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Non-Fungible Tokens (NFTs): A hype or hope? Analysis of random NFT portfolios
Iordosopol, Ana ; Krištoufek, Ladislav (advisor) ; Nechvátalová, Lenka (referee)
This thesis reflects on the newly emerged alternative asset class of non-fungible tokens (NFTs). We perform both qualitative and quantitative analyses on the matter. In the empirical part, we construct different types of random portfolios to investigate the performance of cryptocurrency- based portfolios after the possible inclusion of NFTs in such. Our results suggest that as of the end of 2022, portfolios of Bitcoin and Ether perform better without NFTs, thus rejecting the previous assumptions of limited diversification potential of NFTs, which was detected during the last crisis period during the COVID-19 pandemic. The qualitative analysis on the topic, however, suggests that NFTs are not just the hype and the innovative blockchain solutions that NFTs represent may be of greater use in the near future. Therefore, despite of non-efficiency of NFTs as a financial asset in 2022, they still display significant potential as a disruptive technology. Keywords NFT, Cryptocurrency, Random portfolio, Blockchain, Non-fungible token. Title Non-Fungible Tokens (NFTs): A hype or hope? Analysis of random NFT portfolios.
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Can Bitcoin serve as an inflation hedge in the USA, Euro area, and Czech markets?
Volkov, Aleksandr ; Krištoufek, Ladislav (advisor) ; Šestořád, Tomáš (referee)
Since the 1970s, economists have started studying the concept of inflation hedging as a way to protect investments. With the recent high inflation rates, investors might be interested if newly created assets such as cryptocurrencies can be effective against inflation. This thesis paper aims to find out whether thelargest crypto asset Bitcoin can be used as an inflation hedge. To answer this question, Fisher coefficient estimation and hedging demand for the US, Euro Area, and the Czech Republic for the period between November 2014 and October 2022 will be analyzed. In addition, the vector autoregressive model (VAR)will be used for the US market in the same time frame. The results showed overall positive Bitcoin returns but all three methods indicated no or negative correlation between inflation rates in three regions and Bitcoin returns. The thesis paper concludes that Bitcoin cannot be used as an inflation hedge as notall requirements are met. Keywords Cryptocurrency, Bitcoin, gold, inflation, inflation hedge, Fisher coefficient,VAR model Title Can Bitcoin serve as an inflation hedge asset in the US, Euro Area, andCzech markets?
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Gamified Stock Markets, Sentiment and Volatility: Evidence from the GameStop frenzy
Tran Nguyen, Thai Nhat Phi ; Krištoufek, Ladislav (advisor) ; Kočenda, Evžen (referee)
In this thesis, we study the impact of individual retail investors on the financial markets. We follow the GameStop retail trading frenzy from the beginning of 2021 and the retail investors aggregated on Reddit's r/wallstreetbets. The tools employed include natural language processing, wavelet analysis and vector error correction models. The results propose that the retail investor sentiment is highly susceptible to high volatility, extreme returns and frequent news coverage. Social media is shown to exacerbate these behavioural tendencies. We find evidence that retail investor sentiment is able to predict short-term returns for stocks specifically targeted by retail investors. The findings are, however, dependent on the investment horizon. Over long horizons, we find evidence for the reversal of the relationship. Lastly, while the effect of news and social media is similar in the long run, we show that Reddit sentiment, as opposed to news sentiment, is a significant predictor of retail targeted stocks in the near term. JEL Classification C55 C58, G12, G14, G41 Keywords Sentiment, Social media, GameStop, Reddit, Natural language processing, Wavelet analysis Title Gamified Stock Markets, Sentiment and Volatility: Evid- ence from the GameStop frenzy 1
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Price gaps in the stock market
Vosmanský, Jakub ; Krištoufek, Ladislav (advisor) ; Vácha, Lukáš (referee)
This thesis aims to scrutinise price gaps in the stock market. The key objective is to analyse candlestick charts surrounding price gaps and determine whether any patterns accompany their presence. Firstly, the thesis briefly describes candlestick patterns, literature relevant to price gaps and Convolutional Neural Network (CNN) as the method of choice. Price gaps are studied in a 5-minute time frame in the data of all S&P 500 constituents in the years from 2015 to 2021. By feeding images of the candlestick chart into the CNN, the proposed model reaches an Accuracy of 74.2% in predicting whether a future price will be higher or lower than the price at the gap. This result can be translated into a statement that the CNN detects hidden patterns around the price gaps. Furthermore, the thesis finds that these patterns di er across individual stocks. The thesis also shows that including news sentiment in the analysis does not improve the ability to discover patterns. JEL Classification C45, C55, C88, G14, G15, G41 Keywords price gap, convolutional neural network, pattern detection, news sentiment Title Price gaps in the stock market
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Consequences of Implementation of Video Assistant Referee in Fortuna Liga
Habáň, Ondřej ; Krištoufek, Ladislav (advisor) ; Nevrla, Matěj (referee)
The thesis deals with the issue of the Video Assistant Referee in football. It evaluates the consequences of its implementation in Czech Fortuna Liga on the sample of 678 matches held during two and half seasons. The results from the models designed to treat count data were compared with relevant literature. In the form of both simple and multiple regression with additional control variables was investigated the relationship between VAR and the set of match- changing incidents, including yellow cards, red cards and penalty kicks, and the relationship between VAR and errors of on-pitch referees. The terms presence of VAR, VAR interventions and VAR as the whole were di erentiated. Whereas a significant statistical association of VAR as the whole was not revealed for yellow and red cards, a 56% increase in the number of penalties associated with VAR as the whole significantly performed. Furthermore, the negative and highly significant 118% association of the presence of VAR was reckoned in the case of errors of on-pitch referees. Subsequently, the percentage decreased due to VAR interventions, however, not su ciently to reveal a negative and significant association in errors of on-pitch referees for VAR as the whole. The exception created errors based on factual decisions. JEL Classification Z21, F21, Z29,...
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Gold, oil, and stocks as safe havens for Bitcoin
Nedvěd, Martin ; Krištoufek, Ladislav (advisor) ; Kurka, Josef (referee)
Bitcoin is often compared to gold for its gold-like features such as a store of value, a limited supply, and a safe haven. However, due to Bitcoin's extreme price movements, investors might rather look for a safe haven against Bitcoin. In this thesis, we study such properties among traditional assets. Specifically, we analyze gold, oil, and stocks as safe havens for Bitcoin on a sample period from 2014 until March 2022. We find that gold acts as a strong safe haven suggesting gold's traditional role as a shelter during uncertainty holds also for this crypto asset. 1
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Multifractal nature of financial markets and its relationship to market efficiency
Jeřábek, Jakub ; Vošvrda, Miloslav (advisor) ; Krištoufek, Ladislav (referee)
The thesis shows the relationship between the persistence in the financial markets returns and their efficiency. It interprets the efficient markets hypothesis and provides various time series models for the analysis of financial markets. The concept of long memory is broadly presented and two main types of methods to estimate long memory are analysed - time domain and frequency domain methods. A Monte Carlo study is used to compare the methods and selected estimators are then used on real world data - exchange rate and stock market series. There is no evidence of long memory in the returns but the stock market volatilities show clear signs of persistence.
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Analysis of gasoline and diesel prices in the Czech Republic
Badáňová, Martina ; Krištoufek, Ladislav (advisor) ; Šopov, Boril (referee)
This thesis investigates relationship between fuel (gasoline and diesel) prices in the Czech Republic and world crude oil prices over the period from 2004 to 2011. Using daily data we estimate an asymmetric error correction model and we find that in the short-run fuel prices are adjusted upwards to the long-run equilibrium faster than they are adjusted downwards to the equilibrium. However, the difference in responses is found to be not statistically significant.
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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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