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Analysis of herd behavior across cryptocurrencies
Krouská, Kateřina ; Kukačka, Jiří (advisor) ; Fanta, Nicolas (referee)
This thesis studies herding behavior in the cryptocurrency market between 2017 and 2022. Results from the static model reveal significant imitative behavior in the up market and during the bull year 2017. In addition, this thesis ranks among the first papers that study the effect of the early stage of the war in Ukraine on the market-wide herding behavior. Furthermore, due to Bitcoin's dominant position among other coins, closer attention is devoted to studying its influence on the herding behavior in the market. However, herding seems to be present only during extreme Bitcoin movements. In response to these results, five dominant coins (Bitcoin, Ethereum, XRP, Litecoin and Dogecoin) are excluded from the sample and their influence on the rest of the market is studied. The evidence suggests strong herding behavior of the rest of the market around these five giants. Therefore, the return of smaller coins seems to be influenced by the performance of larger coins, rather by solely that of Bitcoin. JEL Classification G02, G15, G40, C22, C58 Keywords Cryptocurrencies, Herding behavior, Bitcoin, COVID-19 Title Analysis of herd behavior across cryptocurren- cies Author's e-mail 43789078@fsv.cuni.cz Supervisor's e-mail jiri.kukacka@fsv.cuni.cz
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Herd Behaviour in Financial Markets: Evidence from the Technology Sector
Máca, Jaroslav ; Kukačka, Jiří (advisor) ; Hronec, Martin (referee)
This thesis provides an evidence of herd behaviour in financial markets with an emphasis on the technology sector. The adjusted closing prices for the NASDAQ-100 index constituents are analysed on a daily basis during the period 2011-2020. Regarding methodology, the commonly utilized measures of cross-sectional standard deviation of returns and of cross-sectional absolute deviation of returns are considered. The examination reveals no evidence of herd behaviour, even when filtering trading sessions based on extraordinary market volatility or trading volume. However, a closer look at 2020, in which financial markets movements were heavily affected by the ongoing COVID-19 pandemic, shows that herd behaviour contributed to the sharp and significant crash as well as to the subsequent skyrocketing recovery. Furthermore, this thesis presents an innovative way of using an external factor in regression models. Due to their dominant position, the so-called technology giants are excluded from the US stock market and they newly constitute the world market. This specification reveals that the dispersions of the technology giants are contagiously amplified to the rest of the technology sector. Therefore, investors should be aware of the risks associated with a possible cooling of the entire technology sector following...
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Herd behavior of investors in the stock market: An analysis of cross-country effects in the CEE
Lerche, Vojtěch ; Kukačka, Jiří (advisor) ; Vácha, Lukáš (referee)
The thesis examines herding behavior of investors towards the market average in 10 CEE stock markets during the period 2000-2018. Least squares and quantile regression methods provide evidence of herding inside the majority of the countries. During the global financial crisis and the Eurozone crisis, the herding mentality was more intense only in Slovenia and Croatia. The thesis finds mixed results in asymmetric herding during days of positive and negative market returns. The main finding, and a contribution to the literature, is that the domestic cross-sectional dispersion of returns in the CEE is affected by the dispersion of returns of the foreign stock markets in the USA, the UK, and Germany. In addition, empirical results suggest that extreme market conditions in the U.K. market have an impact on the formation of herding forces within the CEE stock markets. Short-run arbitrageurs can benefit from collective decisions of investors that in turn drive stock prices away from their fair value, but the presence of herding undermines benefits of portfolio diversification. In the long-run, the contagious international effects may result in a severe instability of the whole region and in market inefficiency.
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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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