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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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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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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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