Abstract

Using stocks from a wide range of industry sectors on the Australian Securities Exchange, this paper examines the conditional distribution of intra-day stock prices and predicts the direction of the next price change in an ordered-probit-GARCH framework that accounts for the discreteness of prices. The analysis also incorporates the endogeneity of the time between trades in an ACD framework. Other elements considered include depth, trade imbalance, and volume. The results show that trade imbalance has a positive effect on the probability of price change. Durations have a negative effect. In-sample and out-of-sample forecasting analyses reveal that in 71% of the cases the system successfully predicts the direction of the subsequent price change.

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