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Modeling Stock Volatility with Trading Information

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Author Info
Huirong Li (The University of Western Ontario Department of Economics)
Jian Yang (The 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

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Publisher Info
Paper provided by University of Western Ontario, Department of Economics in its series UWO Department of Economics Working Papers with number 9904.

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Date of creation: Jan 1999
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Handle: RePEc:uwo:uwowop:9904

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions

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