D84 - Expectations; SpeculationsReturn

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 closer description of real markets. The main result of the simulations is that the probability distribution functions of the price deviations change significantly when smart traders are added to the model, and they also change significantly when changes in sentiment are introduced. We also use the Hurst exponent to measure the persistence of the price deviations and we find that the Hurst exponent is significantly increasing with the number of smart traders in the simulations. This means that the introduction of the smart traders concept into the model results in significantly higher persistence of the simulated price deviations. On the other hand, the introduction of changing sentiment in the proposed form does not change the persistence of the simulated prices significantly.

The paper deals with the hypothesis of housing price bubble in the Czech economy. This topic is very popular among economists worldwide now, especially because of the U.S. housing crisis and subsequent collapses on financial markets. However, surprisingly there are not many analyses dealing with the Czech housing market (besides e.g. very brief Financial Stability Report published by the Czech National Bank in 2008) and with the possible housing bubble burst. The first standard bubble indicators like P/I ratio are used to identify the bubble possibility on the Czech housing market. As the second step a regression analysis (VAR model) is being used for deeper analysis of the situation. The whole analysis is complicated by a lack of relevant data and quite short-time series.

The efficient market hypothesis (EMH) fails as a valid model of financial markets. The fractal market hypothesis (FMH) is a more general alternative way to the EMH. The FMH is formed on the following parameter space: agents' investment horizons. A financial market is more stable when a fractal character in the structures of agent's investment horizons is adopted. For computer simulations, the classical model is modified. This adjusted model shows that various frequency distributions on agents' investment horizons lead to different returns behaviour. The FMH focuses on matching of demand and supply of agents' investment horizons in the financial market. The FMH asserts that investors have different information based on temporal attributes. Since all investors in the market have different time investment horizons, the market remains stable. Our simulations of probability distributions of agents' investment horizons demonstrate that many investment horizons guarantee stability on the financial market.

The efficient markets hypothesis provides a theoretical basis on which technical trading rules (TTRs) are rejected as a viable trading strategy. TTRs, providing a signal to the user when to buy or sell asset based on such price patterns, should not be useful for generating excess returns. Technical traders tend to put little faith in strict efficient markets hypothesis. This approach relies on heterogeneity in the agent information and subsequent decisions either as fundamentalists or as technical traders. Switching between the technical trader's and fundamentalist's strategy is a basis of the cycle behaviour. This event is analysed by the Brock and Hommes (BH) model. Moreover, the memory case is added to this model because BH model was the memory-less model. This branch consists of a behaviour analysis among fundamentalists and technical traders. Here is a basis for endogenous source of the real business cycle.