National Repository of Grey Literature 41 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Frequency Connectedness of Financial, Commodity, and Forex Markets
Šoleová, Juliána ; Baruník, Jozef (advisor) ; Vácha, Lukáš (referee)
This Thesis is dedicated to the variance decompositions from the VAR model un- der the Diebold, Yilmaz (2012) methodology combined with the Baruník, Křehlík (2017) method of frequencies that was used to create traditional and directional spillover tables to be compared under different frequencies. Diverse markets vari- ables were used for the analysis during the period 1/6/1999 to 29/6/2018. The S&P 500 Index represented the financial markets, EUR/USD and YEN/USD rep- resented the Forex markets, and eight types of commodities: Crude Oil, Natural Gas, Gasoline, and Propane represented energy commodities and Corn, Coffee, Wheat, and Soybeans represented food commodities. This analysis contribute to understanding of the dynamic frequency connectedness in case of a differentiated system of markets. The main finding was the strongest short-frequency reaction to shocks in case of all variables, which is opposite behavior than usually observed in banking sector frequency dynamics analyses. JEL Classication: F12, F21, F23, H25, H71, H87 Keywords: connectedness, financial market, forex market, commodity market, systemic risk, spillovers, frequency analysis Author's e-mail: Supervisor's e-mail:
Co-jumping of yield curve
Fišer, Pavel ; Baruník, Jozef (advisor) ; Vácha, Lukáš (referee)
The main focus of the thesis is on jumps and co-jumps and their influence on the term structure of the U.S. Treasury bond futures contracts. Using high frequency data I am able to quantify to which extent co-jumps affect the correlation between bond futures pairs with different maturities which is not common in the literature. In order to separate the price process into continuous and discontinuous components represented by jumps and to pre- cisely localize significant co-jumps a new wavelet-based estimator is used for the analyses. Furthermore, I am studying the co-jump behavior in response to scheduled macroeconomic news announcements. Empirical findings re- veal strong influence of co-jumps to the correlation structure of bond futures across all maturity pairs as well as a significant link between Federal Open Market Committee news announcements and higher probability of co-jump occurrence.
Low Interest Rates and Asset Price Fluctuations: Empirical Evidence
Ali, Bano ; Horváth, Roman (advisor) ; Vácha, Lukáš (referee)
The thesis focuses on estimating the effect of expansionary monetary policy concerning asset prices, specifically house and stock prices as they are of pri- mary importance in financial markets. A structural vector autoregressive model is used including data for the Euro Area, the United Kingdom, and the United States from 2007 to 2017. Moreover, instead of short-term nominal interest rate, the shadow policy rate is used to measure the stance of both conventional and unconventional monetary policy. It is useful when policy rates of central banks are at or near zero as it neglects the zero-lower bound. Using both impulse response functions and forecast error variance decomposition, results suggest that higher interest rates are indeed associated with lower asset prices. That is confirmed by including two different estimates of shadow rates into the model and observing the effect for two specific types of assets. More precisely, house prices react almost immediately showing the most substantial decrease for the United Kingdom, while stock prices slightly increase at first and de- crease afterward with similar size of the effect for all areas under consideration. Finally, the discussion of how the monetary authority should react to asset price fluctuations is provided, summarizing the vast amount of literature...
Time-scale analysis of sovereign bonds market co-movement in the EU
Šmolík, Filip ; Vácha, Lukáš (advisor) ; Krištoufek, Ladislav (referee)
The thesis analyses co-movement of 10Y sovereign bond yields of 11 EU mem- bers (Greece, Spain, Portugal, Italy, France, Germany, Netherlands, Great Britain, Belgium, Sweden and Denmark) divided into the three groups (the Core of the Eurozone, the Periphery of the Eurozone, the states outside the Eurozone). In the center of attention are changes of co-movement in the crisis period, especially near the two significant dates - the fall of Lehman Brothers (15.9.2008) and the day, when increase of Greek public deficit was announced (20.10.2009). Main contribution of the thesis is usage of alternative methodol- ogy - wavelet transformation. It allows to research how co-movement changes across scales (frequencies) and through time. Wavelet coherence is used as well as wavelet bivariate and multiple correlation. The thesis brings three main findings: (1) co-movement significantly decreased in the crisis period, but the results differ in the groups, (2) co-movement significantly differs across scales, but its heterogeneity decreased in the crisis period, (3) near to the examined dates sharp and significant decrease of wavelet correlation was observable across lower scales in some states. JEL Classification C32, C49, C58, H63 Keywords Co-movement, Wavelet Transformation, Sovereign Debt Crisis, Sovereign Bond Yields,...
Estimation of Financial Agent-Based Models
Kukačka, Jiří ; Baruník, Jozef (advisor) ; Vácha, Lukáš (referee) ; ZWINKELS, REMCO C. J. (referee) ; GERBA, EDDIE EDIN (referee)
This thesis proposes computational framework for empirical estimation of Finan- cial Agent-Based Models (FABMs) that does not rely upon restrictive theoretical assumptions. First, we develop a two-step estimation methodology for one of the his- torically first FABMs-the stochastic cusp catastrophe model. Our method al- lows us to apply catastrophe theory to stock market returns with time-varying volatility and to model stock market crashes. The methodology is empirically tested on nearly 27 years of U.S. stock market returns. We find that the U.S. stock market's downturns were more likely to be driven by the endogenous market forces during the first half of the studied period, while during the sec- ond half of the period, the exogenous forces seem to be driving the market's instability. The results suggest that the proposed methodology provides an important shift in the application of catastrophe theory to stock markets. Second, we customise a recent methodology of the Non-Parametric Simu- lated Maximum Likelihood Estimator (NPSMLE) based on kernel methods by Kristensen & Shin (2012) and elaborate its capability for FABMs estimation purposes. To start with, we apply the methodology to the most famous and widely analysed model of Brock & Hommes (1998). We extensively test finite sample properties of the...
Time-frequency analysis of technology IPOs
Kuš, Martin ; Vácha, Lukáš (advisor) ; Seman, Vojtěch (referee)
In our work, we focus on the dynamics of the volatility and co-movement during the first year of public trading. We use the wavelet analysis to investigate the return volatility of the technology stocks an their co-movement with the market in the time-frequency space. We employ the data sampled on multiple frequencies, ranging from 1 second high-frequency to daily data. We present three main findings. First, we identify gradual decline of the return volatility on all but the shortest investment horizons. Second, we do not find a convincing evidence that the technology stocks synchronize with the rest of the market as they get mature. Third, the different nature of the synchronization with the NASDAQ and S&P 500 indices is also not confirmed. JEL Classification C22, C32, C58, G19 Keywords IPO, technology stocks, wavelet analysis Author's e-mail Supervisor's e-mail
The Impact of High Frequency Trading on Price Volatility
Vondřička, Jakub ; Vácha, Lukáš (advisor) ; Vošvrda, Miloslav (referee)
This thesis examines an impact of high frequency trading on equity market qualities. As an indicator of market quality, stock prices realized volatility is used. To estimate the high frequency trading activity, we implement a special method of identification of high frequency orders from quote data. Study of relation between high frequency trading and market qualities is incited by growing concerns about the welfare impacts of high frequency trading and connected activities. In order to test the dependence and causality between high frequency trading activity and volatility, we implement time-scale estimation techniques. Wavelet coherence is used to study localized dependence. The analysis is amended by a robustness check, using wavelet correlation. Results show inconsistent dependence at short trading horizons and regions of significant continuous dependence at trading horizons within hours. Powered by TCPDF (

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2 VÁCHA, Ladislav
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