|
|
Arbitrage on the Cryptocurrency Markets: An Analysis of Potential Opportunities
Suchánek, Vojtěch ; Fanta, Nicolas (advisor) ; Čech, František (referee)
1 Abstract Cryptocurrency markets have currently a lot of attention both from the public and researchers. This thesis connects the well-documented field of arbitrage with the relatively new bitcoin phenomenon. Thanks to the efforts of cryptocurrencies for decentralization and non-regulation, they are an ideal asset for arbitrage trading. This study tries to answer whether price differences between cryptocurrency exchanges existed during the second and third quartal of 2021 and if it was possible to perform an arbitrage trading with positive profit. It analyzes several trading strategies and ways how to execute these trades. An important part of the study is the involvement of trading fees, which play a crucial role in total profitability but are often omitted in similar research. The findings confirm that price differences existed during the analyzed period, and their values allow for profitable arbitrage trading. The best performing strategy uses stable-coin USDT as a mean of transport money between exchanges, which lowers the time of one trade and allows multiple trades during one price difference spike. This strategy was able to gain 362.60% profit over the analyzed period. On the other hand, the distribution of trades over the analyzed period shows some irregularities, which might have a negative impact...
|
|
|
The empirical research of cross-listed shares: The case of AH shares
Zhang, Haiying ; Čech, František (advisor) ; Novák, Jiří (referee)
This thesis analyzes the information transmission and correlation of the AH share and its listed stock markets and uses the Shanghai-Hong Kong Stock Connect (refer as "the Connect") as a breakthrough to study its development trend. The dataset includes the daily returns of Shanghai and Hong Kong stock markets, AH share markets, and eight AH bank shares during 2010-2018. Using DCC GARCH and VAR models, we find persistent correlations for Shanghai and Hong Kong stock markets, the AH share market, and AH bank stocks. However, for AH bank shares, we do not find a growing trend of dynamic correlation. Moreover, the Connect has an insignificant effect on the correlation of cross-listed shares. We also find Granger causality for the SSE index as the Hang Seng index, but for the AH share market and AH bank shares, it is Granger causality for the H stocks as the A stocks.
|
|
| |
|
|
Does LSTM neural network improve factor models' predictions of the European stock market?
Zelenka, Jiří ; Baruník, Jozef (advisor) ; Čech, František (referee)
This thesis wants to explore the forecasting potential of the multi-factor models to predict excess returns of the aggregated portfolio of the European stock mar- ket. These factors provided by Fama and French and Carhart are well-known in the field of asset pricing, we also add several financial and macroeconomic factors according to the literature. We establish a benchmark model of ARIMA and we compare the forecasting errors of OLS and the LSTM neural networks. Both models take the lagged excess returns and the inputs. We measure the performance with the root mean square error and mean absolute error. The results suggest that neural networks are in this particular task capable of bet- ter predictions given the same input as OLS but their forecasting error is not significantly lower according to the Diebold-Mariano test. JEL Classification C45, C53, C61, E37, G11, G15 Keywords Stocks, European market, Neural networks, LSTM, Factor Models, Fama-French, Predic- tions, RMSE Title Does LSTM neural network improve factor mod- els' predictions of the European stock market?
|
|
|
Effect of Quantitative Easing on the US Stock Market During the COVID-19 Pandemic
Michalík, Ondřej ; Čech, František (advisor) ; Džmuráňová, Hana (referee)
This work examines the effects of quantitative easing on different stock in- dices in the form of S&P 500, NASDAQ-100, DJIA and Russell 2000. The effects are analysed through the implementation of standard statistical methods and ARMA-GJR-GARCH models. Weekly data on total assets held by Fed and announcement dates are employed as variables representing quantitative easing. A strong positive relationship between quantitative easing and the stock market indices was found, with the most significant effect on the Russell 2000. The in- clusion of quantitative easing in our ARMA equation visually seemed to explain some of the market's volatility after the Fed's announcements of quantitative easing, but statistical methods did not confirm this hypothesis.
|
|
|
The Principle and Economic Analysis of Bitcoin
Jiang, Jinggang ; Holub, Tomáš (advisor) ; Čech, František (referee)
The development of Internet technology has promoted the progress of all aspects of society. Under the background of Internet finance, the traditional financial model is changing, such as currency payment. With the deepening of Internet technology, the virtualization of money is deepening, and the market entry, trading and payment methods are also subverting the tradition. Bitcoin as a new means of payment began to appear in the public eye. It is a challenge to the traditional way of trading supported by Internet technology. Despite the constant controversy since its inception, Bitcoin still occupies a place with its unique advantages - Asymmetric encryption, decentralization,transparency of transaction records and so on. In the eyes of opponents, Bitcoin is more of a highly speculative asset, and as it becomes progressively more difficult to mine, the cost of mining is increasing. However, in the eyes of supporters, it is a reliable means of payment, not subject to government supervision, nor will it produce a virtual transaction record. From the regulator's point of view, it is more like a shelter for unscrupulous people to evade regulation and commit money laundering and crime. It is undeniable that in just a few years, Bitcoin has developed to a certain scale,has a certain industrial chain...
|
|
|
Liquidity and Predictability of Cryptoassets
Mjartanová, Viktória ; Krištoufek, Ladislav (advisor) ; Čech, František (referee)
The relationship between liquidity and return predictability may be an im- portant aspect to consider when investing in cryptoassets. We examine this relation using both cross-sectional as well as panel data. First, we calculate a set of predictability measures and aggregate the results into four variables. We then regress the predictability variables on a set of controls and two measures of liquidity, specifically the Amihud illiquidity ratio and the Corwin-Schultz spread estimate. The other independent variables include the logarithm of volume, turnover ratio and Garman-Klass volatility. Results from the cross- sectional analysis indicate that liquidity negatively impacts the degree of return predictability. Moreover, findings from a subset of panel data, including only 50 cryptoassets with the largest market capitalization, provide some evidence in favor of this relationship. Results from full panel data, however, present contradictory evidence. For these regressions, liquidity is found to be either in- significant or to possess a positive impact on the degree of return predictability. Altogether, we obtain mixed evidence about the effect of cryptoasset liquidity on return predictability. JEL Classification C53, C58, G14 Keywords Cryptoassets, Predictability, Liquidity, Panel data Title...
|
|
|
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.
|
|
|
Marginal Effect of R&D Expenditures on Value of Technology Companies
Tuček, Lukáš ; Kočenda, Evžen (advisor) ; Čech, František (referee)
1 Abstract Research and development is an inseparable part of technology industry as technology companies, unlike most, rely on R&D not only as means of effi- ciency improvement to existing production, but rather as means of production itself. This thesis presents an alternative approach to R&D intensity measure and applies it in an empirical analysis on technology leaders company data from 2013 through 2018 measuring R&D intensity impact on company market value. Additionally, this thesis explores the differences in impact of R&D on company value dependent on the company's product cycle nature. The re- sults of this thesis are mostly conforming to existing academic literature and show diminishing returns to R&D intensity. A surprising negative effect of a variable comparing given company's R&D expenditures to ones of the segment leader of a given segment has been found. There has been found no lag dif- ference between the groups of companies with open and closed cycle product development. JEL Classification O31, O32, M21 Keywords research and development, technology, market value Title Marginal Effect of R&D Expenditures on Value of Technology Companies
|
|
|
Sector ETF portfolio optimization using differential evolution
Holešínský, René ; Čech, František (advisor) ; Kraicová, Lucie (referee)
This thesis examines the use of differential evolution in a real-world portfolio op- timization task based on US stock data. We empirically test the capability of the algorithm to find an inter-sector allocation that outperforms a broad-market stock index. Two constrained sector ETF portfolios are constructed to simulate realis- tic agent-based settings and performance of the competing portfolios is analyzed in terms of both return and risk. The results are further extended to include Markowitz' global minimum variance portfolio and a naive 1/N portfolio. We show that the con- structed portfolios are indeed capable of outperforming the market whilst simultane- ously maintaining lower tail risk, however, the performance significantly deteriorates if the portfolios are rebalanced based on rolling data windows. Overall the algorithm delivers satisfying results while providing the user with a relative freedom when choosing portfolio constraints. JEL Classification: C61, G11, G17, G19 Keywords: portfolio optimization, exchange-traded funds, differen- tial evolution, empirical analysis Title: Sector ETF Portfolio Optimization Using Differential Evolution Author's e-mail: rene.holesinsky@gmail.com Supervisor's e-mail: frantisek.cech@fsv.cuni.cz 1
|
guest ::
