This research aims to investigate, through simulation models, how the interaction among agents in an artificial stock market can affect the dynamics of asset prices. Thus, the study follows a different methodology for the analysis of prices by exploring the simulation of agents' behavior in an...

The paper empirically analyzes stock market integration and the benefit possibilities of international portfolio diversification across the Southeast Asia (ASEAN) and U.S. equity markets. It employs daily sample of 6 ASEAN equity market indices and S&P 500 index as a proxy of U.S. market index...

In this paper, we examine the changes in the dependence structure of global stock markets amid the outbreak of COVID-19. We divide 56 stock markets into developed, emerging, and frontier markets and study their daily price data from October 15, 2019 to August 17, 2020 using the canonical vine...

We propose a framework to study the optimal liquidation strategy in a limit order book for large-tick stocks, with the spread equal to one tick. All order book events (market orders, limit orders and cancellations) occur according to independent Poisson processes, with parameters depending on...

Optimal execution and trading algorithms rely on price impact models, like the propagator model, to quantify trading costs. Empirically, price impact is concave in trade sizes, leading to nonlinear models for which optimization problems are intractable and even qualitative properties such as...

Portfolio managers’ orders trade off return and trading cost predictions. Return predictions rely on alpha models, whereas price impact models quantify trading costs. This paper studies what happens when trades are based on an incorrect price impact model, so that the portfolio either over- or...

Based on criteria of mathematical simplicity and consistency with empirical market data, a stochastic volatility model is constructed, the volatility process being driven by fractional noise. Price return statistics and asymptotic behavior are derived from the model and compared with data....

An asymmetric multivariate generalization of the recently proposed class of normal mixture GARCH models is developed. Issues of parametrization and estimation are discussed. Conditions for covariance stationarity and the existence of the fourth moment are derived, and expressions for the dynamic...

We develop a multivariate generalization of the Markov-switching GARCH model introduced by Haas, Mittnik, and Paolella (2004b) and derive its fourth-moment structure. An application to international stock markets illustrates the relevance of accounting for volatility regimes from both a...

We model trades-through, i.e. transactions that reach at least the second level of limit orders in an order book. Using tick-by-tick data on Euronext-traded stocks, we show that a simple bivariate Hawkes process fits nicely our empirical observations of trades-through. We show that the...