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Federal Reserve Bank of Dallas
Working Papers
The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility
Rodrigo Hizmeri
Marwan Izzeldin
Anthony Murphy
Mike G. Tsionas
Abstract

We document the forecasting gains achieved by incorporating measures of signed, finite and infinite jumps in forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that vary by sector, volume and degree of jump activity. We use extended HAR-RV models, and consider different frequencies (5, 60 and 300 seconds), forecast horizons (1, 5, 22 and 66 days) and the use of standard and robust-to-noise volatility and threshold bipower variation measures. Incorporating signed finite and infinite jumps generates significantly better real-time forecasts than the HAR-RV model, although no single extended model dominates. In general, standard volatility measures at the 300-second frequency generate the smallest real-time mean squared forecast errors. Finally, the forecasts from simple model averages generally outperform forecasts from the single best model.


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Rodrigo Hizmeri & Marwan Izzeldin & Anthony Murphy & Mike G. Tsionas, The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility, Federal Reserve Bank of Dallas, Working Papers 1902, 28 Mar 2019.
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Keywords: Realized Volatility; Signed Jumps; Finite Jumps; Infinite Jumps; Volatility Forecasts; Noise-Robust Volatility; Model Averaging
DOI: 10.24149/wp1902
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