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This paper investigates the dynamics and drivers of informational inefficiency in the Bitcoin futures market. To quantify the adaptive pattern of informational inefficiency, we leverage two groups of statistics which measure long memory and fractal dimension to construct a global-local market inefficiency index. Our findings validate the adaptive market hypothesis, and the global and local inefficiency exhibits different patterns and contributions. Regarding the driving factors of the time-varying inefficiency, our results suggest that trading activity of retailers (hedgers) increases (decreases) informational inefficiency. Compared to hedgers and retailers, the role played by speculators is more likely to be affected by the COVID-19 crisis. Extremely bullish and bearish investor sentiment has more significant impact on the local inefficiency. Arbitrage potential, funding liquidity, and the pandemic exert impacts on the global and local inefficiency differently. No significant evidence is found for market liquidity and policy uncertainty related to cryptocurrency.
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The purpose of this study was to identify and measure the impact of the different effects of entropy states over the high-frequency trade of the cryptocurrency market, especially in Bitcoin, using and selecting optimal parameters of the Bayesian approach, specifically through approximate Bayesian computation (ABC). ABC corresponds to a class of computational methods rooted in Bayesian statistics that could be used to estimate the posterior distributions of model parameters. For this research, ABC was applied to estimate the daily prices of the Bitcoin cryptocurrency from May 2013 to December 2021. The findings suggest that the behaviour of the parameters for our tested trading algorithms, in which sudden jumps are observed, can be interpreted as changes in states of the generated time series. Additionally, it is possible to identify and model the effects of the COVID-19 pandemic on the series analysed in the research. Finally, the main contribution of this research is that we have characterised the relationship between entropy and the evolution of parameters defining the optimal selection of trading algorithms in the financial industry. [ FROM AUTHOR] Copyright of Mathematics (2227-7390) is the property of MDPI and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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We examine the impact of the Bank of Japan's exchange traded fund (ETF) purchases on two aspects of market efficiency—long-range dependence and price delay—of the TOPIX and Nikkei 225 indices. An increase in ETF purchases results in lower long-range dependence for both indices while the impact on the price delay varies according to index and measure. A sub-period analysis shows that the impact on market efficiency varies over time, with the dominant pattern being a delayed harmful effect, followed by a positive impact and thereafter a negative effect. The implications of these findings are discussed.
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Several recent studies suggest that the home advantage, that is, the benefit competitors accrue from performing in familiar surroundings, was-at least temporarily-reduced in games played without spectators due to the COVID-19 Pandemic. These games played without fans during the Pandemic have been dubbed 'ghost games'. However, the majority of the research to date focus on soccer and no contributions have been provided for indoor sports, where the effect of the support of the fans might have a stronger impact than in outdoor arenas. In this paper, we try to fill this gap by investigating the effect of ghost games in basketball with a special focus on the possible reduction of the home advantage due to the absence of spectators inside the arena. In particular, we test (i) for the reduction of the home advantage in basketball, (ii) whether such reduction tends to disappear over time, (iii) if the bookmakers promptly adapt to such structural change or whether mispricing was created on the betting market. The results from a large data set covering all seasons since 2004 for the ten most popular and followed basketball leagues in Europe show, on the one hand, an overall significant reduction of the home advantage of around 5% and no evidence that suggests that this effect has been reduced at as teams became more accustomed to playing without fans; on the other hand, bookmakers appear to have anticipated such effect and priced home win in basketball matches accordingly, thus avoiding creating mispricing on betting markets.
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Climate change, the scarcity of fossil fuels, advances in clean energy, and volatility of crude oil prices have led to the recognition of clean energy as a viable alternative to dirty energy. This paper investigates the multifractal scaling behavior and efficiency of green finance markets, as well as traditional markets such as gold, crude oil, and natural gas between 1 January 2018, and 9 March 2023. To test the serial dependency (autocorrelation) and the efficient market hypothesis, in its weak form, we employed the Lo and Mackinlay test and the DFA method. The empirical findings showed that returns data series exhibit signs of (in)efficiency. Additionally, there is a negative autocorrelation among the crude oil market, the Clean Energy Fuels Index, the Global Clean Energy Index, the gold market, and the natural gas market. Arbitration strategies can be used to obtain abnormal returns, but caution should be exercised as prices may increase above their actual market value and reduce the profitability of trading. This work contributes to the body of knowledge on sustainable finance by teaching investors how to use predictive strategies on the future values of their investments.
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As a precious metal and investment commodity, gold has been signified to be important for risk management, diversification, and hedging. The gold market has undergone considerable structural changes in the facet of the pandemic and other geopolitical developments, attracting the interest of investors. Thus, it is crucial to look into how these structural changes affect the efficiency of the market. Accordingly, the study examines and compares the evolution of the gold market efficiency in three major economies from January 1, 2018, to August 31, 2022: India, USA, and Brazil. For this, we first decompose the time series using Loess Smoother's Seasonal and Trend Decomposition and then employ a multifractal detrended fluctuation analysis approach. The estimates are strengthened by the alternative approach of the rolling window method of wild bootstrap automatic variance ratio. The findings indicate a considerable decline in the efficiency of the gold returns across three economies, with the highest decline in India, followed by USA and Brazil. Notably, during covid and post covid periods, India and USA show persistence in small fluctuations, while Brazil displays persistent behavior in large fluctuations. Thereby, the market panic makes the gold market unstable, and its use as a safe haven is "erratic”. © 2023 Elsevier Ltd
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Purpose: This study aims to investigate the dependence structure and volatility spillovers among two strategic commodities (crude oil and gold) and a set of Islamic and conventional regional stock market indices, while examining the Ramadan effect Design/methodology/approach: The empirical strategy consists of two complementary measures of dependence and connectedness. This study first uses copulas to examine the dependency between the markets considered, then spillovers compute the magnitude of the connectedness among them. Findings: The copulas analysis shows that Frank's copula appears to better capture the relationship between most asset returns and highlights the almost absence of extreme dependence and, therefore, the existence of diversification opportunities. Moreover, the connectedness analysis suggests that gold is a net volatility receiver and provides, thereby, greater diversification benefits compared to crude oil. In addition, the high levels of time-varying connectedness support strong integration among the financial markets studied, specifically during the COVID-19 crisis period. Furthermore, the connectedness among the markets studied increases during the Ramdan subperiods, supporting shift contagion among financial markets considered during this religious holiday. Practical implications: The results provide investors with a better understanding of the nature as well as the magnitude of the interdependences between commodity markets and a set of Islamic and conventional regional stock markets. Indeed, it is of paramount importance for investors to clearly understand how Islamic and conventional markets are segmented or integrated during stress and stress-free periods, as well as the effect of the month of Ramadan on the interdependence among markets, to better assess risks, diversify portfolios and implement more effective hedging strategies. Originality/value: While a considerable body of literature examines financial contagion and volatility transmission between financial markets, there is still much to be said regarding connectedness among commodity and stock markets, particularly when it comes to studying the effects of religious holidays on the interaction between conventional and Islamic assets. This paper fills in this gap by focusing on the dependence structure as well as the connectedness between Islamic stock indices, conventional stock indices, gold and crude oil for six different regions, while examining the Ramadan effect. © 2023, Emerald Publishing Limited.
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The Turn of the month (ToM) effect is a calendar anomaly when the majority of returns of an asset are con-centrated into several days around the end of the old month and the start of the new one. Until now, the investigation of the ToM effect has mainly been focused on the stock markets. However, this paper investigates the presence of the ToM effect in eight key agricultural commodity markets (cocoa, coffee, corn, cotton, rice, soybean, sugar, wheat), using three different alternatives of the ToM window, during the 2001–2021 time period. The results show a statistically significant ToM effect in the rice, coffee, and sugar markets. Further results show that the ToM pattern changed during the COVID-19 pandemic, and that, in the case of commodities with a statistically significant ToM effect, the ToM effect can be efficiently used to beat the buy & hold investment strategy convincingly. © The authors.
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Empirical finance is about building an understanding of security prices and financial markets so as to foster better decision making while avoiding anecdote biases. Successful investors are often cognisant of their risk exposures coupled with extreme discipline and leverage. Therefore, the aim of this study was to explore the concept of joint market hypothesis in five international stock indexes. This study used the Taleb's ratio which is an extension of the Parkinson model. The financial distress periods were the financial crisis (December 1, 2007 to June 30, 2009) and the Covid-19 pandemic (January 1, 2020 to December 31, 2021). Joint hypothesis was evident in the JSE, CAC 40, the DAX and the Nikkei 225 while the Nasdaq displayed high levels of market efficiencies. Allocating more capital to the JSE, CAC 40, the DAX and the Nikkei 225 during periods of financial distress in conjunction with the Fama French five factor model will generate higher returns. As per the author's knowledge, this study is the first to explore the concept of joint market hypothesis during periods of distress
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Purpose: This study aims at testing efficiency of the Egyptian stock market at semi-strong level through exploring the impact of the COVID-19 outbreak on Egyptian stock returns. Design/methodology/approach: The author applied the "Event Study” method that addresses the impact of a particular event or group of events on stock returns, from 12 September 2019 to 5 April 2020, choosing Egyptian Stock Exchange (EGX) 100 companies which constitute constitutes the highest-level 100 companies in terms of liquidity and activity. Findings: The study found inefficiency of the Egyptian stock market at the semistrong level, as the declaration of the COVID-19 has a negative insignificant effect on stock returns, whether on the day of the declaration, before or after it, The underlying reasons for these results can be referred to the idea that can be explained that investors are noise trading when making their investment decisions. Research limitations/implications: There are two limitations to the interface of this paper. The first one is the short-term impact of COVID-19, using 141 days, and then it is not clear in the research the long-term impact of events related to the epidemic. Secondly, because the author deals with a short period term, the author does not test the characteristics of the company or any other major events that may affect the stock returns of the companies under study. Originality/value: This adds to the finance literature on the impact of the COVID-19 announcement on stock returns in the context of African countries. The explanation of the interconnection of the COVID-19 announcement on stock returns in Egypt. © 2023, Emerald Publishing Limited.
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We find evidence that markets anticipate the potential loss of firm value in the event of the CEO falling sick and eventually dying of COVID-19 in a sample of almost 3000 listed firms from across 137 regions in 10 European countries. First, we use soccer games as "super-spreader"events. The instrumented number of infected cases per capita in the region where company headquarters are located predicts a significant drop in stock returns during March and April 2020 for firms managed by CEOs with a higher probability of dying from COVID-19. Second, we show that the stock price of these firms increases significantly the day on which positive news on the development of COVID-19 vaccines are released in the market. © 2022 World Scientific Publishing Company. Midwest Finance Association.
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This study investigates the U.S. stock market efficiency from the symmetric and asymmetric perspectives during the COVID-19 pandemic. We explore that the pandemic boosts (hurts) the information role of symmetrically (asymmetrically) informed trading. Specifically, we find that the epidemic outbreak and infection scale strengthen (weaken) the stock return reaction to symmetrically (asymmetrically) informed trading. Evidence also indicates that the effect of symmetrically (asymmetrically) informed trading on stocks' permanent price shocks and price informational efficiency is enhanced (impaired) during the pandemic. Moreover, all these effects are consistently more intensive to informed buys.
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The study investigated performance of the stock market, foreign exchange market and the cryptocurrencies market as a result of COVID-19 outbreak. Event studies methodology was employed to determine the abnormal return (AR) and corresponding cumulative abnormal return (CAR) following the first confirmed case of the pandemic and the first recorded case of fatality, after controlling for the concurrent effect of crude price fluctuations. Consistent with previous studies, the paper documented evidence of negative reaction of –0.34% and –1.01% for the Nigerian stock market and the cryptocurrency market respectively at the announcement of first case of the pandemic's outbreak. The study also documented negative and statistically significant effects of –1.71% and –0.78% for Nigerian stock market and the cryptocurrency market respectively when the first case of death was announced. Adverse effect of the pandemic was found to be stronger when the first case of death was announced compared to first reported case of the outbreak. However, negative but insignificant effect was recorded for the foreign exchange market. The paper concluded that negative reaction for the stock market is consistent with market panic and policy uncertainty during the pandemic. Furthermore, adverse effect of the pandemic on the cryptocurrency market was due to increased co-movement of the market with regulated financial markets such as the stock market as well as correlation of returns between the markets. Copyright © 2023 Inderscience Enterprises Ltd.
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This study analyzes the efficiency of the crude palm oil (CPO) futures market by conducting a variance ratio test and comparing it to the West Texas Intermediate (WTI) futures market. We discover that the weak-form efficient market hypothesis holds for both the CPO and WTI futures markets despite the significant difference in their liquidity. Using a scaling exponent, we investigate speculative trading activities and find that trading CPO futures in expectation of significant returns does not strongly involve a high level of risk unlike WTI futures. Our findings regarding market efficiency of the two futures markets are supported by the significant integration of the two with similar level of information flow from each market to the other. To explore the role of speculation in their market integration, we introduce a natural experimental setting using the coronavirus disease 2019 (COVID-19) pandemic, which caused a sudden decrease in the demand for fuel. The bidirectional information flow between the two markets is intensified after the COVID-19 pandemic due to lower level of speculation. The findings suggest that (i) stakeholders in the CPO market need to pay attention to the crude oil markets to anticipate its price changes, (ii) investors can use WTI futures as a hedging tool against CPO futures as long as there is mutual information flow, and (iii) regulators should carefully implement new CPO futures market policy, as either asymmetric changes in speculation or unbalanced regulation with the WTI futures market can create market distortion and regulatory arbitrage. © 2022 The Authors
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Heterogeneity in informational inefficiency in a cross-market virtual currency, such as Bitcoin, allows for the extraction of differential gains from a portfolio of investments over time. In this paper, we measure inefficiency in five country/region segmented Bitcoin markets based on dynamic estimation of the fractional integration order of their price series. Results reveal a time-varying and country-specific pattern of inefficiency in the five Bitcoin markets, although the degree of inefficiency in each market has declined over time. Further, we introduce a new decomposition method to disentangle components of the inefficiency degree. Results suggest that the total variation around the convergence benchmark has fallen, whilst the proportion due to the difference between convergence and efficiency has risen from approximately 77% in 2013 to almost 100% in 2020. Besides, evidence of convergence emerges until the outbreak of COVID-19, beyond which the inefficiency degree diverges measurably. We show that Bitcoin markets have become more efficient after the first-wave COVID era and then the nature of market segmentation has played a less important role, levelling the cross-market difference and thus reducing the potential for arbitrage. © 2023 Elsevier B.V.
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This paper investigates the impact of COVID-19 on financial markets. It focuses on the evolution of the market efficiency, using two efficiency indicators: the Hurst exponent and the memory parameter of a fractional Lévy-stable motion. The second approach combines, in the same model of dynamic, an alpha-stable distribution and a dependence structure between price returns. We provide a dynamic estimation method for the two efficiency indicators. This method introduces a free parameter, the discount factor, which we select so as to get the best alpha-stable density forecasts for observed price returns. The application to stock indices during the COVID-19 crisis shows a strong loss of efficiency for US indices. On the opposite, Asian and Australian indices seem less affected and the inefficiency of these markets during the COVID-19 crisis is even questionable. © 2022 Elsevier B.V.
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We examine the impact of the COVID-19 pandemic on the credit risk of companies around the world. We find that increased infection rates affect firms more adversely as reflected by the wider increase in their credit default swap (CDS) spreads if they are larger, more leveraged, closer to default, have poorer governance and more limited stakeholder engagement, and operate in more highly exposed industries. We observe that country-level determinants like GDP, political stability, foreign direct investment, and commitment to crisis management (income support, health and lockdown policies) also affect the sensitivity of CDS spreads to COVID-19 infection rates. A negative amplification effect exists for firms with high default probability in countries with fiscal constraints. A direct comparison between global CDS and stock markets reveals that the CDS market prices in a distinct set of corporate traits and government policies in pandemic times.
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There has been a tremendous growth in cryptocurrencies, which has challenged policy makers around the globe. We obtain millisecond data of some of the most frequently traded cryptocurrencies - bitcoin, ethereum, ripple, litecoin and dash - and two cryptocurrency indices - CRIX and CCI30 - to examine their profitability. Our profitability findings suggest that cryptocurrency traders generate significant profits after considering reasonable transaction costs. We also observe that cryptocurrency market participants can expand and sustain the levels of profitability levels in the subsequent trading activity. Our robustness checks with more recent post-Covid data are consistent with the initial profitability findings, although we observe lower levels of profits for the two indices and weaker profit persistency for all digital assets.
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Heterogeneity in informational inefficiency in a cross-market virtual currency, such as Bitcoin, allows for the extraction of differential gains from a portfolio of investments over time. In this paper, we measure inefficiency in five country/region segmented Bitcoin markets based on dynamic estimation of the fractional integration order of their price series. Results reveal a time-varying and country-specific pattern of inefficiency in the five Bitcoin markets, although the degree of inefficiency in each market has declined over time. Further, we introduce a new decomposition method to disentangle components of the inefficiency degree. Results suggest that the total variation around the convergence benchmark has fallen, whilst the proportion due to the difference between convergence and efficiency has risen from approximately 77% in 2013 to almost 100% in 2020. Besides, evidence of convergence emerges until the outbreak of COVID-19, beyond which the inefficiency degree diverges measurably. We show that Bitcoin markets have become more efficient after the first-wave COVID era and then the nature of market segmentation has played a less important role, levelling the cross-market difference and thus reducing the potential for arbitrage.
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This study empirically analysed the stock price reaction and the efficiency of Indian stock market of the Nifty 50 index around the budget announcements during covid periods from 2020 to 2022 by applying event study methodology. The market efficiency was tested by employing 61 days event study window including 30 days before and 30 days after the announcement date, and the event date of the budget, while the estimation window period comprises of 120 days of the pre-event period. The market model is employed to demonstrate abnormal returns near the event date and to assist in estimating expected returns. Abnormal returns, Average abnormal returns, Cumulative average abnormal returns, and ttests were applied for analysing the market efficiency on Indian budget announcements. This research paper reveals that the efficiency level of the Indian stock market is high and the investors can not make an abnormal profit over the budget announcements during Covid periods. © 2022, Remittances Review. All Rights Reserved.