Jozef Baruník

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In this paper we extend the original heterogeneous agent model by introducing smart traders and changes in agents’ sentiment. The idea of smart traders is based on the endeavor of market agents to estimate future price movements. By adding smart traders and changes in sentiment we try to improve the original heterogeneous agents model so that it provides a(More)
The main aim of this work is to incorporate selected findings from behavioural finance into a Heterogeneous Agent Model using the Brock and Hommes (1998) [34] framework. Behavioural patterns are injected into an asset pricing framework through the so-called ‘Break Point Date’, which allows us to examine their direct impact. In particular, we analyse the(More)
In this paper we propose a new approach to estimation of the tail exponent in financial stock markets. We begin the study with the finite sample behavior of the Hill estimator under α−stable distributions. Using large Monte Carlo simulations we show that the Hill estimator overestimates the true tail exponent and can hardly be used on samples with small(More)
Traditional prediction methods for time series often restrict on linear regression analysis, exponential smoothing, and ARMA. These methods generally produce reasonable prediction results for stationary random time series of linear systems. In the recent decades, development in econometrics resulted also in methods which are capable of forecasting more(More)