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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)
In this paper, we show how the sampling properties of Hurst exponent methods of estimation change with the presence of heavy tails. We run extensive Monte Carlo simulations to find out how rescaled range analysis (R/S), multifractal detrended fluctuation analysis (M F − DF A), detrending moving average (DM A) and generalized Hurst exponent approach (GHE)(More)
• We aim to incorporate findings from behavioural finance into a HAM. • Herding, overconfidence, and market sentiment are studied in numerical analysis. • Interesting price pattern of 30 DJIA constituents is revealed. • Simulations replicate price behaviour found in the data during turbulent periods. a b s t r a c t The main aim of this work is to(More)
We detect and quantify asymmetries in the volatility spillovers of petroleum commodities: crude oil, gasoline, and heating oil. The increase in volatility spillovers after 2001 correlates with the progressive financialization of the commodities. Further, increasing spillovers from volatility among petroleum commodities substantially change their pattern(More)
a r t i c l e i n f o Keywords: Fractional cointegration Long memory Range Volatility Daily high and low prices This work provides empirical support for the fractional cointegration relationship between daily high and low stock prices, allowing for the non-stationary volatility of stock market returns. The recently formalized fractionally cointegrated(More)
Extended Abstract 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(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)
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