Quantitative Finance · 2002 · 126 citations · 10 references
BusinessEconomicsFinanceFinancial EconomicsFinancial MarketsTime Series AnalysisTime Series ForecastingVolatility ModelingAutocorrelation FunctionAutocorrelation Function AnalysisAutocorrelation Function DecayCorrelation DynamicsLimit Order MarketsLimit Order TradingRelative PricesTemporal Structure Analysis
In this paper we demonstrate a striking regularity in the way people place limit orders in financial markets, using a data set consisting of roughly two million orders from the London Stock Exchange. We define the relative limit price as the difference between the limit price and the best price available. Merging the data from 50 stocks, we demonstrate that for both buy and sell orders, the unconditional cumulative distribution of relative limit prices decays roughly as a power law with exponent approximately -1.5. This behaviour spans more than two decades, ranging from a few ticks to about 2000 ticks. Time series of relative limit prices show interesting temporal structure, characterized by an autocorrelation function that asymptotically decays as C(τ)∼τ-0.4. Furthermore, relative limit price levels are positively correlated with and are led by price volatility. This feedback may potentially contribute to clustered volatility.
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Generalized autoregressive conditional heteroskedasticity
Tim Bollerslev · Journal of Econometrics · 1986 · 22.3K citations · Full text
Business, Finance, Econometrics +11
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James Theiler, Stephen Eubank, André Longtin et al. · Physica D Nonlinear Phenomena · 1992 · 3.8K citations