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Momentum in Stock Returns: Analysis for European Countries
Drmotová, Kristýna ; Kukačka, Jiří (advisor) ; Maršál, Aleš (referee)
This thesis investigates one of the most pervasive anomalies in the behaviour of stock returns, the momentum. We analyse whether there is momentum in European stock returns that would generate profitable investment strategies. First, we compute the average monthly returns on strategies built in accordance with the existing literature. Next, we compare returns on momentum strate- gies between markets with different levels of capitalization and development. Further, we test whether these returns can be explained as the compensation for risk exposures through the Capital Asset Pricing Model. We find that even though the underlying risk has perceptible predictive power for stock re- turns, there still remains a substantial part of abnormal returns unexplained by this model. Therefore, we extend it with additional explanatory variables that might have a predictive power for stock returns according to the Fama & French (1993) three-factor model and Fama & French (2015) five-factor model. We find that stocks that performed best over the short-term past tend to con- tinue to outperform other stocks and stocks that performed worst tend to have one of the lowest returns in subsequent months. We find that strategies based on buying past winners yield statistically significant positive abnormal returns. Furthermore,...
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Seasonal Effects on Stock Markets in Europe
Rosol, Jaroslav ; Kukačka, Jiří (advisor) ; Čornanič, Aleš (referee)
This thesis researches the problem of stock market efficiency and market anomalies. Specifically, we look on European stock markets and possible presence of four seasonal effects - January, Halloween, Turn-of-the-month and Monday effects. These seasonal anomalies imply that returns for specific period are unusually higher or lower than returns for the rest of the time, which presents a challenge for the Efficient Market Hypothesis. The empirical side of this problem is the possible opportunity for excessive profit from trading on stock markets that could be based on the seasonal anomalies. Firstly, we summarize previous research in the field and attempts of explanation of individual effects. Further, we present the tools needed for our analysis - Ordinary Least Squares regression with dummy variables and few extensions. Data used for the analysis consists of 32 European stock indices. The actual analysis is performed as a comparison of returns on stock for certain specified periods. The evidence on January and Monday effects is found not strong enough to confirm the presence of such anomalies. On the other side, there is enough significant evidence on the presence of Halloween and Turn-of-the-month effects. Moreover, we are unable to explain the Halloween effect as manifestation of January effect. Powered...
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Does trading strategy based on overreaction and stock-bond decoupling generate additional profits?
Bosák, Martin ; Čech, František (advisor) ; Baruník, Jozef (referee)
Studying whether new trading rules provide higher returns than the buy-and-hold strategy is relevant for both finance theory and the asset management field. In this thesis, we examine the profitability of the newly proposed trading strategy based on the concept of price overreaction on eight developed stock indices. In comparison to other studies, we extend a definition of price overreaction with an inclusion of a minimum volatility threshold. Based on the Ordinary Least Squares model, we find that a volatility condition significantly improves the predictability of return reversals after positive price overreaction. For comparison with the buy-and-hold, we use Hansen's Superior Predictive Ability test that corrects the data snooping bias. Despite better annualised returns during in-sample and out-of-sample periods, the results show that the proposed strategy is not superior to the buy-and-hold at any stock index due to heavy reliance on the predictions of the largest declines. Nevertheless, we confirm the effect of decoupling (flight to quality) that can positively affect our strategy, but only when we do not take into account transaction costs. In the end, we summarize behavioural concepts that lie behind our strategy as the overreaction and decoupling are mostly justified with cognitive biases.
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The Trump Sentiment: The Effect of News on the US Stock Market
Pinteková, Aneta ; Kukačka, Jiří (advisor) ; Horváth, Roman (referee)
This thesis examines how the American economy is affected by the market sentiment that arises from the news about actions and decisions of the American President Donald Trump. The news articles are obtained from Reuters for the period between the 1st of May and the 30th of November 2018, based on which a sentiment variable is created using natural language processing methods. Firstly, the impact of Trump sentiment on the returns on the S&P 500 Index is examined. The results show a positive and statistically significant impact of sentiment from the previous day on today's S&P 500 Index return. A statisti cally significant effect of the sentiment from a week ago is also found, however, this effect is negative. This result indicates that there is an initial overreaction to the new information, followed by subsequent market correction to the mean. Such result is consistent with the findings of the field of behavioural finance, which incorporates the idea that investor psychology is involved in investment decision making. Secondly, the impact of the news sentiment on the performance of individual sectors of the American economy, as measured by the returns on S&P 500 sector indices, is analysed. A statistically significant effect of sentiment on sector index return is found in the case of Consumer...
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Momentum in Stock Returns: Analysis for European Countries
Drmotová, Kristýna ; Kukačka, Jiří (advisor) ; Maršál, Aleš (referee)
This thesis investigates one of the most pervasive anomalies in the behaviour of stock returns, the momentum. We analyse whether there is momentum in European stock returns that would generate profitable investment strategies. First, we compute the average monthly returns on strategies built in accordance with the existing literature. Next, we compare returns on momentum strate- gies between markets with different levels of capitalization and development. Further, we test whether these returns can be explained as the compensation for risk exposures through the Capital Asset Pricing Model. We find that even though the underlying risk has perceptible predictive power for stock re- turns, there still remains a substantial part of abnormal returns unexplained by this model. Therefore, we extend it with additional explanatory variables that might have a predictive power for stock returns according to the Fama & French (1993) three-factor model and Fama & French (2015) five-factor model. We find that stocks that performed best over the short-term past tend to con- tinue to outperform other stocks and stocks that performed worst tend to have one of the lowest returns in subsequent months. We find that strategies based on buying past winners yield statistically significant positive abnormal returns. Furthermore,...
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Seasonal Effects on Stock Markets in Europe
Rosol, Jaroslav ; Kukačka, Jiří (advisor) ; Čornanič, Aleš (referee)
This thesis researches the problem of stock market efficiency and market anomalies. Specifically, we look on European stock markets and possible presence of four seasonal effects - January, Halloween, Turn-of-the-month and Monday effects. These seasonal anomalies imply that returns for specific period are unusually higher or lower than returns for the rest of the time, which presents a challenge for the Efficient Market Hypothesis. The empirical side of this problem is the possible opportunity for excessive profit from trading on stock markets that could be based on the seasonal anomalies. Firstly, we summarize previous research in the field and attempts of explanation of individual effects. Further, we present the tools needed for our analysis - Ordinary Least Squares regression with dummy variables and few extensions. Data used for the analysis consists of 32 European stock indices. The actual analysis is performed as a comparison of returns on stock for certain specified periods. The evidence on January and Monday effects is found not strong enough to confirm the presence of such anomalies. On the other side, there is enough significant evidence on the presence of Halloween and Turn-of-the-month effects. Moreover, we are unable to explain the Halloween effect as manifestation of January effect. Powered...
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Behavioural Breaks in the Heterogeneous Agent Model
Kukačka, Jiří ; Baruník, Jozef (advisor) ; Víšek, Jan Ámos (referee)
This thesis merges the fields of Heterogeneous Agent Models (HAMs) and Be- havioural Finance in order to bridge the main deficiencies of both approaches and to examine whether they can complement one another. Our approach suggests an alternative tool for examining HAM price dynamics and brings an original way of dealing with problematic empirical validation. First, we present the original model and discuss various extensions and attempts at empirical estimation. Next, we develop a unique benchmark dataset, covering five par- ticularly turbulent U.S. stock market periods, and reveal an interesting pattern in this data. The main body applies a numerical analysis of the HAM extended with the selected Behavioural Finance findings: herding, overconfidence, and market sentiment. Using Wolfram Mathematica we perform Monte Carlo simu- lations of a developed algorithm. We show that the selected findings can be well modelled via the HAM and that they extend the original HAM considera- bly. Various HAM modifications lead to significantly different results and HAM is also able to partially replicate price behaviour during turbulent stock market periods. Bibliographic Record Kukačka, J. (2012): Behavioural Breaks in the Heterogeneous Agent Model. Rigorous thesis, Charles University in Prague, Faculty of Social...
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Behavioural Breaks in the Heterogeneous Agent Model
Kukačka, Jiří ; Baruník, Jozef (advisor) ; Víšek, Jan Ámos (referee)
This thesis merges the fields of Heterogeneous Agent Models (HAMs) and Be- havioural Finance in order to bridge the main deficiencies of both approaches and to examine whether they can complement one another. Our approach suggests an alternative tool for examining HAM price dynamics and brings an original way of dealing with problematic empirical validation. First, we present the original model and discuss various extensions and attempts at empirical estimation. Next, we develop a unique benchmark dataset, covering five par- ticularly turbulent U.S. stock market periods, and reveal an interesting pattern in this data. The main body applies a numerical analysis of the HAM extended with the selected Behavioural Finance findings: herding, overconfidence, and market sentiment. Using Wolfram Mathematica we perform Monte Carlo sim- ulations of a developed algorithm. We show that the selected findings can be well modelled via the HAM and that they extend the original HAM consider- ably. Various HAM modifications lead to significantly different results and HAM is also able to partially replicate price behaviour during turbulent stock market periods. Bibliographic Record Kukačka, J. (2011): Behavioural Breaks in the Heterogeneous Agent Model. Master thesis, Charles University in Prague, Faculty of Social Sciences,...
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Behavioral finance and their application to capital markets
Šuvadová, Barbara ; Čajka, Radek (advisor) ; Taušer, Josef (referee)
Thesis addresses the topic of behavioral finance. The aim of the paper is to identify most common investors's mistakes and examine the impact, the psychological and sociological factors have on their behavior when trading equities. The first part of thesis deals with the definition of classical theoretical concepts. The second part is devoted to the description of behavioral deviations. The final section consists of a questionnaire survey which aims to establish whether the behavior of participants is biased with behavioral deviations or is in accordance with the theory of efficient markets.
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