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Dynamic Network Risk across main U.S. sectors
Malecha, Jan ; Baruník, Jozef (advisor) ; Čech, František (referee)
We study the effects of financial networks formed by the connectedness of stock return volatilities within sectors of the S&P 500 Index. We test whether the risk arising from dynamic volatility connections is priced in the cross-section of stock returns. Separately, for each sector, we estimate the dynamic network formed by firm-level realized volatilities from 2006 to 2018. We study how connectedness differs across sectors. Comparing the sector results, we conclude that there is a homogeneous pattern that describes the development of volatility connectedness. The pattern holds across all sectors throughout the studied period and is shaped by major financial events. We create risk factors that attempt to assess the risk arising from dynamic volatility connections. For each sector, we create a factor model that we test using the Fama-Macbeth regression. The results provide evidence that the created risk factors are priced in four out of ten sectors, that is, significant results are found in the Energy, Financials, Industrials, and Consumer Discretionary sectors.
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Correlation between stock and bond returns and it's determinants: Case of Fragile Five
Daldal, Cagatay ; Kočenda, Evžen (advisor) ; Čech, František (referee)
The correlation between stock market returns and government bond yields is helping investors to diversify their investments and hence, reducing their investment risk if the correlation between these asset classes is low or negative. However, the correlation measure is not solely sufficient for investors to diversify their risk considering that correlation between stock market returns and government bond yields and impacted by the same economic conditions. Therefore, it is important understand how correlation between stock market returns and government bond yields is developing over-time and which economic indicators impacting the correlation. The author contributes to the existing literature by modelling the time-varying correlation between stock marketreturnsand governmentbond yields.The currentresearch focused on Turkey,Brazil,South Africa, India and Indonesia. These countries were defined as Fragile Five in 2013 by Morgan Stanley because the currencies of these countries were under high pressure against United States Dollar and shared common vulnerability in their current account levels, inflation, unemployment rate and gross domestic product. These economic indicatorsof Fragile Five are used to determine if the correlation between stock market returns and government bond yields is impacted by...
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High Frequency Price Index of Construction Materials
Štefl, Josef ; Polák, Petr (advisor) ; Čech, František (referee)
The paper explores the possibilities of using big data in economics in an effort to shift research from a study of statistical samples towards basic populations. To this end, the Construction Materials Price Index was created to capture price level movements in this market segment on weekly basis. This specific field was chosen because, despite its signi- ficance, it has not yet been examined in much detail by the Czech Statistical Office. The underlying index data represent the complete offer of the three most significant Czech eshops with building materials, which is periodically obtained through web scraping. The research took place between October 2021 and June 2022. The nine-month evolu- tion of the index reflects the economic recovery after the covid-19 pandemic, but also the sharp market response after the Russian invasion of Ukraine. This bachelor thesis contains a detailed description of the methods used as well as a thorough analysis of the results. JEL classification Keywords Title C43, C55, C80, E31, E37 inflation, high frequency price index, big data, web scraping, construction materials price level High Frequency Price Index of Construction Materials High Frequency Price Index of Construction Materials Josef Štefl
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The Impact of Popular Sports Events on the Local Stock Markets
Konvičný, Martin ; Čech, František (advisor) ; Kukačka, Jiří (referee)
The diploma thesis studies the impact of hosting popular sports events and sports results on local stock market indexes and sponsors' stock using ARMA- GARCH and ARMA-DCC-GARCH models between January 2009 and May 2021. The empirical evidence shows that sports results positively affect the returns of emerging stock market indexes in some cases. However, hosting mega sports events has a limited impact on local financial markets. I did not observe any significant loss effect after defeats. According to research results, sports variables do not influence the stock variance. Despite controlling for dependencies related to soccer sentiment, significant interdependencies across Polish and Ukrainian stock market indexes still occurred. That implies other factors are driving the correlation between the stock markets. JEL Classification G41, D53, D81, C58, Z2 Keywords sports sentiment, stock markets, behavioral fi- nance, sports events Title The Impact of Popular Sports Events on the Lo- cal Stock Markets
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Can a Dual-beta Five-Factor Model Explain Stock Market Variation in CEE?
Lu, Shuhong ; Čech, František (advisor) ; Chondrogiannis, Ilias (referee) ; Paulus, Michal (referee)
The study applies a dual-beta five-factor model to investigate how return is correlated with market factor, size, value, profitability and investment factors in the CEE region. Dual betas are employed in a pooled regression to account for different behaviour in different market conditions. The results show that market factor is significant across the sample period from 2003 to 2017, and the coefficient of the market factor is lower in bearish market and higher in bullish market. By employing dual betas, the explanatory power of a model has increased. However, the effect is limited, and we do not recommend using the dual-beta model due to the loss of simplicity. Post-regression diagnosis has confirmed the appropriateness of using our model by checking the key assumptions of Ordinary Least Square. Limitations are presented at the end to suggest future study.
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ETFs: Analysis of Timing and Length of Investment
Polanka, Martin ; Čech, František (advisor) ; Švéda, Josef (referee)
This bachelor's thesis provides an analysis of the effect of timing and length of investment on return with the use of ETF data. The results show evidence that both variables are affecting returns. The author found a positive relationship between the length of an investment horizon and the probability of a positive return, as well as significant differences in return among different starts of investments. Further, the author describes ETF in the context of similar investment instruments such as other types of funds and exchange-traded products with their main benefits and drawbacks.
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The transition from IBORs to new benchmarks
Ratajová, Kateřina ; Polák, Petr (advisor) ; Čech, František (referee)
The manipulation of LIBOR (London Interbank O ered Rate) and other issues around the interbank o er rates have led to their replacement by overnight rates. Some interbank o ered rates ceased at the end of 2021. Thus, this thesis is devoted to observing their behavior, estimating their drivers, and comparing them. For analysis of the rates' drivers is used ARIMAX model, which is an ARIMA model extended by exogenous variables. The possible drivers are indexes, which indicate volatility, sensibility, financial stress, and liquidity. Among key findings of this thesis are that the European IBOR rates are more prone to market volatility, which explains the impact of the European stock index. Furthermore, Bloomberg's indexes of financial condition are a good indicator for both European IBOR rates as well as British pound LIBOR and SONIA. In the US, USD LIBOR reacts to a liquidity index, while SOFR to the volatility in the market. JEL Classification F33, F37, G15, G2 Keywords interbank rates, transition, financial conditions index, LIBOR Title The transition from IBORs to new benchmarks
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Influence of stock market variables on correlations among S&P sectors
Coufal, Matěj ; Čech, František (advisor) ; Baruník, Jozef (referee)
This thesis investigates the influence of the exogenous variables (S&P 500 Index, 10-year US Treasury Note, crude oil, and CBOE Volatility Index (VIX)) on the dynamics of correlations among S&P sectors. We concentrate on daily and weekly investment horizons, and employ the bivariate Dynamic Conditional Correlation (DCC) model. Changes in correlations implied by the DCC model are further modelled using the exogenous variables. The results indicate that VIX has the best ability to predict future changes in correlations. An increase in VIX on day (week) t is expected to cause a rise in correlations on day (week) t + 1. Next, correlations of the Energy sector tend to increase in weeks when crude oil prices are falling. Further, correlations of the Information Technology sector are likely to increase on days of rising yield on the 10-year US Treasury Note. Although we detect a certain power to predict future changes in correlations, very little of these changes is actually explained. 1
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Perceiving Uncertainty on Financial Markets During the Covid-19 Pandemic
Balažovič, Matej ; Čech, František (advisor) ; Hronec, Martin (referee)
This thesis examines the effects of the COVID-19 pandemic on forward rate agreements (FRA) spreads in the Czech Republic. Since FRA serves as a useful instrument to hedge against possible risk associated with interest rate movements, it is a relevant indicator of a consensus view and perceived uncertainty about the future financial situation. We measure the effects by employing ARMA-GJR- GARCH modeling. Several COVID-19 indices, representing the government response to the pandemic, are included as explanatory variables. The results show a significant drop in FRA spreads as the pandemic began, as well as a strong increase in the FRA spreads volatility, which doubled during that period. Our main findings suggest that the COVID-19 affected the decrease of FRA spreads. However, we were not able to explain the volatility increase by the COVID-19 data.
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