Waiting Times in Simulated Stock Markets

Exploiting a precise reproduction of a stock exchange, the robustness of the Continuous Double Auction (CDA) mechanism, evaluated by means of the waiting time distributions, has been proved versus 36 different set ups made by varying both the operators' behaviour and the market micro structure. The obtained results demonstrate that the CDA remains able to clear strongly different order flows, though the Milan stock exchange seemed to be a little more efficient than the NYSE under the allocative point of view, witnessing the intrinsic complexity of the stock market. The simulation has been built as an Agent Based Model in order to obtain a plausible order flow. The decisions of single agents and their interaction through the market book are realistic and reproduce some empirical analysis results. The mentioned results have been obtained either by the analysis of the complete pending time series and the same computation of the asks and bids series alone.Waiting times; Agent Based Modeling; Stock Market; Micro structures; Market Architectures

Waiting Times in Simulated Stock Markets

Exploiting a precise reproduction of a stock exchange, the robustness of the Continuous Double Auction (CDA) mechanism, evaluated by means of the waiting time distributions, has been proved versus 36 different set ups made by varying both the operators' behaviour and the market micro structure. The obtained results demonstrate that the CDA remains able to clear strongly different order flows, though the Milan stock exchange seemed to be a little more efficient than the NYSE under the allocative point of view, witnessing the intrinsic complexity of the stock market. The simulation has been built as an Agent Based Model in order to obtain a plausible order flow. The decisions of single agents and their interaction through the market book are realistic and reproduce some empirical analysis results. The mentioned results have been obtained either by the analysis of the complete pending time series and the same computation of the asks and bids series alone.Comment: 11 pages, 4 figures. Presented at ECCS'07. Submitted at AC

Train schedule coordination at an interchange station through agent negotiation

In open railway markets, coordinating train schedules at an interchange station requires negotiation between two independent train operating companies to resolve their operational conflicts. This paper models the stakeholders as software agents and proposes an agent negotiation model to study their interaction. Three negotiation strategies have been devised to represent the possible objectives of the stakeholders, and they determine the behavior in proposing offers to the proponent. Empirical simulation results confirm that the use of the proposed negotiation strategies lead to outcomes that are consistent with the objectives of the stakeholders

"Market making" behaviour in an order book model and its impact on the bid-ask spread

It has been suggested that marked point processes might be good candidates for the modelling of financial high-frequency data. A special class of point processes, Hawkes processes, has been the subject of various investigations in the financial community. In this paper, we propose to enhance a basic zero-intelligence order book simulator with arrival times of limit and market orders following mutually (asymmetrically) exciting Hawkes processes. Modelling is based on empirical observations on time intervals between orders that we verify on several markets (equity, bond futures, index futures). We show that this simple feature enables a much more realistic treatment of the bid-ask spread of the simulated order book.Comment: 17 pages, 9 figure

Mixtures of compound Poisson processes as models of tick-by-tick financial data

A model for the phenomenological description of tick-by-tick share prices in a stock exchange is introduced. It is based on mixtures of compound Poisson processes. Preliminary results based on Monte Carlo simulation show that this model can reproduce various stylized facts.Comment: 12 pages, 6 figures, to appear in a special issue of Chaos, Solitons and Fractal

Financial correlations at ultra-high frequency: theoretical models and empirical estimation

A detailed analysis of correlation between stock returns at high frequency is compared with simple models of random walks. We focus in particular on the dependence of correlations on time scales - the so-called Epps effect. This provides a characterization of stochastic models of stock price returns which is appropriate at very high frequency.Comment: 22 pages, 8 figures, 1 table, version to appear in EPJ

Compensating asynchrony effects in the calculation of financial correlations

We present a method to compensate statistical errors in the calculation of correlations on asynchronous time series. The method is based on the assumption of an underlying time series. We set up a model and apply it to financial data to examine the decrease of calculated correlations towards smaller return intervals (Epps effect). We show that this statistical effect is a major cause of the Epps effect. Hence, we are able to quantify and to compensate it using only trading prices and trading times.Comment: 13 pages, 7 figure