|
|
Quantitative Methods of Risk Control
Marcinek, Daniel ; Hurt, Jan (advisor) ; Hendrych, Radek (referee)
This thesis deals with stock modelling using ARCH and GARCH time series. Important aspect of stock modelling is to capture volatility correctly. Volatility in finance is usually defined as a standard deviation of asset returns. Many different models, which are summarized in the first part of this thesis, are used to model volatility. This thesis focus on multivariate volatility models including multivariate GARCH models. An approach to constructing a conditional maximum likelihood estimate to these methods is given. Discussed theory is applied on real financial data. In numeric application there is a construction of a volatility estimates for two specific stocks using models described in the first part of this thesis. Using the same financial data various bivariate models are compared. Based on comparison using maximum likelihood a specific model for these stocks is recommended. Powered by TCPDF (www.tcpdf.org)
|
|
|
Commodity Connectedness: Short-run Versus Long-run
Jurka, Vojtěch ; Baruník, Jozef (advisor) ; Buzková, Petra (referee)
Commodity Connectedness: Short-run Versus Long-run Vojtěch Jurka Bachelor Thesis, IES FSV UK, 2018 The thesis contributes to empirical literature that studies volatility spillovers among the commodity and equity market, focusing on short-term and long-term linkages between them. Studying the persistence of volatility transmission is helpful for understanding the information flow, which is crucial for risk management and regulators. The persistence of volatility linkages represents how quickly information can be processed by markets. In this work, we explain the theoretical background of connectedness measures proposed by Diebold and Yilmaz (2012) and show the relationship with measures defined in the frequency domain by Baruník and Křehlík (2018), that allows us to distinguish between short and long persistent shocks in volatility of markets. We continue with the analysis of volatility transmission among stock market and key commodities which represents various sectors of the commodity market. Our first key finding is that in the period 1993- 2015 spillovers among markets more than doubled and persistence of connections have increased. Using a rolling sample over 250 days, we evaluate rich dynamics of connections between equity and commodity sectors. The dynamic analysis reveals that the global financial...
|
|
|
Extreme value theory: Empirical analysis of tail behaviour of GARCH models
Šiml, Jan ; Šopov, Boril (advisor) ; Kocourek, David (referee)
This thesis investigates the capability of GARCH-family models to capture the tail properties using Monte Carlo simulation in framework of Conditional Extreme Value Theory. Analysis is carried out for three different GARCH-type models: GARCH, EGARCH, GJR-GARCH using Normal and Student's t-distributed innovations on four well-known stock market indices: S&P 500, FTSE 100, DAX and Nikkei 225. After conducting 3000 simulations of every estimated model, the Hill estimate of shape parameter implied by the GARCH-type models will be calculated and the models' performance will be assessed based on histograms, descriptive statistics and Root Mean Squared Error of simulated Hill estimates. Interesting results and im- plications for further research have been identified. Firstly, we highlight the Normal distribution's inappropriate nature in this case and its inability to capture the tail properties. Furthermore, GJR-GARCHT with t-distributed innovations is identified to be the best model, closely followed by other t-distributed GARCH-type models. Finally, a pattern in all Q-Q plots forecasting the simulation study results is appar- ent, with the exception of the DAX. This anomalous behaviour therefore necessitated further analysis and a significant right tail influence was recorded. Even though Hill estimates...
|
|
|
Modeling of Long Memory in Volatility Using Wavelets
Kraicová, Lucie ; Baruník, Jozef (advisor) ; Adam, Tomáš (referee)
ii Abstract This thesis focuses on one of the attractive topics of current financial literature, the application of wavelet-based methods in volatility modeling. It introduces a new, wavelet-based estimator (wavelet Whittle estimator) of a FIEGARCH model, ARCH- family model capturing long-memory and asymmetry in volatility, and studies its properties. Based on an extensive Monte Carlo experiment, both the behavior of the new estimator in various situations and its relative performance with respect to two more traditional estimators (maximum likelihood estimator and Fourier-based Whittle estimator) are assessed, along with practical aspects of its application. Possible solutions are proposed for most of the issues detected, including suggestion of a new specification of the estimator. This uses maximal overlap discrete wavelet transform instead of the traditionally used discrete wavelet transform, which should improve the estimator performance in all its applications, not only in the case of FIEGARCH model estimation. The thesis concludes that, after optimization of the estimation setup, the wavelet-based estimator may become an attractive robust alternative to the traditional methods.
|
|
|
Efficiency of the prediction markets: case of Intrade
Brandejs, David ; Dózsa, Martin (advisor) ; Benčík, Daniel (referee)
1 Abstract Bachelor thesis confirms weak market efficiency hypothesis for political events, which took place on Intrade prediction market and finished between 1. October and 31. December 2012. Three unit root tests, ADF GLS, KPSS and Lo-Mackinlay test proved on 5% confidence level, that 140 of 191 tested political events is weakly market efficient, which means high relative market efficiency (73,3%). Testing out-of-political markets shows significantly lower market efficiency. Logit model rejected on 5% confidence level the assumption, that total volume of traded shares is significant parameter for the estimation of market efficiency. Keywords Prediction market, Intrade, efficiency market hy- pothesis, relative market efficiency, ADF test, KPSS test Author's e-mail David.Brandejs@seznam.cz Supervisor's e-mail Martin@Dozsa.cz
|
|
|
Electricity market: Analysis and prediction of volatility
Kunc, Vladimír ; Krištoufek, Ladislav (advisor) ; Hájek, Jan (referee)
Electricity market: Analysis and prediction of volatility Abstract Vladimír Kunc July 30, 2015 The last two decades can be characterized by restructuring of energy industry and the creation of new, competitive energy markets, where accurate forecasts of elec- tricity prices and price volatility are valuable both to consumers and producers. The aim of this work is to analyse several models for prediction of the price volatility of electricity on the Czech Electricity Day-ahead market on price data provided by OTE, a.s. for years 2009-2014. This work compares 144 different models' configura- tions for three distinct classes of models - autoregressive models, GARCH models, and artificial neural network models. This work provides comparison based on five different criteria, each describing the model in different way. Keywords: price prediction, volatility prediction, GARCH, neural networks, LSTM 1
|
|
|
The Impact of Renewable Electricity on the Czech Electricity Balancing Market
Kašparová, Amálie ; Hanus, Luboš (advisor) ; Janda, Karel (referee)
As global investments in renewable energy technologies continue to grow, their effects on electricity markets are a challenge for regulators and policymakers. The thesis examines the effects of forecast errors of Czech and German renew- able energy sources on the size and volatility of the system imbalance of the Czech balancing market. Using a quantile regression and ARFIMA-GARCH models on hourly data, I found that higher solar and wind forecast errors in- crease the system imbalance in absolute terms and affect the volatility. The results show that the Czech solar and wind forecast errors have significantly higher effect than the German forecast errors on the size and volatility of the system imbalance. The strongest effect on the size and volatility of the system imbalance have the Czech solar forecast errors. Therefore, the Czech govern- ment should insist on improving the accuracy and availability of renewable energy forecasts from the transmission system operator ČEPS. Klasifikace JEL C14, C50, Q42 Klíčová slova renewable sources, forecast errors, balanc- ing market, system imbalance
|
|
|
Analysis of the US stock market during the COVID-19 pandemic
Tůma, Adam ; Krištoufek, Ladislav (advisor) ; Fanta, Nicolas (referee)
This work investigates the effect of the COVID-19 pandemic on the S&P 500 stock index and its eleven sectors. Employing the ARMA and the T-GARCH model on a time series of daily returns from 2018 until March 2021, we examine the impact on volatility, returns, and day-of-the-week effect during the stock market crash caused by the pandemic and the period after. Our main findings imply that in the case of returns, the Monday effect was more negative than the Friday effect during the market crash and vice versa in the rising market after the crash. Concluding that the calendar time hypothesis holds for the observed periods. In terms of volatility, it drastically increased across the US stock market during and even after the crash. The increase was especially noticeable for the IT and Energy sectors. We also found the U-shaped daily volume pattern changed significantly with proportionately less volume of trades happening in the first half-hour of trading and more throughout the whole day.
|
|
|
Power markets and the EU ETS: How volatility propagates across Central Europe?
Jurka, Vojtěch ; Baruník, Jozef (advisor) ; Čech, František (referee)
The thesis deals with connectedness in the uncertainty of the carbon and power markets in Central Europe. While the drivers of power price were extensively documented in the literature, we investigate how uncertainty propagates between the German power market and its production factors using a recently developed framework of connectedness measurement. The connections in uncertainty on markets are insightful for the decision of the agents that require a premium for undertaking risk. The empirical results suggest that connectedness in uncertainty significantly varies over the studied period. The interdependence of power with coal decreases while the spillovers between gas and power rise on importance reflecting the changes in generation mix of Germany. For most of the period, the volatility of carbon and power markets is highly correlated. However, the share of volatility transmission spikes several times during the period of 2016-2019. In reaction to the reform of the EU Emission Trading Scheme, the uncertainty about emission allowance prices propagates to the German power market, increasing the uncertainty about power prices on the long horizon.
|
|
|
Vliv ceny ropy na hodnotu akcií společností těžících ropu
Pavlata, Josef
This diploma thesis is focused on evaluation of impact of oil price changes on share values of oil companies. The main goal was to clarify whether stocks of oil companies with state share react to oil price movements differently than stocks of oil companies without state share. This hypothesis was verified by analysis of time series of oil price (WTI) and share values of seven oil companies (BP, ExxonMobil, Lukoil, PetroChina, Statoil, Petrobras). One-day data from 2002-2016 period were used. Investment recommendation based on econometric methods (correlation analysis, regression analysis, VAR model, Granger causality) and financial methods (volatility, profitability) was drawn up in this study. The hypothesis of state influence was confirmed.
|
guest ::
