Does Bitcoin still own the dominant power? An intraday analysis

The study investigates the intraday dynamics and price patterns of the primary cryptocurrencies. The Granger Mackey-Glass (M-G) model is employed to examine the asymmetric and nonlinear dynamic interactions in the first moment using positive and negative returns. The bivariate BEKK-GARCH model is applied to identify cross-market volatility shocks and volatility transmissions in the cryptocurrency market. The intra-cryptocurrency market analysis reveals that Bitcoin contains predictive information that can nonlinearly forecast the performance of other digital currencies when cryptocurrency prices either are rising or declining. The dominant power of Bitcoin is not dismissed using the intraday data. Further, Bitcoin's intraday lagged shocks and volatility induces more rapid and destabilizing effects on the conditional volatility of other currencies than each of the other currencies does on BTC's conditional volatility. The virtual currency markets are dynamically correlated and integrated through first and second-moment spillovers.     

Directional predictability from central bank digital currency to cryptocurrencies and stablecoins

This paper investigates the interaction and the directional predictability between the central bank digital currencies (CBDCs) and the major cryptocurrencies and stablecoins during the period between 17 May, 2019–31 December, 2021. To this aim, we employ the "Cross-Quantilogram” model, to examine how and whether the traditional digital currencies react to the CBDC uncertainty and attention shocks. Our findings suggest that CBDC uncertainty index is negatively related to cryptocurrency and stablecoin returns. Furthermore, the CBDC attention index is negatively associated with Bitcoin, Ethereum, XPR and Terra USD, however, it is positively related to Tether, Binance, USD Coin and Dai. Our results are useful for regulators, investors and policy makers, to understand and assess the potential effect of CBDC adoption news on the volatility of the stablecoins and traditional cryptos.     

The economics of Bitcoin and similar private digital currencies

Recent innovations have made it feasible to transfer private digital currency without the intervention of an organization such as a bank. Any currency must prevent users from spending their balances more than once, which is easier said than done with purely digital currencies. Current digital currencies such as Bitcoin use peer-to-peer networks and open source software to stop double spending and create finality of transactions. This paper explains how the use of these technologies and limitation of the quantity produced can create an equilibrium in which a digital currency has a positive value. This paper also summarizes the rise of 24/7 trading on computerized markets in Bitcoin in which there are no brokers or other agents. The average monthly volatility of returns on Bitcoin is higher than for gold or a set of foreign currencies in dollars, but the lowest monthly volatilities for Bitcoin are less than the highest monthly volatilities for gold and the foreign currencies.     

Cryptocurrencies: Stylized facts on a new investible instrument

We present stylized facts on the asset pricing properties of cryptocurrencies: summary statistics on cryptocurrency return properties and measures of common variation for secondary market returns on 222 digital coins. In our sample, secondary market returns of all other currencies are strongly correlated with Bitcoin returns. We also provide some investment characteristics of a sample of 64 initial coin offerings.     

Investor attention in cryptocurrency markets

We examine the relationship between investor attention, and measures of uncertainty, with the market dynamics of Bitcoin and other cryptocurrencies. We find that increases in investor attention are associated with higher returns, more volatility, and greater illiquidity in cryptocurrency markets. In contrast, cryptocurrency uncertainty (UCRY) and financial market uncertainty (VIX) are also positively related to volatility and illiquidity but have a negative contemporaneous relationship with returns. The identified relationships are accentuated during the COVID-pandemic, and are robust to different measures of investor attention, volatility, and illiquidity. Our results suggest that monitoring investor attention could assist both investors and policymakers.     

Static and dynamic connectedness between NFTs,Defi and other assets: Portfolio implication

The paper examines the return and volatility transmission between NFTs, Defi assets, and other assets (oil, gold, Bitcoin, and S&P 500) using the TVP-VAR framework. The results report weak static return and volatility spillovers between NFTs and Defi assets and selected markets, showing that these new digital assets are still relatively decoupled from traditional asset classes. Bitcoin, oil, and half of the NFTs and Defi assets are net transmitters of return and volatility spillovers, whereas rest of the markets are net recipients of spillovers. Our findings show that the dynamic return and volatility connectedness become higher during the initial phase of the COVID-19 pandemic and the cryptocurrency bubble of 2021. We also compute the static and dynamic optimal weights, hedge ratios, and hedging effectiveness for the portfolios of NFTs/other asset and Defi asset/other asset and show that investors and portfolio managers should consider adding NFTs and Defi assets in their portfolios of gold, oil, and stock markets to achieve diversification benefits.     

Volatility changes in European currency exchange rates due to EMS announcements

This study examines the effects of announcements concerning European Monetary Union on the exchange rate volatilities of several European currencies. It is expected that when good news is portrayed in regard to a single currency this will be considered bad news, thus eliciting a negative reaction, for the German mark. Conversely, good news for a single currency should also be good news for weaker currencies, such as the Portuguese escudo, the Italian lira, the Greek drachma, and the Spanish peseta. In terms of volatility, a reaction to good news should be a reduction in volatility, as bad news should cause an increase in volatility. In total there are 22 announcements examined from January 1986 through September 1997. The German mark is observed to experience greater increases in volatility than decreases, as does the Italian lira. Portugal and Greece appear to react more strongly to positive news in that the decreases in volatility are on average greater than the increases.     

The impact of central bank digital currency news on the stock and cryptocurrency markets: Evidence from the TVP-VAR model

This study employs a non-linear framework to investigate the impacts of central bank digital currency (CBDC) news on the financial and cryptocurrency markets. The time-varying vector autoregressive (TVP-VAR) model developed by Primiceri (2005) is estimated based on weekly data from the first week of January 2015 to the last week of December 2021. The vector of endogenous variables in the VAR estimation contains the Central Bank Digital Currency uncertainty index (CBDCU), cryptocurrency policy uncertainty index, S&P 500 index, VIX, and Bitcoin price. The TVP-VAR model’s time-varying responses demonstrated that the reactions of the cryptocurrency market to central bank digital currency announcements vary remarkably over time. The impacts of the CBDC shocks on the financial market have been increasingly visible during the COVID-19 pandemic. According to the time-varying forecast error decompositions, CBDCU and VIX shocks have accounted for most of the variance in cryptocurrency uncertainty and Bitcoin return shocks, notably during the COVID-19 period.     

Bitcoin as a Complement to Emerging Market Currencies

Bitcoin is a digital currency that has gained significant traction as an economic instrument. Despite its rise, it has received little attention from the scholarly community. This study is one of the first studies to examine Bitcoin’s use as a complement to emerging markets currencies; more specifically, I analyze the value and volatility of Bitcoin relative to emerging market currencies and explore ways in which Bitcoin can complement emerging market currencies. The results suggest that Bitcoin has characteristics that make it well-suited to work as a complement to emerging market currencies and that there are ways to minimize Bitcoin’s risks.     

Equilibrium Bitcoin Pricing

We offer a general equilibrium analysis of cryptocurrency pricing. The fundamental value of the cryptocurrency is its stream of net transactional benefits, which depend on its future prices. This implies that, in addition to fundamentals, equilibrium prices reflect sunspots. This in turn implies multiple equilibria and extrinsic volatility, that is, cryptocurrency prices fluctuate even when fundamentals are constant. To match our model to the data, we construct indices measuring the net transactional benefits of Bitcoin. In our calibration, part of the variations in Bitcoin returns reflects changes in net transactional benefits, but a larger share reflects extrinsic volatility.     

Currency jumps,cojumps and the role of macro news

This study investigates the impact of macro news on currency jumps and cojumps. The analysis uses intra-day data, sampled at 5-min frequency, for four currencies for the period 2005–2010. Results indicate that currency jumps are a good proxy for news arrival. We find 9–15% of currency jumps can be directly linked to U.S. announcements. Notably, news can explain 22–56% of the 5-min jump returns, and there is evidence that better-than-expected news about the U.S. economy has a negative impact on currency jumps. Cojump statistics suggest close dependencies among European currencies, especially between the euro and the Swiss franc. We also provide evidence on the uncertainty resolution to news.     

Good volatility,bad volatility,and the cross section of cryptocurrency returns

This paper examines the predictability of realized volatility measures (RVM), especially the realized signed jumps (RSJ), on future volatility and returns. We confirm the existence of volatility persistence and future volatility is more strongly related to the volatility of past positive returns than to that of negative returns in the cryptocurrency market. RSJ-sorted cryptocurrency portfolios yield statistically and economically significant differences in the subsequent portfolio returns. After controlling for cryptocurrency market characteristics and existing risk factors, the differences remain significant. The investor attention explains the predictability of realized jump risk in future cryptocurrency returns.     

Asymmetric mean reversion of Bitcoin price returns

Non-linearity is characterised by an asymmetric mean-reverting property, which has been found to be inherent in the short-term return dynamics of stocks. In this paper, we explore as to whether cryptocurrency returns, as represented by Bitcoin, exhibit similar asymmetric reverting patterns for minutely, hourly, daily and weekly returns between June 2010 and February 2018. We identify several differences in the behaviour of Bitcoin price returns in the pre- and post-$1000 sub-periods and evidence of asymmetric reverting patterns in the Bitcoin price returns under all the ANAR models employed, regardless of the data frequency considered. We also present evidence indicating stronger reverting behaviour of negative price returns in terms of both reverting speed and magnitude compared to positive returns and evidence of positive serial correlation with prior positive price returns. Finally, we also investigated asymmetries in Bitcoin price return series' persistence by employing higher order ANAR models, finding evidence of a higher persistence of positive returns than negative returns, a result that further supports the existence of asymmetric reverting behaviour in the Bitcoin price returns.     

The impact of jumps on carry trade returns

This paper investigates how jump risks are priced in currency markets. We find that currencies whose changes are more sensitive to negative market jumps provide significantly higher expected returns. The positive risk premium constitutes compensation for the extreme losses during periods of market turmoil. Using the empirical findings, we propose a jump modified carry trade strategy, which has approximately two-percentage-point (per annum) higher returns than the regular carry trade strategy. These findings result from the fact that negative jump betas are significantly related to the riskiness of currencies and business conditions.     

Currency carry trade regimes: Beyond the Fama regression

We show that carry trade strategies resemble FX option strategies that sell out of the money puts on high interest rate currencies. Both strategies collect premiums to generate persistent excess returns that unwind sharply when volatility increases. We also show that the widely documented negative slope coefficient in regressions of exchange rate depreciation on forward currency premiums is an artifact of the volatility regime. In high volatility regimes, the so-called Fama regression produces a positive coefficient greater than unity. We finally document the existence of an intuitive co-movement between currency risk premiums and yield curve risk factors.     

Investigating the nature of interaction between crypto-currency and commodity markets

This paper investigates the dynamic relationship and volatility spillovers between cryptocurrency and commodity markets using different multivariate GARCH models. We take into account the nature of interaction between these markets and their transmission mechanisms when analyzing the conditional cross effects and volatility spillovers. Our results confirm the presence of significant returns and volatility spillovers, and we identify the GO-GARCH (2,2) as the best-fit model for modeling the joint dynamics of various financial assets. Our findings show significant dynamic linkages and volatility spillovers between gold, natural gas, crude oil, Bitcoin, and Ethereum prices. We find that gold can serve as a safe haven in times of economic uncertainty, as it is a good hedge against natural gas and crude oil price fluctuations. We also find evidence of bidirectional causality between crude oil and natural gas prices, suggesting that changes in one commodity's price can affect the other. Furthermore, we observe that Bitcoin and Ethereum are positively correlated with each other, but negatively correlated with gold and crude oil, indicating that these cryptocurrencies may serve as useful diversification tools for investors seeking to reduce their exposure to traditional assets. Our study provides valuable insights for investors and policymakers regarding asset allocation and risk management, and sheds light on the dynamics of financial markets.     

On the investment credentials of Bitcoin: A cross-currency perspective

We examine diversification capabilities of Bitcoin for a global portfolio spread across six asset classes from the standpoint of investors dealing in five major fiat currencies namely US Dollar, Great Britain Pound, Euro, Japanese Yen and Chinese Yuan. Considering the period of prolonged decline in Bitcoin’s value throughout 2018, we employ modified conditional value-at-risk and standard deviation as measures of risk to perform portfolio optimisations across three asset allocation strategies. Results show that portfolios denominated in Japanese Yen, Chinese Yuan and US Dollar account for greater proportion of optimal investment in Bitcoin and exhibit higher improvement in risk-adjusted returns due to investment in Bitcoin. We also perform a comprehensive risk-adjusted evaluation of portfolios with and without Bitcoin to reinforce striking variation in degree of diversification benefits of Bitcoin in a cross-currency context. Taken together, our findings provide insights into sharp disparity in Bitcoin trading volumes across national currencies from a portfolio theory perspective.     

The Role of People’s Expectation in the Recent US Housing Boom and Bust

This paper investigates how an important driver of the recent housing boom and bust, people’s expectation, influences housing asset returns. Specifically, it extends the volatility feedback model to study the relationship between housing volatility and asset returns during 19632007. The analysis considers two alternative breakpoints, 1984Q1 and 1999Q1, in order to distinguish the permanent structural break from temporary Markov-switching volatility. The novelty of this study lies in its insightful investigations into the recent U.S. housing boom and bust in the post-1999 period in four dimensions. First, the significantly negative volatility feedback effect in the housing market suggests a positive relationship between housing volatility and expected asset returns, and highly supports the important role of people’s expectations in the recent housing boom and bust. Second, the high-volatility regimes of the housing market delivered by this study indicate a strong association between housing cycles and business cycles, as well as a remarkable uncertainty in the U.S. housing market after the recession 2001. Third, the violated fundamental which refers to the broken negative relationship between housing volatility and realized asset returns during 2001–2004 implies the possible presence of a housing bubble during this period. Finally, volatility feedback anticipates the recent bubble-like housing market dynamics because high volatility during 2002–2003 implies low realized returns in the early housing-boom stage (2002–2003), as well as high expected returns in the second stage of the housing boom (2004–2005).     

Speculation or currency? Multi-scale analysis of cryptocurrencies—The case of Bitcoin

This paper proposes a novel two-stage VMD-based multi-scale regression to analyze various cryptocurrency attributes that are still unclear in the existing literature. In the first stage, Variational Mode Decomposition (VMD) is used to decompose the cryptocurrency prices into low, medium and high frequency modes with different attributes. In the second stage, the VMD-based multi-scale regression is proposed for these modes with selected explanatory variables. Using the proposed framework, we focus on analyzing the multiple attributes of daily Bitcoin price data as a case study. Empirical results indicate that the low-frequency mode has specific currency or long-term investment characteristics, unlike the short/medium-term investment attributes for the medium-frequency mode, while the high-frequency mode represents some speculation. Some events merely affect a single frequency mode, but others impact all frequency modes. The results of events analysis based on VMD could enhance the identification of the multiple attributes of Bitcoin. Our findings are insightful for future regulation and management of virtual currencies.     

Estimating the reaction of Bitcoin prices to the uncertainty of fiat currency

Recent studies have found that investors move from fiat currencies to Bitcoin cryptocurrency in environments with low trust and high uncertainty. This paper investigates the reaction of Bitcoin prices to uncertainty concerning fiat currencies by introducing a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)-based event analysis approach. The 2013 Cyprus bailout is used as an event over the uncertainty of fiat currencies. With the proposed approach, the original Bitcoin price series is decomposed into high-frequency, low-frequency, and trend components, thus disentangling the short-, medium-, and long-term effects of the events on Bitcoin prices, respectively. We find that the low-frequency component is dominant and increased because of the event. In addition, the announcement significantly increased the intensity of short-term fluctuations in Bitcoin prices. However, there was no structural change in Bitcoin prices in the long-term trend. This paper provides a way to show the reaction of Bitcoin prices to the uncertainty of fiat currencies at different time scales and suggests that the reaction is mainly captured by the medium-term trend.