Modeling Stock Volatility with Trading Information

Huirong Li and Jian Yang
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Huirong Li: The University of Western Ontario Department of Economics, https://economics.uwo.ca/
Jian Yang: The University of Western Ontario Department of Economics, https://economics.uwo.ca/
Authors registered in the RePEc Author Service: Ronald J. Wonnacott

No 9909, University of Western Ontario, Departmental Research Report Series from University of Western Ontario, Department of Economics

Abstract: This paper studies volatility in individual stocks of the Toronto Stock Exchange (TSE), using a recently developed nonlinear approach, a stochastic threshold model. Trading information is embedded into the determination process for volatility in the stochastic threshold model with a generalized conditional heteroskeasticitic variance (STGARCH). We use the number of price changes (quote changes) to approximate the trading information. This trading variable has significantly positive impact on stock volatility following a declining market and ambiguous impact on the stock volatility following a rising market; there is higher probability to fall into a highly volatile state after a declining market than after a rising market. The GARCH- type persistence in volatility is reduced significantly in our nonlinear model for individual stocks with high persistence. The STGARCH model also gives satisfactory fitting in terms of alternative model selection criteria. Keywords: Volatility; Asymmetry; Trading variable; Information arrivals; Stochastic threshold

JEL-codes: C12 C22 (search for similar items in EconPapers)
Date: 1999
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