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1.
European Journal of Finance ; 2023.
Article in English | Web of Science | ID: covidwho-20242863

ABSTRACT

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.

2.
Financ Innov ; 9(1): 80, 2023.
Article in English | MEDLINE | ID: covidwho-2294735

ABSTRACT

This study aims to examine the time-varying efficiency of the Turkish stock market's major stock index and eight sectoral indices, including the industrial, financial, service, information technology, basic metals, tourism, real estate investment, and chemical petrol plastic, during the COVID-19 outbreak and the global financial crisis (GFC) within the framework of the adaptive market hypothesis. This study employs multifractal detrended fluctuation analysis to illustrate these sectors' multifractality and short- and long-term dependence. The results show that all sectoral returns have greater persistence during the COVID-19 outbreak than during the GFC. Second, the real estate and information technology industries had the lowest levels of efficiency during the GFC and the COVID-19 outbreak. Lastly, the fat-tailed distribution has a greater effect on multifractality in these industries. Our results validate the conclusions of the adaptive market hypothesis, according to which arbitrage opportunities vary over time, and contribute to policy formulation for future outbreak-induced economic crises.

3.
International Journal of Energy Economics and Policy ; 13(2):272-283, 2023.
Article in English | ProQuest Central | ID: covidwho-2277166

ABSTRACT

This paper investigates the total and net directional connectedness of the energy market and currency market amid volatilities (local and international) of BRICS for the period May 7, 2012 to March 31, 2022. The Time-varying parameter Vector Autoregression (TVP-VAR) connectedness approach is specifically employed. We reveal that the average value of the total connectedness index (TCI) is 46.91%, for the specific network of energy commodities, currency rates, and volatilities. Also, from the averaged dynamic connectedness, the global energy commodity index demonstrated the most transmitter of shocks. Conversely, BRICS currency markets (except for Brazilian Rubble) and most implied energy volatilities and realised exchange rate volatilities were net receivers of shocks. Moreover, the total connectivity indices were seen to vary significantly during the study sample period with strong susceptibility to crisis periods, especially, the COVID-19 pandemic. We advocate that most volatilities were consistent net transmitters across time as indicated by the net directional connectedness. The findings imply that in a network of energy commodities, exchange rate, and volatilities, risk minimisation is elated to boost investors' confidence across time.

4.
Developments in Marketing Science: Proceedings of the Academy of Marketing Science ; : 211-212, 2023.
Article in English | Scopus | ID: covidwho-2271202

ABSTRACT

According to Day (2011), adaptive marketing capabilities (AMC) can make the adaptation of existing business models more effective, especially when firms are confronted to chaotic and nonlinear market changes. Evidence suggests that AMC enhance the business performance (Maryanti, 2019) the international performance (Reimann, 2021), the market performance of B2B firms (Guo et al., 2018), as well as the innovation performance (Ali, 2021;Shen, 2020). However, little is known about how AMC contribute to the proper adaptation of the business model components, particularly in a context of crisis. Our objective is therefore to test the potential contribution of AMC, as internal drivers of the Business Model Innovation process, in the specific context of the COVID-19 pandemic. Building upon the literature on AMC and BMI (Day, 2011;Foss & Saebi, 2018;Moorman & Day, 2016), we posit that Adaptive market experimentation capabilities (AMC) and Open marketing capabilities (OMC) (i) complement each other and (ii) contribute to the adaptive process by which SMEs succeed to properly align the three dimensions of their business model according to the new conditions (value proposition, value creation and value capture). From March to September 2021, in partnership with the economic department of Ville de Montréal, we collected 173 online self-administered questionnaires from Canadian SMEs, most of them (76%) having fewer than 20 employees. Measures were adapted from existing scales (Guo et al., 2018;Miroshnychenko et al., 2020;Spieth & Schneider, 2016) and we tested our model using a PLS-SEM approach. Our results confirm that the OMC (i) contribute to reinforce the AMC and (ii) significantly enhance the overall adaptation of the business model, but only through its value creation and value capture dimensions. On the contrary, the analysis shows that AMC do not seem to have a significant impact on the overall BM adaptation as they only enhance the value creation facet of the adaptive process. The potential contributions of these findings are of two folds. First, we shed lights on the potential contribution of two complementary adaptive marketing capabilities (AMC and OMC) in the process by which SMEs strive to adjust their business model in a context of economic crisis. Second, contrary to the initial premises made by Day (2011), results show that these two internal drivers do not contribute equally to this evolutionary process. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

5.
Global Finance Journal ; 2022.
Article in English | Scopus | ID: covidwho-2227989

ABSTRACT

This study examines whether the adaptive market hypothesis (AMH) explains calendar anomalies across 16 headline stock market indices in 10 markets. We employ the rolling window analysis and estimate a T-GARCH (1,1) for a long time series that includes two years coinciding with the COVID-19 pandemic. Overall, the empirical results reveal that calendar day anomalies across our sample markets exhibit time-varying behavior, evolving through patterns that shift markets between periods of efficiency and inefficiency, thereby providing support for the AMH framework. The results also highlight the calendar anomalies that reappeared after the onset of the COVID-19 pandemic across international markets. © 2022 Elsevier Inc.

6.
International Journal of Economics and Management ; 16(SpecialIssue1):59-80, 2022.
Article in English | Scopus | ID: covidwho-2206844

ABSTRACT

The study investigates the time-varying efficiency of the four most commonly traded international commodities from the U.S. Chicago Board of Options Exchange (CBOE) over a more extended period as well as during COVID-19. The study also explores how adaptive behavior of returns induces profitable opportunities in the commodity markets. Daily returns of commodity indices (gold, silver, oil, metal) are divided into subsamples of six years, to apply a battery of linear/nonlinear tests. The study uncovers the linear and nonlinear serial dependence in returns from commodities and finds evidence of time-varying volatility, thus consistent with the Adaptive Market Hypothesis over the full sample period. Moreover, returns from all the commodities are highly volatile and predictable during COVID-19. JEL Classification: G4, G41 © International Journal of Economics and Management. ISSN 1823-836X. e-ISSN 2600-9390.

7.
Cogent Economics & Finance ; 10(1), 2022.
Article in English | Web of Science | ID: covidwho-2017537

ABSTRACT

The specific properties of assets such as cryptocurrencies, gold, and stocks have welcomed more empirical studies in assessing their nexus. As a result, market conditions, whether good or bad, become imperative to assess the benefits of safe have, hedges or diversification. Also, the presence of uncertainties in markets may have asymmetrical effects which make it necessary to assess their impact over time. The emergence of COVID-19 pandemic as a global uncertainty has altered the dynamics of most financial markets. Consequently, this may influence the lead/lag relationships in most financial time series at various frequencies to contribute to the heterogeneous nature of market participants. Hence, the study examines the interdependencies between cryptocurrencies, selected stocks markets of Africa, and Gold returns in a time-frequency domain before and during the COVID-19 pandemic. Using a day-to-day observations, from August 8th, 2015 to May 5th, 2020, we assess the benefits of portfolio diversification, hedges, and safe haven with the bi-wavelet technique. The findings reveal that gold and cryptocurrencies provide a safe haven, diversification and, hedge for investors of African stock especially in the Ghanaian stock market (short-term) and also during this COVID-19 period. These findings contribute to the literature on financial market interdependencies, asymmetries to demonstrate financial market participants' diverse investment horizons. Again, policymakers and governments of these stock markets should institute a sound system of controls in regulating stock markets. This will enable the benefits of safe haven, hedges or diversification to be efficiently realized for Gold and Cryptocurrencies during different market conditions.

8.
Global Finance Journal ; : 100777, 2022.
Article in English | ScienceDirect | ID: covidwho-1996180

ABSTRACT

This study examines whether the adaptive market hypothesis (AMH) explains calendar anomalies across 16 headline stock market indices in 10 markets. We employ the rolling window analysis and estimate a T-GARCH (1,1) for a long time series that includes two years coinciding with the COVID-19 pandemic. Overall, the empirical results reveal that calendar day anomalies across our sample markets exhibit time-varying behavior, evolving through patterns that shift markets between periods of efficiency and inefficiency, thereby providing support for the AMH framework. The results also highlight the calendar anomalies that reappeared after the onset of the COVID-19 pandemic across international markets.

9.
Eurasian Economic Review ; : 14, 2022.
Article in English | Web of Science | ID: covidwho-1982412

ABSTRACT

This study proposes a new approach for testing for random walk behavior in daily Bitcoin returns (19/07/2010-03/03/2022) by contextualizing the Dickey-Fuller test in time-frequency space using continuous complex wavelet transforms. By splitting our full sample into smaller sub-sample periods segregated by Bitcoin halving dates, we find that Bitcoin returns are most predictable or least market efficient (i) at higher frequency or short-run cycles of between 2 and 16 days, (ii) between November-February months, (iii) during 'bubble' periods, (iv) across the consecutive halving dates, (v) during the 'Black Swan event' caused by financial market turmoil arising from the COVID-19 pandemic, and (vi) subsequent to the announcements of new COVID-19 variants. Altogether, our findings have important policy implications for different stakeholders in Bitcoin markets.

10.
Economic Change and Restructuring ; 55(3):1673-1699, 2022.
Article in English | ProQuest Central | ID: covidwho-1930464

ABSTRACT

This paper studies the information efficiency of BRICS currency markets during the COVID-19 pandemic using daily data spanning 3rd February 2020–31st August 2021. In our preliminary analysis, which consists of tests for random walk and martingale processes, we provide evidence of time-varying weak-form market efficiency in the currency markets. In our main empirical analysis, we use wavelet coherence tools to examine the time–frequency relationship between COVID-19 death rates and BRICS currency returns, and we find higher frequency components dominate periods of panic and financial turmoil. However, subsequent to government intervention in financial markets and the more recent rollout of mass vaccination programmes, we find that higher frequency oscillations disappear, and only very low-frequency co-movements remain. Important academic, market and policy implications derived from our study are discussed.

11.
Digital Signal Processing ; : 103619, 2022.
Article in English | ScienceDirect | ID: covidwho-1885723

ABSTRACT

This paper explores a time-varying version of weak-form market efficiency that is a key component of the so-called Adaptive Market Hypothesis (AMH). One of the most common methodologies used for modeling and estimating a degree of market efficiency lies in an analysis of the serial autocorrelation in observed return series. Under the AMH, a time-varying market efficiency level is modeled by time-varying autoregressive (AR) process and traditionally estimated by the Kalman filter (KF). Being a linear estimator, the KF is hardly capable to track the hidden nonlinear dynamics that is an essential feature of the models under investigation. The contribution of this paper is threefold. We first provide a brief overview of time-varying AR models and estimation methods utilized for testing a weak-form market efficiency in econometrics literature. Secondly, we propose novel accurate estimation approach for recovering the hidden process of evolving market efficiency level by the extended Kalman filter (EKF). Thirdly, our empirical study concerns an examination of the Standard and Poor's 500 Composite stock index and the Dow Jones Industrial Average index. Monthly data covers the period from November 1927 to June 2020, which includes the U.S. Great Depression, the 2008-2009 global financial crisis and the first wave of recent COVID-19 recession. The results reveal that the U.S. market was affected during all these periods, but generally remained weak-form efficient since the mid of 1946 as detected by the estimator.

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