ABSTRACT Recent literature explores the profitability of various cryptocurrency momentum trading strategies and proposes cryptocurrency momentum as a pricing factor (Liu et al.). How risky is this factor‐based investment strategy for crypto‐investments? We answer this question by examining the distributional characteristics (hence, riskiness) of six cryptocurrency momentum trading strategies. The empirical evidence suggests that the realised variances of cryptocurrency momentum strategies are governed by power laws. The statistical tests derived from block bootstraps indicate that the population mean and variance of the momentum factor realised variances are statistically not defined. Contrary to the belief that cryptocurrency momentum trading strategies produce generous payoffs, our results imply that, in real life, we might not be able to realise these risk premiums. We conclude that the performance metrics evaluating the profitability of cryptocurrency momentum strategies, using variance as an input, are not informative. We also find cross‐sectional dependence amongst the tail risk of momentum strategies based on different formation periods.
This Bachelor's thesis studies connectedness effects between returns of US-listed cryptocurrency-linked stocks (CLS), the traditional US stock market, and ma- jor cryptocurrencies. We present results of connectedness measures obtained by utilizing the Dynamic Networks framework. Our dataset contains daily returns of 20 CLS, the stock market index S&P 500 and five major cryptocurrencies, with a time span ranging from September 2021 to July 2023. The connected- ness measures indicate a significant total connectedness among variables within the system, across the whole time span. We also present directional connected- ness measures for individual variables and decompose the total connectedness into time horizons. We report the short-term horizon of connectedness effects between 1-5 days to be the most significant. Finally, we build Ordinary Least Squares (OLS) regressions for CLS returns and find connectedness measures to influence returns of CLS with high exposure to the cryptocurrency market most significantly. Keywords Connectedness effects of returns, Cryp- tocurrencies, Bitcoin, Dynamic Networks, Cryptocurrency-linked stocks, Stock market Title Connectedness between Stocks of Cryptocurrency-linked US companies and the Cryptocurrency market.
Abstract Despite recent studies focused on comparing the dynamics of market efficiency between Bitcoin and other traditional assets, there is a lack of knowledge about whether Bitcoin and emerging markets efficiency behave similarly. This paper aims to compare the market efficiency dynamics between Bitcoin and the emerging stock markets. In particular, this study indicates whether the dynamics of Bitcoin market efficiency mimic those of emerging stock markets. Thus, the paper's contribution emerges from the combination of Bitcoin and emerging markets in the field of dynamics of market efficiency. The dynamics of market efficiency are measured using the Hurst exponent in the rolling window. The study uses daily data for the MSCI Emerging Markets Index and the Bitcoin market over the period 2011–2022. Our results show that there is at most a moderate correlation between the dynamics of Bitcoin and emerging stock markets’ efficiency over the entire study period. The strongest correlations occur mainly in periods of high economic policy uncertainty in the largest Bitcoin mining countries. Therefore, the association between Bitcoin market efficiency and emerging stock markets’ efficiency may strengthen with an increase in economic policy uncertainty. These findings may be useful for investors and portfolio managers in constructing better investment strategies.
This paper investigates the profitability of Bitcoin and US equity. More concretely, we inspect the performances of the S&P 500 index and Bitcoin by comparing their returns and volatilities. As a result, we obtain the following significant findings. First, our regression analysis clarifies that for the period after the sudden appearance of COVID-19, there was a weak nexus between the S&P 500 index and Bitcoin returns. In addition, our return and return spread analysis evidences that for this period, on average, Bitcoin returns were much higher than the S&P 500 index returns. Moreover, our volatility and volatility spread analysis reveals that for this period, on average, the volatilities of Bitcoin returns were much higher than those of the S&P 500 index returns.
Virtual assets and currency sector are becoming increasingly intertwined.According to new IMF research, the correlation of crypto assets with traditional holdings like equities has increased dramatically as usage has grown, limiting their risk perception investment opportunities, and raising the danger of spillover across financial markets.Theoretical and empirical findings concerning cryptocurrencies and stock market behaviour have been misleading thereby putting policy makers at a crossroads.This paper therefore examines the response of stock market to investment in cryptocurrencies in the US stock market.Monthly data covering the period between February 2016 to February 2022 was used.The answer was achieved using novel dynamic autoregressive-distributed lag (ARDL) simulation techniques along with the Breitung and Candelon causality test.Findings revealed that cryptocurrencies impacted positively on the US stock market.Secondly, investment in Bitcoin and Ethereum is a good predictor of stock market while no evidence of causality between investment in ripple and stock market indices in the US stock market.Thirdly, a long-run relationship exists between investment in cryptocurrencies and behaviour of stock market indices in the United State, and that investment in cryptocurrencies has a significant long-run increasing effect on stock prices in United State.
The Russia-Ukraine conflict has once again highlighted the need for diversification across asset classes to avoid the fallout of black swan events. This study aims to identify the optimal portfolio weights for long-only investors in emerging Ghana stocks and two major cryptocurrencies: Bitcoin and Ethereum. BEKK-GARCH (1, 1) has been deployed to investigate the volatility spillover between the Ghana Stock Exchange (GSE) and two major cryptos by market share: Bitcoin and Ethereum between January 2019 and December 2021. The influence of the COVID-19 crisis has been examined by dividing the full sample period into three sub-periods: pre-COVID-19, during-COVID-19 and post-COVID-19 pandemic. This study has several important implications. First, the investors can take advantage of higher returns in cryptos by allocating low-single digits exposure and enhancing portfolio risk-adjusted returns. Second, policymakers can formulate policies to encourage more investors to adopt cryptos as an asset class in Ghana.
Bitcoin was presented at the end of 2008 but the question still remains whether it is a form of money or something entirely different. Bitcoin was not designed with the aim to create money in a strict sense but primarily with the intention to make the transfer of value as effective as possible. Yet, Bitcoin has a capacity to take on the role of money, and that capacity was recognized in court cases. In this regard, the paper presents the results of the primarily empirical but also theoretical research conducted previously on the volatile but still very deflationary nature of Bitcoin and its effect on monetary obligations. The idea that cryptocurrencies can be also used as a hedging instrument to prevent the negative effects of domestic currency depreciation might be controversial for a number of reasons, one of which is certainly the volatile nature of bitcoin "price". We stress that periodic depreciation of its value does not mean that bitcoin is inflationary. On the contrary, bitcoin is deflationary by nature, which is evident in different in-built mechanisms and new ways of application. In this paper, the author uses different analytical method techniques to single out and describe various deflatory mechanisms, both preprogramed and factual ones. The author also applies the synthetical method and its techniques, primarily abstraction and generalization, to sum up the data confirming the main hypothesis that bitcoin is by nature deflationary despite its volatility and, therefore, it can be used as a hedging mechanism.
Ta-Cheng Chang, Wei-Ying Nie, Hsuan-Ling Chang, Kuang‐Chieh Yen
We examine how economic policy uncertainty (EPU) influences realized variance dependency and tail-risk synchronization across major cryptocurrencies. Using 5-min high-frequency returns to construct realized variance and signed jump variance measures, we document that global and Western EPU (the US, UK, France) significantly strengthen both variance dependency (VD) and signed jump variance dependency (SJVD) among the top 15 cryptocurrencies, whereas Asian EPUs exhibit weaker and less consistent effects. The sensitivity of SJVD is particularly pronounced, reflecting the asymmetric transmission of tail risk during uncertainty shocks. These findings remain robust after controlling for Bitcoin’s realized volatility and hold in post-COVID subsample analysis. Our results suggest that cryptocurrency markets exhibit greater systemic interconnectedness and heightened tail-risk co-movements during periods of elevated policy uncertainty, with important implications for risk management and financial stability monitoring.