Are there “day-of-the-week” and “holiday” anomalies in the mexican stock market?

Samaniego, Jesús Dacio Villarreal; Salgado, Roberto Joaquín Santillán; Pérez, Moreno

doi:10.22201/fca.24488410e.2022.2920

Cited by 3 publications

(1 citation statement)

References 49 publications

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“…Winkelried & Iberico (2018) found the DOW effect in five of the six Latin American stock markets they examined. Villarreal-Samaniego, Santillán-Salgado, & Lagunes-Pérez (2022) concluded that the DOW effect was consistently present in the Mexican stock market's returns and volatility.…”

Section: Introductionmentioning

confidence: 99%

The Day-of-the-Week Effect and the Adaptive Market Hypothesis in Latin American Stock Markets

Villarreal-Samaniego,

Santillán

2023

estud.gerenc.

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The objective of this work is to examine the Day-of-the-Week anomaly from the perspective of the Adaptive Markets Hypothesis for the stock market indices of Argentina, Brazil, Chile, Colombia, Mexico, and Peru in different subperiods and under different market conditions. The Autoregressive-Moving-Average, Generalized-Autoregressive-Conditional-Heteroskedasticity specifications, and the Kruskal-Wallis test used in the study reveal that the Day-of-the-Week effect appears and disappears in three of the indices and that its presence varies under different market conditions in all of them. This empirical evidence supports the Adaptive Markets Hypothesis.

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Section: Introductionmentioning

confidence: 99%

The Day-of-the-Week Effect and the Adaptive Market Hypothesis in Latin American Stock Markets

Villarreal-Samaniego,

Santillán

2023

estud.gerenc.

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Herding behavior in cryptocurrency market: evidence from COVID-19, Russia–Ukraine war, and Palestine–Israel conflict

Sharma,

Verma,

Al-Bukari

et al. 2024

Cogent Economics & Finance

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Forecasting Modeling of Day of the Week Calendar Anomalies in Pakistan Stock Exchange: An Artificial Intelligence Perspective

Karim,

Rasheed

2024

BBE

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Stock price forecasting provide valuable insight to the investor to facilitate well-informed investment decision making. The aim of this study is to examine the calendar anomalies i.e. DOW in Pakistan stock exchange though Artificial intelligence techniques. For this purpose, Support vector machine (SVM), Decision Tree (DT) and Artificial Neural Network is used to forecast the daily stock prices. The daily stock prices data of KSE100 index ranges from May,1994 to August 2023 is used as out variable while stock open, close, high and low prices are used as features/input variables. The training and testing ratio was 80:20 means 80% of the data was used in training and the 20% values were utilized for forecasting. To evaluate the accuracy of predictions, mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE)/mean absolute deviation (MAD), mean absolute percent error (MAPE), and R-squared (R^2) are taken as decision criteria. The daily forecasted stock prices show the almost zero error on Tuesday, Wednesday and Thursday in SVM. Decision tree show very low error in actual and forecasted stock prices. Therefore, it is concluded that, the DOW anomalies exist in KSE100 index of PSX. Results show that, SVM can better predict the stock prices than DT and ANN. These results conclude that the forecasted stock prices are much closer to actual daily stock price means the daily stock prices can be forecast in KSE100 index. These finding contradicts the Efficient market hypothesis and conclude that the Pakistan stock exchange (PSX) is weak-form inefficient market.

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Are there “day-of-the-week” and “holiday” anomalies in the mexican stock market?

Abstract: Are there "day-of-the-week" and "holiday" anomalies in the mexican stock market?¿Hay anomalías "día de la semana" y "día festivo" en el mercado accionario mexicano?

Cited by 3 publications

References 49 publications

The Day-of-the-Week Effect and the Adaptive Market Hypothesis in Latin American Stock Markets

The Day-of-the-Week Effect and the Adaptive Market Hypothesis in Latin American Stock Markets

Herding behavior in cryptocurrency market: evidence from COVID-19, Russia–Ukraine war, and Palestine–Israel conflict

Forecasting Modeling of Day of the Week Calendar Anomalies in Pakistan Stock Exchange: An Artificial Intelligence Perspective

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