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Monetary Policy Under Behavioral Expectations: An Empirical Validation of the Heuristic Switching Model
Bolshakov, Sergey ; Kukačka, Jiří (advisor) ; Kučera, Tomáš (referee)
This work takes one of the most prominent behavioral New-Keynesian models from the shelf and estimates it via the simulated method of moments. The model exhibits a remarkably good ft to the auto- and cross-covariance pro- fles of the euro area macroeconomic time series, especially compared to the standard rational expectations model. This result corroborates the claim that central banks which implement strict infation targeting are better of reacting to the output gap, on top of infation. JEL Classifcation E52, E70, D84, C53 Keywords Behavioral macroeconomics, heterogeneous ex- pectations, New-Keynesian model, Heuristic Switching Model, simulated method of moments Title Monetary Policy Under Behavioral Expecta- tions: An Empirical Validation of the Heuristic Switching Model
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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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Occupancy Rate in Paid Parking Zones in Prague
Kašparová, Amálie ; Pleticha, Petr (advisor) ; Kukačka, Jiří (referee)
The bachelor thesis deals with occupancy measurement in Paid Parking Zones (PPZ) in Prague with system of random monitoring by special vehicles equipped with cameras. It introduces distinction between immediate occupancy, i.e. the percentage use of parking spaces in a given area in a given time and effective occupancy, i.e. the percentage use of time parking capacity in a given time interval. Since the effective occupancy cannot be determined in real conditions of PPZ by random monitoring, the method of simulation of parking in the model area was chosen. The model was created based on parameters expected parking time of visitors and residents and parking interest. The model simulates the use of parking capacity and its output are simulated effective and immediate occupancy. The basic parameter values were obtained by analysing the real data for 2018 from PPZ. The goal of the thesis was to analyse under which conditions and number of measurements, the immediate occupancy is a good estimate of effective occupancy. In total, 10500 simulations were performed for 21 different parameter combinations resulting in an effective occupancy of about 45%-95%. The results of the simulation show, that five measurements in one working week are sufficient to estimate effective occupancy in the same time interval....
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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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Corporate Acquisitions and Expected Stock Returns: A Meta-Analysis
Parreau, Thibault ; Havránek, Tomáš (advisor) ; Kukačka, Jiří (referee)
This thesis aims at investigating the puzzling relationship between cor- porate acquisitions and expected stock returns by reviewing numerous studies on this topic through the use of state of the art meta-analysis tools. Such an analysis is required because many papers examined this relationship but their results varied. We therefore collected 421 estimates from 20 papers and led multiple regressions to test for the presence of publication bias. Throughout this analysis we indeed found evidence supporting the existence of publication bias. Furthermore, we decided to apply Bayesian Model Averaging to reduce the model uncertainty and find out why our abnormal returns estimates greatly vary across stud- ies. Our results suggest that one of the most important drivers are the standard-error terms. This subsequently proves that publication bias is the most responsible for the heterogeneity amongst our estimates. Our analysis fails to demonstrate any positive effects from M&A activity on a firm post-acquisition performance. We suggest that other motives are under-represented in the underlying theory that aims to assess M&A outcomes. Keywords Mergers and Acquisitions, Stock Returns, Abnormal Re- turns, Meta-Analysis, Publication bias Author's e-mail thibault.parreau@gmail.com Supervisor's e-mail...
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Cusp catastrophe theory: Application to the housing market
Kořínek, Vojtěch ; Kukačka, Jiří (advisor) ; Nevrla, Matěj (referee)
The bachelor's thesis applies the stochastic cusp catastrophe model to the housing market of the United States. Weekly data over the period from 2007 to 2017 are used. The current catastrophe theory literature related to the housing market is reviewed, the models found are assessed and expanded. Specifically, we have identified three deficiencies of the catastrophe models applied to housing market in the current literature and our contribution lies in the elimination of these deficiencies. In order to satisfy the constant volatility assumption of the model, the state variable is normalized by the estimated volatility derived from GARCH. Furthermore, multiple control variables are added to the model to represent the activity of fundamentalists and chartists. The results suggest that the cusp catastrophe model fits the data better than the linear and logistic models. The normalization of the state variable improves the model performance while the introduction of the additional control variables does not produce better results. Keywords Housing market, catastrophe theory, stochastic cusp catastrophe model, hous- ing bubble, real estate, fundamental investors, speculation. 1
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The weather and stock returns
Černý, Patrik ; Kukačka, Jiří (advisor) ; Čornanič, Aleš (referee)
This thesis examines a behavioral finance topic, the effect of weather on stock returns. The research was performed with the aim to verify formerly published results of various weather variables like sunshine, precipitation or temperature influencing stock markets. For the analysis Ordinary Least Squares regressions were implemented to investigate the relationships of stock returns and weather variables proposed in the previous literature as well as other market efficiency effects, a Monday and a January effect. In addition, GARCH model was carried out to check the influence of weather conditions on stock return volatility. Data used for the analysis consists of 24 emerging and 23 developed markets worldwide in the period 2006-2017. The results are not in support of the theory of weather affecting market trading which corresponds to the market efficiency theory. There seems to be no difference between the developed and emerging countries, not even countries' land area plays a role. However, in the thesis repeatedly appears significant evidence of the presence of the Monday effect. Keywords Behavioral finance, Weather effect, Market efficiency, Anomaly, GARCH 1
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Frequency connectedness and cross section of stock returns
Haas, Emma ; Baruník, Jozef (advisor) ; Kukačka, Jiří (referee)
The thesis presents a network model, where financial institutions form linkages at various investment horizons through their interdependence measured by volatility connectedness. Applying the novel framework of frequency connectedness mea- sures Baruník & Křehlík (2018), based on spectral representation of variance de- composition, we show fundamental properties of connectedness that originate in heterogeneous frequency responses to shocks. The newly proposed network mod- els characterize financial connections and systemic risk at the short-, medium- and long-term frequency. The empirical focus of this thesis is on the interde- pendence structure of US financial system, specifically, major U.S. banks in the period 2000 - 2016. In the light of frequency volatility connectedness measures, we argue that stocks with high levels of long-term connectedness represent greater systemic risk, because they are subject to persistent shocks transmitted for longer periods. When we assess institutions' risk premiums in asset pricing model, the model confirms the significance of volatility connectedness factor for asset prices. JEL Classification C18, C58, C58, G10, G15, Keywords connectedness, frequency, spectral analysis, sys- temic risk, financial network Author's e-mail 93539385@fsv.cuni.cz Supervisor's e-mail...
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Artificial Prediction Markets, Forecast Combinations and Classical Time Series
Lipán, Marek ; Baruník, Jozef (advisor) ; Kukačka, Jiří (referee)
Economic agents often face situations, where there are multiple competing fore- casts available. Despite five decades of research on forecast combinations, most of the methods introduced so far fail to outperform the equal weights forecast combination in empirical applications. In this study, we gather a wide spectrum of forecast combination methods and reexamine these findings in two different classical economic times series forecasting applications. These include out-of- sample combining forecasts from the ECB Survey of Professional Forecasters and forecasts of the realized volatility of the U.S. Treasury futures log-returns. We asses the performance of artificial predictions markets, a class of machine learning methods, which has not yet been applied to the problem of combin- ing economic times series forecasts. Furthermore, we propose a new simple method called Market for Kernels, which is designed specifically for combining time series forecasts. We found that equal weights can be significantly out- performed by several forecast combinations, including Bates-Granger methods and artificial prediction markets in the ECB Survey of Professional Forecasters application and by almost all examined forecast combinations in the financial application. We also found that the Market for Kernels forecast...
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Analysis of a Behavioral New Keynesian Model
Křížková, Šárka ; Kukačka, Jiří (advisor) ; Hlaváček, Michal (referee)
The thesis focuses on the analysis of a Behavioral New Keynesian DSGE model. In particular, various specifications of the model are collected from the existing literature and their combinations are simulated. The specifications include heuristics for forecasting output gap, sets of estimated or calibrated parameters and model structures. The resulting simulated output and inflation gap series are compared with the macroeconomic stylized facts and real world data from the US and Euro area based on their distributional characteristics and autocorrelation structures. In addition, a comparison of various simulated model specifications is performed based on the level of correlation between fractions of agents following a specific heuristic and the resulting output and inflation gap values. The distributional characteristics of the US output gap seem to be matched the best by the specifications with unbiased and extrapolative output gap heuristics generating series with higher levels of variance and kurtosis. Contrarily, the Euro output gap is best matched by specifications with optimistic, pessimistic and unbi- ased heuristics producing series with lower levels of variance and kurtosis. Second, the autocorrelation structure of the simulated series tends to mirror the stylized facts as opposed to the...
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