market or sectoral RVs. In contrast, when random forests are used, a nonlinear nonparametric estimator, aggregate and disaggregate shortage indexes are detected to improve forecast accuracy of market and sectoral RVs after controlling for realized moments (realized leverage, realized skewness, realized kurtosis, realized tail risks). RV is then decomposed into a high, medium, and low-frequency component, and the shortage indexes are found to correlate mainly with the medium and low frequencies of RV.
