Testing Weak Form of Efficient Market Hypothesis Before and During COVID-19 Pandemic Periods: Evidence From Indonesia

Faisal, Faisal; Majid, M. Shabri Abd.; Rakhmawati, Lenny

doi:10.1109/sibf56821.2022.9940133

Cited by 3 publications

(4 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Applying the Efficient Market Hypothesis (EMH) in this prediction study aligns with other findings that have indicated that predictions can be made if the market index has a market efficiency status that matches EMH. Several previous studies (Faisal et al, 2022;Hadianto et al, 2021;Jawadi et al, 2015;Kasidi & Banafa, 2022;Rodoni et al, 2022;Rossi & Gunardi, 2018;Santoso & Ikhsan, 2020) have also supported the idea that the possibility of accurate prediction can be obtained from an efficient market according to EMH. One of the implications of EMH is that if the market has been efficient, then all relevant information has already been reflected in the stock price, thus making price predictions more reliable.…”

Section: Discussionmentioning

confidence: 62%

“…In other words, investors can obtain unusual returns in an efficient market in any form when there is an anomaly (Elango & Macki, 2008;Kasidi & Banafa, 2022;Surachmadi et al, 2021). Rodoni & Yong (2002) stated that market anomalies were primarily found in market efficiency forms of weak/weak forms (prices in the past cannot be used to predict current or future prices) and semi-strong forms (Agustin, 2019;Elangovan et al, 2022;Faisal et al, 2022;Khan et al, 2021). At least four types of anomalies occur in the market: corporate, event, seasonal, and accounting (Barberis et al, 2021;Elango & Macki, 2008;Keloharju et al, 2014;Koesoemasari et al, 2018;Ain et al, 2021).…”

Section: Literature Review Efficient Market Hypothesismentioning

confidence: 99%

See 1 more Smart Citation

Predicting Shariah Stock Market Indices with Machine Learning: A Cross-Country Case Study

Khairunnisa,

Rodoni,

Rama

2024

JESTT

View full text Add to dashboard Cite

Stock prices are influenced by numerous factors, including policy adjustments, economic conditions, and international developments. Consequently, forecasting stock price trends accurately has posed a significant challenge for economists to study. The Islamic financial industry experiences fewer shocks compared to the traditional financial sector, allowing investors to anticipate the performance of Islamic indices. This study aims to predict the Islamic stock market indices in six countries, including Indonesia, Thailand, Malaysia, Pakistan, the United Arab Emirates, and Qatar, using the Autoregressive Integrated Moving Average (ARIMA) model. Monthly data from 2013 to 2023 sourced from investing.com and Yahoo Finance are analyzed using R machine learning. The objective of this study is to provide accurate predictions for the next 25 months and offer insights into potential price movements. Overall, this research also sheds light on the dynamics of the Islamic market in Indonesia, Thailand, Malaysia, Pakistan, the United Arab Emirates, and Qatar, which adhere to the Efficient Market Hypothesis (EMH) due to the predictability of index prices by historical data. Keywords: forecating, R-Studio, ARIMA, Islamic Stock Market, Machine Learning, R-Programming ABSTRAK Harga saham dipengaruhi oleh banyak faktor, termasuk penyesuaian kebijakan, kondisi ekonomi, dan perkembangan internasional. Oleh karena itu, memprediksi tren harga saham dengan akurat telah menjadi tantangan signifikan bagi para ekonom untuk mempelajarinya. Industri keuangan Islam mengalami lebih sedikit goncangan dibandingkan dengan sektor keuangan tradisional, yang memungkinkan investor untuk memperkirakan kinerja indeks Islam. Studi ini bertujuan untuk memprediksi indeks pasar saham Islam di enam negara, termasuk Indonesia, Thailand, Malaysia, Pakistan, Uni Emirat Arab, dan Qatar, menggunakan model Autoregressive Integrated Moving Average (ARIMA). Data bulanan dari tahun 2013 hingga 2023 yang berasal dari investing.com dan Yahoo Finance dianalisis menggunakan pembelajaran mesin R. Tujuan dari studi ini adalah untuk memberikan prediksi yang akurat untuk 25 bulan mendatang dan menawarkan wawasan tentang pergerakan harga yang potensial. Secara keseluruhan, penelitian ini juga memberikan cahaya tentang dinamika pasar Islam di Indonesia, Thailand, Malaysia, Pakistan, Uni Emirat Arab, dan Qatar, yang mengikuti Hipotesis Pasar Efisien (EMH) karena dapat diprediksi oleh data historis.. Kata Kunci: Prediksi, R-Studio, ARIMA, Indeks Pasar Modal Syariah, Machine Learning, R-Programming

show abstract

Section: Discussionmentioning

confidence: 62%

Section: Literature Review Efficient Market Hypothesismentioning

confidence: 99%

Predicting Shariah Stock Market Indices with Machine Learning: A Cross-Country Case Study

Khairunnisa,

Rodoni,

Rama

2024

JESTT

View full text Add to dashboard Cite

show abstract

“…The study focuses on efficiency in weak form, which assumes that all historical prices are already included in current stock prices (Zebende et al, 2022), meaning it is nearly impossible to use historical information alone to outperform the market consistently. The debate on market efficiency continues; understanding the weak form is essential for investors seeking to navigate the complexities of the stock market (Faisal et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Mixed results were found in the literature on the stock price movement to accept the market efficiency hypothesis (Nurunnabi, 2012;Karasinski, 2020;Faisal et al, 2022). Some studies found that stock prices do not follow a random walk (Hawaldar et al, This Journal is licensed under a Creative Commons Attribution 4.0 International License 2017; Ahmed and Hossain, 2019;Houfi, 2019;Al-Faryan and Docker, 2021;Dias et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Regional Stock Market Efficiency at Weak Form after the Covid-19 Vaccination Approval

Saleem,

Mustafa,

Asaad

et al. 2023

IJEFI

View full text Add to dashboard Cite

The contradiction in the previous results provides a deep avenue for researchers to take more interest in the stock market efficiency and conduct more studies. Therefore, the study objective is to decide whether the Arab Federation of Exchanges (S&P AFE 40 Index Return) is efficient at weak-form based on normality and random walk hypothesis using several statistics such as the Jarque-Bera test as a parametric technique to check the normality and the Augmented Dickey-Fuller test as a parametric method to test the random walk hypothesis. Moreover, the results are reinforced by six non-parametric techniques to test the normality hypothesis such as the Kolmogorov-Smirnov test, Shapiro-Wilk test, Lilliefors test, Cramer-von Mises test, Watson test, Anderson-Darling test, and four non-parametric techniques such as run test, variance ratio test, Phillips-Perron test, and autocorrelation test to check the random walk hypothesis for daily data after the Covid-19 vaccination program over the period from 31 March 2020 to 31 March 2023, the results of all tests indicated that the market index return is non-efficient at the weak form, and concluded that the investors could analyze the Arab Federation of Exchanges’ past stock prices or other historical data as opportunities to predict future stock prices and earn unusual profits; therefore, Policymakers may further improve access to information to prevent investors from having opportunities to predict stock movements to obtain abnormal returns.

show abstract

Testing the Impact of Covid-19 on Weak form Efficiency Hypothesis for Sharia-Compliant Indices and Stocks: Evidence from Bahrain

Al-Muharraqi,

Munir

2023

2023 International Conference on Sustainable Islamic Business and Finance (SIBF)

View full text Add to dashboard Cite

Testing Weak Form of Efficient Market Hypothesis Before and During COVID-19 Pandemic Periods: Evidence From Indonesia

Cited by 3 publications

References 9 publications

Predicting Shariah Stock Market Indices with Machine Learning: A Cross-Country Case Study

Predicting Shariah Stock Market Indices with Machine Learning: A Cross-Country Case Study

Regional Stock Market Efficiency at Weak Form after the Covid-19 Vaccination Approval

Testing the Impact of Covid-19 on Weak form Efficiency Hypothesis for Sharia-Compliant Indices and Stocks: Evidence from Bahrain

Contact Info

Product

Resources

About