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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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Good volatility, bad volatility, and the cross-section of stock returns at different investment horizons
Sako, Tony Ryan Hlali ; Baruník, Jozef (advisor) ; Kukačka, Jiří (referee)
Starting with the assumption that different investors have different investment time preferences and different risk tolerances within their given investment time-frames, this paper investigates the value of employing multiresolution analysis to model volatility and risk-pricing. In terms of estimation and fore- casting performance we were able to reduce by at least half the volatility fore- casting errors, with even better results at longer horizons. In regards to risk pricing we learn that extreme aggregate volatility (i.e. tail risk) is priced but regular volatility is not. Additionally we find that whilst aggregate volatility is generally more important over the long-horizon, during periods of market turmoil it is much more significant over the short-horizon. Finally we show that stocks with high sensitivity to aggregate volatility have lower subsequent returns supporting the idea that they become attractive as a hedge against market volatility. JEL Classification C12, C13, C21, C22, C31, C32, C51, C52, C53 Keywords Realized Volatility, Wavelet, Long-Memory Models, Cross-Section, Volatility Forecast, High-Frequency Data Author's e-mail tony sako@yahoo.com Supervisor's e-mail barunik@fsv.cuni.cz
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Accounting-based credit scoring models - The Altman Z-score
Dibon, Michael ; Čornanič, Aleš (advisor) ; Kukačka, Jiří (referee)
This Bachelor thesis is focused on accounting-based credit scoring models, predominantly on Altman (1968) Z-score. We examine the relevance of the Z-score model on European publicly traded companies over the period 2012 - 2017. Moreover, we analyze whether it is important to calibrate original models as well as we test the performance of models given different misclassification costs. Our results suggest that Altman original Z-score model is still, after 50 years of existence, relevant in the European after-crisis environment. Further, we found evidence that re-estimation of the model is unnecessary and could even cause harm to model performance. Finally, the performance of models seems to be stable given not equal misclassification costs, as the more accurate models from ROC analysis reported better results in an economic test. Keywords Z-score, accounting-based models, credit score, Altman, financial ratios, bankruptcy, ROC, Europe
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Extending Hotelling's location model into Agent-based domain
Vainer, Jan ; Kukačka, Jiří (advisor) ; Smutná, Šarlota (referee)
This thesis examines behaviour of adaptive agents in Hotelling's location model. We conduct an agent-based simulation in Hotelling's setting with two agents, where the agents use Nash-Q learning mechanism for adaptation. Traditional game-theoretic models often stand on strong assumptions imposed on players such as rationality and perfect information. We explore what alternations or re- finements of results this technique brings in comparison to the original analytical solution of the theoretical Hotelling's location model. We discover that under Nash-Q learning and quadratic consumer cost func- tion, agents with high enough valuation of future profits learn behaviour similar to aggressive market strategy, where both agents make similar products and lead a price war in order to eliminate their opponent from the market. This be- haviour closely resembles the Minimum differentiation principle from the original Hotelling's paper with linear consumer costs. This result is surprising because in our simulation, quadratic consumer cost functions are used, which should result in maximum differentiation of the products. Our results suggest that the Prin- ciple of minimum differentiation could be justified based on repeated interaction of the agents and long-run optimization. Additionally, suitability of...
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Inflation Targeting Turns Ten in Georgia: Assessment of the Experience
Megrelishvili, Ketevan ; Baxa, Jaromír (advisor) ; Kukačka, Jiří (referee)
The paper evaluates transition of the monetary policy in Georgia to inflation targeting and the record of the first years of experience with this policy. The inflation targeting was officially announced in 2009; nevertheless, the National bank of Georgia ("NBG") was investigating and planning the transition since 2006. The NBG implemented new instrument the monetary rate - as a precondition for switching to the inflation targeting. The NBG has also improved the independence and transparency following its introduction. Then, we assess the success of the policy change by investigating the efficiency of the monetary transmission mechanism using vector auto-regression models with alternative identification schemes, in particular, the Cholesky decomposition and sign restrictions approach. Our findings suggest that the monetary transmission mechanism works primarily via the Tbilisi interbank rate while the effects of changes in the newly implemented monetary policy rate are bit weaker. The maximum price decrease is achieved after about 15-17 months and it somewhat coincides with the NBG's horizon (4-6 quarters). We have further established that the monetary policy supports the financial stability to a certain extent. JEL Classification E4, E52, P2 Keywords Inflation targeting, Monetary Transmission...
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Agent-Based Analysis of Market Potential for Electric Vehicles in the Czech Republic
Wojnarová, Renáta ; Kukačka, Jiří (advisor) ; Chorna, Olena (referee)
This study explores the economical, ecological, and social impact of poten- tial rise of the number of electric vehicles in the Czech Republic. For this purpose, the methodology of agent-based modelling and cost-benefit analysis is used. Particularly, a simple agent-based model in the NetLogo software is created and calibrated to the Czech environment. It enables us to examine the impact of possible policies aimed at increasing electric vehicles' market potential. Results of the cost-benefit analysis suggest that under the current Czech conditions, over their whole life cycle, electric vehicles produce less CO2 emissions in comparison to conventional internal combustion engine vehicles and thus, are more ecological. With the actual policy without any financial incentives, however, electric vehicles' total costs connected to their purchase, usage and maintenance for an average Czech consumer are still higher com- pared to conventional vehicles. If the government would intend to signific- antly increase electric vehicles' market share, both financial incentives and policies making their everyday usage easier are suggested to be implemented. Purchase discounts together with accessibility advantages are, according to this analysis, the most effective ways. Charging infrastructure development and electricity...
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Spillovers between low and high risk assets during business cycle
Matyáš, Jan ; Krištoufek, Ladislav (advisor) ; Kukačka, Jiří (referee)
1 Abstract This master thesis examines linkages among bond and stock markets in Ger- many, Austria and Italy. For the purpose of analysis of return spillovers, we use Spillover index framework which enables us to describe development of inter- market linkages over time. The data used in the study includes the period from January 2nd, 1998 to May 23rd, 2017 which allows us to estimate long- term development of spillovers among markets. We find unequal link between stocks and bonds and increase in co-integration of markets during the financial crisis of 2007-2008 with significant persistence after the crisis. Mechanism of transmission of financial shocks among European countries is affected by eco- nomic and political integration of countries. We identify strong interlinkages of markets with substantial influence of Italian assets in transmitting shocks to German and Austrian assets, especially during periods of economic distress. On the other hand, Germany represents an open economy that is increasingly integrated to other markets. Scale of return spillovers is highly dependent on economic situation which is evident from clustering of high spillovers during recessions and a great deal of persistence of these interdependencies. JEL Classification G01, G12, G15, C63, C67 Keywords return spillovers, asset...
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