Role behaviorálních faktorů na finančních trzích

Abstract

The existence of market anomalies is a subject to reflection on the validity of classical financial theory assumptions. The need to find out the causes of these anomalies defines the theoretical aspect of this bachelor thesis, which deals with the role of behavioral factors in financial markets. The objective is to identify the relevance and significance of behavioral factors, expressed through sentiment indices, as indicators of market course. The content of the thesis draws on the theoretical basis of behavioral finance discipline and responds to the imperfections of the effective market hypothesis and the theory of rational expectations. The primary aim is to emphasize the influence of behavioral factors on the individual decision-making process and to discuss the aspects that shape the behavior of market participants and mediately imply the form of the prevailing market trend.

The practical part of the thesis aims at verifying the hypotheses discussed in the theoretical part, namely by observing the direction of the market and the parallel course of behavioral factors (sentiment indices). For example, there is observed direction of the course of sentiment indices linked to development of historical market bubbles and subsequent market crashes, stock price volatility, market liquidity or gold prices. Within the thesis, there are studied all currently used categories of sentiment indices, namely indices based on market indicators, on text sources analysis and on surveys. On the basis of the observations, there are defined causal relationships that are subsequently examined in more detail through regression analysis, where the sentiment indices represent a role of explanatory variables which describe the development of dependent variables in the form of stock indices (NASDAQ Composite Index, S&P 500 and the like). The regression analysis results show that sentiment indices are able to reliably reflect the stock indices course direction (and thus overall market trend).

In the final part of the thesis, there are drawn up in-sample static predictions with the aim to explore a potential prediction power of the sentiment indices. The predictions are based on two types of models – models including sentiment indices as explanatory variables and models based on simple autoregression (AR) or moving average (MA) processes. The prediction results demonstrate the ability of sentiment indices to improve the market trend description (as compared to the simple AR/MA process) as well as their potential to signal future market trend. Based on empirical observations, it is thus possible to state that behavioral factors are important indicators of market course and could be used as a supporting tool for market analysis.