The Monday effect in the EUR/USD currency pair: Periods of EUR strength and weakness

Bush, Peter J.; Stephens, John E.

doi:10.1016/j.jbef.2016.03.003

Cited by 4 publications

(1 citation statement)

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“…In a different note, Urquhart and McGroarty (2014) evaluated DJIA index returns and disclosed that the Monday effect is not static, and it changes with time. Bush and Stephens (2016) explored the Monday effect for the EUR/USD exchange rate and described that the Monday effect depends on the relative strength and weakness of the domestic currency. However, many other studies advocated that there is no presence of the Monday effect (Prokop, 2010; Hui et al , 2014; Xiong et al , 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Adaptive calendar effects and volume of extra returns in the cryptocurrency market

Khuntia

Pattanayak

2021

IJOEM

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PurposeThis study broadly attempts to explore adaptive or dynamics patterns of calendar effects existed in the cryptocurrency market as per the adaptive market hypothesis (AMH) framework. Another agendum of this study is to investigate the quantum of extra returns which may result from the presence of calendar effects.Design/methodology/approachThe present study considers both parametric and non-parametric approaches to verify calendar effects empirically. Specifically, this study has implemented Generalised Autoregressive Conditional Heteroscedasticity (1, 1) and Kruskal–Wallis tests in the rolling window approach to reveal adaptive patterns of calendar effects. Additionally, the present study has used the implied trading strategy to evaluate the volume of excess returns resulted from calendar effects than buy-and-hold (BH) strategy.FindingsThe overall results of the current study exhibit that calendar effect in the cryptocurrency market is dynamic rather than static which indicates the calendar effect is a time-varying phenomenon. Moreover, this study also confirmed that ITS is not suitable to obtain extra returns despite the existence of calendar effects.Research limitations/implicationsThe present study has covered some broad aspects of calendar anomalies in the cryptocurrency market, keeping aside certain other limitations which need to be addressed in the following dimensions. Future studies may aim at addressing issues like, Turn-of-the-Year effect, Halloween effect, weather effect, and Month-of-the-Year effects, and try to explore the reasons of presence of dynamic patterns of calendar effects.Practical implicationsThe significant implication of this study is that it alerts investors about market return predictability due to calendar patterns or effects in different periods. It also suggests the period in which the ITS can perform better than the BH strategy.Originality/valueIt is the first study in the cryptocurrency literature which has adopted the AMH framework to verify adaptive calendar effects or anomalies. Furthermore, this study, instead of a mere examination of the presence of calendar effects, has evaluated the potential of calendar effects to produce extra returns through trading strategies.

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Section: Literature Reviewmentioning

confidence: 99%

Adaptive calendar effects and volume of extra returns in the cryptocurrency market

Khuntia

Pattanayak

2021

IJOEM

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Calendar anomalies’ adaptiveness in exchange rates: evidence from the concordance coefficient and AR-GARCH tests

Villarreal-Samaniego

2024

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PurposeThis research aims to examine the time-varying behavior of the Weekend, Turn-of-the-Month, January, and Halloween effects in eight foreign exchange rates against the U.S. dollar from the Adaptive Market Hypothesis (AMH) perspective. It also explores whether these anomalies can generate excess returns compared to a buy-and-hold strategy.Design/methodology/approachUsing daily return data from January 2004 to December 2023 in a rolling-window framework, the study employs the Concordance Coefficient test and AR-GARCH models to assess the time-varying behavior of four calendar anomalies. It also assesses the statistical significance of the trading strategies implied by these anomalies using t-tests and applies F-tests for subperiod analysis.FindingsThe results reveal a generalized time-varying presence of calendar anomalies in emerging currencies and, to a lesser extent, developed currencies. However, the trading strategies implied by these anomalies generally did not show statistical significance, except for the Turn-of-the-Month effect, which exhibited statistically significant unprofitability.Originality/valueThe study pioneers an analysis of five calendar anomalies across various currencies from the standpoint of the AMH and proposes case-specific explanations for their occurrence. It also examines the potential for the anomalies’ implied trading strategies to generate excess returns compared to a straightforward buy-and-hold strategy. Additionally, the study introduces the recently developed Concordance Coefficient test as a valuable alternative to other non-parametric methods.

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Forecasting Volatility in the EUR/USD Exchange Rate Utilizing Fractional Autoregressive Models

Benzid,

Saâdaoui

2024

Fluct. Noise Lett.

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This study investigates the volatility of the Euro-to-US Dollar exchange rate, specifically focusing on identifying long-memory characteristics. Through the analysis of daily data spanning from January 1, 2018, to January 10, 2023, the study uncovers a robust long-memory feature. Supporting this exploration, the study endorses the use of sophisticated models such as Fractionally Integrated Generalized Autoregressive Conditionally Heteroskedastic (FIGARCH) and Hyperbolic Generalized Autoregressive Conditionally Heteroskedastic (HYGARCH), incorporating both student and skewed student innovation distributions. The results underscore the superior performance of FIGARCH and HYGARCH models, particularly when coupled with a skewed student distribution. This collaborative approach enhances the predictability of crucial financial metrics, including Value at Risk (VaR) and Expected Shortfall (ESF), for both long and short trading positions. Significantly, the FIGARCH model, when utilizing a skewed student distribution, demonstrates exceptional predictive power. This outcome challenges the efficient market hypothesis and suggests the potential for generating outstanding returns. In light of these findings, this research contributes valuable insights for comprehending and navigating the intricacies of the Euro-to-US Dollar exchange rate, providing a forward-looking perspective for financial practitioners and researchers alike.

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The Monday effect in the EUR/USD currency pair: Periods of EUR strength and weakness

Cited by 4 publications

References 11 publications

Adaptive calendar effects and volume of extra returns in the cryptocurrency market

Adaptive calendar effects and volume of extra returns in the cryptocurrency market

Calendar anomalies’ adaptiveness in exchange rates: evidence from the concordance coefficient and AR-GARCH tests

Forecasting Volatility in the EUR/USD Exchange Rate Utilizing Fractional Autoregressive Models

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