Many agent-based models of financial markets have been able to reproduce certain stylized facts that are observed in actual empirical time series data by using “zero-intelligence” agents whose behaviour is largely random in order to ascertain whether certain phenomena arise from market microstructure as opposed to strategic behaviour. Although these models have been highly successful, it is not...

The Gates Hillman prediction market (GHPM) was an internet prediction market designed to predict the opening day of the Gates and Hillman Centers, the new computer science complex at Carnegie Mellon University. Unlike a traditional continuous double auction format, the GHPM was mediated by an automated market maker, a central agent responsible for pricing transactions with traders over the poss...

Recent initiatives to accelerate the insertion of materials and link the materials design and systems design processes have called for the advancement of microstructure-property relationships. In order to achieve these goals, the development of digital microstructure models in conjunction with computational methods for simulating material response is a necessity. There have been significant adv...

One of the essential features of the agent-based financial models is to show how price dynamics is affected by the evolving microstructure. Empirical work on this microstructure dynamics is, however, built upon highly simplified and unrealistic behavioral models of financial agents. Using genetic programming as a rule-inference engine and self-organizing maps as a clustering machine, we are abl...

Recorded prices are known to diverge from their “efficient” values due to the presence of market microstructure contaminations. The microstructure noise creates a dichotomy in the model-free estimation of integrated volatility. While it is theoretically necessary to sum squared returns that are computed over very small intervals to better indentify the underlying volatility over a period, the s...

The aim of this study is to develop a bias-correction method for realized variance (RV) estimation, where the equilibrium price process is contaminated with market microstructure noise, such as bid-ask bounces and price changes discreteness. Though RV constitutes the simplest estimator of daily integrated variance, it remains strongly biased and many estimators proposed in previous studies requ...

Abstract. Inspired by the theoretically oriented dynamic analysis of moving average rules in Chiarella, He and Hommes (CHH) (2006a) model, this paper conducts a dynamic analysis of a microstructure model of continuous double auctions in which the probability of heterogeneous agents to trade is determined by the rules of either fundamentalists mean-reverting to the fundamental or chartists who u...

In many studies of market microstructure, theoretical analysis quickly becomes intractable for all but the simplest stylized models. This thesis considers two alternative approaches, namely, the use of experiments with human subjects and simulations with intelligent agents, to address some of the limitations of theoretical modeling. The thesis aims to study the design, development and character...

This paper presents a comprehensive empirical evaluation of option-implied and returnsbased forecasts of volatility, in which new developments related to the impact on measured volatility of market microstructure noise and random jumps are explicitly taken into account. The option-based component of the analysis also accommodates the concept of model-free implied volatility, such that the forec...