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Good vs. Bad Volatility in Major Cryptocurrencies: The Dichotomy and Drivers of Connectedness
Šíla, Jan ; Kočenda, Evžen ; Kukačka, Jiří ; Krištoufek, Ladislav
Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. We investigate the volatility connectedness dynamics of a representative set of eight major crypto assets. Methodologically, we decompose the measured volatility into positive and negative components and employ the time-varying parameters vector autoregression (TVP-VAR) framework to show distinct dynamics associated with market booms and downturns. The results suggest that crypto connectedness reflects important events and exhibits more variable and cyclical dynamics than those of traditional financial markets. Periods of extremely high or low connectedness are clearly linked to specific events in the crypto market and macroeconomic or monetary history. Furthermore, existing asymmetry from good and bad volatility indicates that information about market downturns spills over substantially faster than news about comparable market surges. Overall, the connectedness dynamics are predominantly driven by fundamental crypto factors, while the asymmetry measure also depends on macro factors such as the VIX index and the expected inflation.
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The Impact of News on Videogame Stock Market Prices and Volatility
Mertová, Veronika ; Čech, František (advisor) ; Kukačka, Jiří (referee)
The thesis investigates the impact of social media and news headline sentiment on stock prices, specifically comparing gaming firms to companies from other industries. Tweets and news headlines containing keywords referring to four selected gaming and four non-gaming companies were collected over 5 and 3 months, respectively. Both tweets and news collected came from the general users or media rather than focusing solely on financial ones. The data were aggregated into daily values. Daily stock price data were also collected for each examined company to derive returns and volatility. The data were analysed using a vector autoregression model in combination with Granger causality. The study found no significant differences between gaming and non-gaming sectors. The polarity of sentiment showed no effect on stock prices. However, when sentiment was divided into different emotions, some significance was observed, although the findings varied across individual firms regardless of their sectors. It was concluded that when using sentiment for market predictions, it is beneficial to either utilize specifically financial media or determine the specific type of sentiment that influences a particular stock. JEL Classification G14, G17, C32, C58 Keywords Tweets, News Headlines, Gaming Industry, Sentiment...
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Dynamics of the volume-volatility relationship in the currency markets
Tůma, Adam ; Baruník, Jozef (advisor) ; Komárek, Luboš (referee)
This work investigates the volume-volatility relationship dynamics in the currency markets using data of five currency pairs in the period between 2010 and 2022. By employing multiple specifications of the HAR model with volume- related regressors and also with time-varying parameters (TVP), we examine the relationships' changing dynamics over time with a focus on improving volatility forecasting performance. Our main findings suggest a strong correlation between volume and volatility. The TVP-HARV model shows significantly changing dy- namics of the volume-volatility relationship, especially during periods affected by politics, changing monetary policies or global crises. The proposed models, however, do not improve out-of-sample volatility forecasting performance com- pared to the benchmark HAR model. The causal effect in the volume-volatility relationship in the currency markets is slightly more substantial in the direction of volatility towards volume, where we find slight forecasting improvements. Our findings conclude that volume and volatility in the currency markets are mainly moving simultaneously with a very strong correlation and much weaker and often insignificant causal effects on both sides, which supports the mixture of distributions hypothesis.
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Gold as a Stable Asset in Economic Recession: An Econometric Analysis
Petrželka, Václav ; Baruník, Jozef (advisor) ; Kukačka, Jiří (referee)
Due to its reliability, durability and rarity, gold has been seen for centuries as a safe haven investment that should prevent large losses during financial crises. However, the question arises whether this characteristic is still relevant for gold. In our thesis, we distinguish between two main aspects of a safe haven asset, namely the degree of volatility and the ability to predict as accurately as possible the evolution of the volatility of a given asset. The major economic crises of the 20th century show us that the volatility of gold during them was lower than that of other assets. We therefore follow up with a detailed analy- sis comparing the volatility of daily returns for gold, stocks, commodities and cryptocurrencies over the period 2006-2021. We find that gold volatility was indeed lowest during the Great Recession after 2007 and after the outbreak of the Covid-19 pandemic in 2020. We also confirm an asymmetric response to negative returns for stocks and commodities, which is not the case for gold and cryptocurrencies. We test the ability to predict assets by comparing predicted daily volatilities and realized daily volatilities over more than a six-month inter- val in 2014 and 2021. We find no relationship to confirm that gold has higher predictability than other assets. Our findings...
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Who Is the Far-Right Voter in Slovakia Today?
Kocábek, Pavel ; Kubátová, Hana (advisor) ; Hájek, Lukáš (referee)
This thesis deals with far-right parties in Slovakia. The objective is to compare them based on selected factors in order to answer the question: Who is the far-right voter in Slovakia today? For this purpose, the most successful far-right parties in recent years were chosen: the Slovak National Party (SNS), the People's Party Our Slovakia (ĽSNS), and a new formation called Republic. The factors adopted are characteristics and genesis, electorate and geographic support definition, and electoral volatility. The paper is divided into four parts. The first part concerns the far-right in Eastern Europe and Slovakia especially. In the second part, the focus is placed on the milestones that shaped and changed the Slovak political environment. Specifically, these are the Slovak state, the transformation period, Mečiar and anti-Hungarian politics, the fall of Mečiar, Fico and a government with the SNS, and the murder of Ján Kuciak. The third chapter analyses individual parties according to the factors mentioned above. Finally, the comparison itself is approached, where differences are identified but particularly parallels. Based on these findings, the author subsequently answers the research question.
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Risk Analysis of Selected Cryptocurrencies in Personal Finance
Strouhal, Tomáš ; Stroukal,, Dominik (referee) ; Karpíšek, Zdeněk (advisor)
This diploma thesis deals with cryptocurrency’s risk regarding other investment opportunities, such as funds. The aim of the work is to present a simple indicator of risk and reward in order to place cryptocurrencies in the context of other investments. First, selected cryptocurrencies are described, then their characteristics are compared with the funds. Synthetic risk and reward indicator is used as a tool to compare risk and reward of cryptocurrencies with the funds. This indicator is modified to match the cryptocurrency’s characteristics and still have a narrative value. After this modification, it is used to calculate the risk and reward of the S&P 500, Allianz Global Artificial Intelligence, Binance Coin, Bitcoin, Cardano, Ethereum, Solana, Tether, USD Coin and XRP. The results show that the original range of the indicator is insufficient given the higher volatility of cryptocurrencies, which it is unable to reflect. Conversely, the adjusted indicator is already very good at calculating with higher volatility in cryptocurrencies and assigning them to a higher risk class.
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Portfolio Proposal of the Fund of Hedge Funds
Fischer, Karel ; Brauner, Roman (referee) ; Rejnuš, Oldřich (advisor)
Diploma thesis deals with the portfolio creation of the fund of hedge funds. Theoretical part describes investment concepts, the theoretical and legislative parts of hedge funds and decription of the various methods used in practical part. The practical part is focused on the selection, analysis and comparison of the hedge funds. Proposal part contains investment recommendations of the portfolio of funds which meet requirements of the management of ABC fund.
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Volume - volatility relation across different volatility estimators
Kvasnička, Tomáš ; Krištoufek, Ladislav (advisor) ; Avdulaj, Krenar (referee)
The main objective of this thesis is to analyze whether traded volume increases predictive power of volatility. We are mostly focused on Garman-Klass volatility estimator, which is more efficient than squared returns. Both univariate (AR, HAR, ARFIMA) and multivariate models (VAR, VAR-HAR) are used to find out if traded volume improves volatility forecasting. Furthermore, GARCH(1,1) both with and without traded volume is carried out and forecasted. All these methods are estimated on a basis of rolling window and during each step 1-day ahead forecast is computed. Final assessment is based on MAPE, RMSE and Mincer-Zarnowitz test of the out-of-sample forecasts, which are compared with the realized volatility. It turns out that traded volume slightly improves predictive power of the scrutinized models in case of FTSE 100 and IPC Mexico, contrary to Nikkei 225 and S&P 500 when a decrease of the predictive power is detected. Moreover, we observe that only HAR and VAR-HAR models are able to produce an unbiased forecast. As the evidence of the improvement is not conclusive and to maintain model parsimony, HAR model fitted by Garman-Klass volatility appears to be the best alternative in case of missing the realized volatility.
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