Working Paper

The Contribution of Jump Signs and Activity to Forecasting Stock Price Volatility


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.

Keywords: Realized Volatility; Signed Jumps; Finite Jumps; Infinite Jumps; Volatility Forecasts; Noise-Robust Volatility; Model Averaging;

JEL Classification: C22; C51; C53; C58;

https://doi.org/10.24149/wp1902

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Bibliographic Information

Provider: Federal Reserve Bank of Dallas

Part of Series: Working Papers

Publication Date: 2019-03-28

Number: 1902

Pages: 48 pages