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Vliv sentimentu na kryptoměnové trhy
Maňoušek, David
This paper empirically identifies the relationship between sentiment and cryptocurrency profitability. The analysis uses daily data for the five largest cryptocurrencies by market capi-talisation: bitcoin, ethereum, binance coin, ripple, and cardano. The sentiment variable used in the analysis is the Fear & Greed Index, which is a quantified measure of market fear and greed. We use wavelet coherence as the main method of the paper to determine the relationship between sentiment and cryptocurrency returns. All cryptocurrencies analysed have a positive correlation for investment horizons ranging from 4 to 32 days, with the sentiment variable as the leading indicator. For traders belonging to the group investing in cryptocurrencies for time frames of 4 to 32 days, the Fear & Greed Index can be used as an indicator to optimise trade entry. If the Fear & Greed Index is rising, investors can expect an increase in returns over a 4 to 32 day horizon and open a long position in response to the move, profiting from the move. The recommendation also applies with the opposite sign: if the Fear & Greed Index falls, investors can speculate on a fall in returns. For longer investment horizons, the Fear & Greed Index acts as a lagging indicator and should not be used to predict future market movements.
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Natural Gas Comovement with Other Commodity Markets - A Wavelet Analysis
Otradovec, Michal ; Gutiérrez Chvalkovská, Jana (advisor) ; Kraicová, Lucie (referee)
This thesis studies the impact of shale gas on commodity and stock markets in the U.S. by employing wavelet approach and conducting a time-frequency analysis of dynamic correlations between natural gas and important representatives of commodity markets: crude oil, coal, corn, wheat, and several indices. It covers the period from 2006 to 2015 and is performed on daily data. Our thesis enlarges existing literature on comovement between natural gas with other energy commodities and stocks using wavelet coherence - a methodology which allows analyzing comovement among assets not only from a time series perspective but also over different frequencies. Financialization of natural gas and its involvement in investment portfolios under changing conditions on the U.S. gas market provide space for examination of gas proper correlation estimates in respect to other financial assets. Our results reveal natural gas comovement behaviour with examined commodities during the Financial Crisis. They show gradual decoupling between gas and crude oil prices in time. To the best of our knowledge we are the first to address natural gas using wavelet coherence in connection to agricultural commodities corn and wheat. These commodities together with natural gas are primary sources for bioethanol production being used in...
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Is hype really that powerful? The correlation between mass and social media and cryptocurrency rates fluctuations
Ilina, Viktoriia ; Král, Michal (advisor) ; Kukačka, Jiří (referee)
Twelve years after Satoshi Nakamoto published the paper describing the functioning mechanism and principals of cryptocurrency that maintains secure and anonymous digital transactions beyond any banks, cryptocurrencies have become a multi-billion-dollar industry comprising millions of investors, miners, developers and profiteers. However, the actual price determinants and ways to forecast future price changes remain an open question yet to discover the answer for. This study attempts to figure out whether media hype exerts that much influence upon cryptocurrencies price movements and whether it can be used as the basis for future movements prediction. Two cryptocurrencies, Bitcoin and Tezos, and 7 mass and social media factors for each of them were considered on daily basis from 08-01-2018 to 10-31-2020. To explore the interdependence between media drivers and cryptocurrencies' prices in short, medium and long timespan, this study deploys wavelet coherence approach. There was found, that price changes turn to be the supreme prior to hype, even though the growing ado may push the prices even higher. Thus, hype is failing to prove itself as a reliable cryptocurrency price predictor. Crypto investors, though, should anyways take the news background into account while building trading strategies,...
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Volatility spillovers between crude oil and food commodities
Hrycej, Martin ; Krištoufek, Ladislav (advisor) ; Janda, Karel (referee)
In this thesis, we analyze volatility spillovers between crude oil and food commodities. The principal hypothesis assumes crude oil to behave as a production factor of the agricultural food commodities, thence we are looking for appropriate price effects. We mainly employ wavelet coherence and partial wavelet coherence, which provide us with valuable insight into the commodities nexus, without any strict restraints and assumptions levied on our data. Secondly, we build a DCC-GARCH model in order to model the presumed volatility spillovers. We also perform several simple benchmark analyses, in particular we test for Granger causality and we compute the Pearson correlation coefficients. Our data sample, including 10 commodities and 2 indices, covers the latest decade, significantly widening the existing contextual literature. Our results are mostly compliant with related literature, especially regarding the crude oil-fuels bundle and food commodities bundle, respectively. Considering the main research question of volatility spillovers between food commodities and crude oil, our results are indicating reasonably strong relationships with crude oil for soybeans and corn, leaving cotton and wheat rather on the verge of strong relationship and finding cattle to be completely unrelated. Main merits of the thesis...
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Natural Gas Comovement with Other Commodity Markets - A Wavelet Analysis
Otradovec, Michal ; Gutiérrez Chvalkovská, Jana (advisor) ; Kraicová, Lucie (referee)
This thesis studies the impact of shale gas on commodity and stock markets in the U.S. by employing wavelet approach and conducting a time-frequency analysis of dynamic correlations between natural gas and important representatives of commodity markets: crude oil, coal, corn, wheat, and several indices. It covers the period from 2006 to 2015 and is performed on daily data. Our thesis enlarges existing literature on comovement between natural gas with other energy commodities and stocks using wavelet coherence - a methodology which allows analyzing comovement among assets not only from a time series perspective but also over different frequencies. Financialization of natural gas and its involvement in investment portfolios under changing conditions on the U.S. gas market provide space for examination of gas proper correlation estimates in respect to other financial assets. Our results reveal natural gas comovement behaviour with examined commodities during the Financial Crisis. They show gradual decoupling between gas and crude oil prices in time. To the best of our knowledge we are the first to address natural gas using wavelet coherence in connection to agricultural commodities corn and wheat. These commodities together with natural gas are primary sources for bioethanol production being used in...
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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 (www.tcpdf.org)
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Food vs. Fuel: The Role of Bioenergy
Filip, Ondřej ; Janda, Karel (advisor) ; Pertold-Gebicka, Barbara (referee)
This thesis studies the relationship between the first generation biofuels and selected commodities and assets in the USA, Europe, and Brazil. It is the first attempt to combine the taxonomy and wavelet analyses in a single research application. Our unique dataset comprises 32 weekly price series covering the 2003--2015 time period. First, we employ a method of minimum spanning trees and hierarchical trees to model a biofuel-related price network. We demonstrate a development phase shift between Brazilian and the US/EU biofuel industries. We reveal a strong and stable connection between Brazilian ethanol and its main production factor, local sugarcane. We further find that US ethanol is closely linked to corn. In the contrary, European biodiesel exhibits only moderate ties to its production factors. Subsequent wavelet analysis scrutinizes the identified price connections both in time and frequency domains. Both Brazilian and US ethanols are found to be positively related to their respective feedstock commodities. In particular, feedstock proves to lead the price of the biofuel and not vice versa. Moreover, the dynamics remains qualitatively unchanged when controlled for the influence of crude oil.
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Comovement of Stock Markets and Commodities: A Wavelet Analysis
Vavřina, Marek ; Vácha, Lukáš (advisor) ; Princ, Michael (referee)
The thesis applies the wavelet analysis to four developed stock market indices (USA, UK, Germany and Japan), four developing stock market indices (Brazil, China, India, Russia) and four commodities (Gold, Crude oil, Heating oil and Natural gas) and it aims to reveal how they comoved in the period of the Global financial crisis, which began in the USA as the Subprime mortgage crisis. Also the potential presence of contagion caused by the bankruptcy of Lehman Brothers bank is investigated. In addition the Granger causality test is applied to give a different perspective and to extend the analysis. Empirical results revealed that the wavelet correlation of stock markets and commodities differ significantly when talking about the short-term and the long-term horizon. This information can be utilized in the portfolio analysis. The wavelet analysis revealed contagion coming from the USA to the German and Brazil stock market, Crude oil and Heating oil market after the bankruptcy of Lehman Brothers. The Granger causality test indicates that there is a very strong causal relationship between stock markets and commodities and it differs at different scales.
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Crude oil co-movement with other representatives of energy and non-energy commodity markets
Mustivaya, Julia ; Baruník, Jozef (advisor) ; Jánský, Ivo (referee)
Financialization of crude oil and its frequent inclusion into investment portfo- lios raise the demand for proper correlation estimates of this commodity and other financial assets. This thesis particularly examines the co-movement of crude oil price with prices of four other representatives of commodity market (gasoline, natural gas, gold and Industrials Index). It contributes to the exist- ing literature by the results obtained from application of wavelet coherence, which allows uncovering dynamics of interconnection between commodity prices in time as well as over different frequencies. Analysis brings many in- teresting findings and practical implications. Among others, it specifies the investment horizons that should be considered to maximize diversification properties of studied commodities. 1
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Food vs. Fuel: The Role of Bioenergy
Filip, Ondřej ; Janda, Karel (advisor) ; Pertold-Gebicka, Barbara (referee)
Bibliographic entry Filip, O. (2015): "Food vs. Fuel: The Role of Bioenergy." (Unpublished master's thesis). Charles University in Prague. Supervisor: prof. Ing. Karel Janda M.A., Dr., Ph. D. Length: 121,976 characters Abstract This thesis studies the relationship between the first generation biofuels and selected commodities and assets in the USA, Europe, and Brazil. It is the first attempt to combine the taxonomy and wavelet analyses in a single research application. Our unique dataset comprises 32 weekly price series covering the 2003-2015 time period. First, we employ a method of minimum spanning trees and hierarchical trees to model a biofuel-related price network. We demonstrate a development phase shift between Brazilian and the US/EU biofuel industries. We reveal a strong and stable connection between Brazilian ethanol and its main production factor, local sugarcane. We further find that US ethanol is closely linked to corn. In the contrary, European biodiesel exhibits only moderate ties to its production factors. Subsequent wavelet analysis scrutinizes the identified price connections both in time and frequency domains. Both Brazilian and US ethanols are found to be positively related to their respective feedstock commodities. In particular, feedstock proves to lead the price of the biofuel and not...
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