IDEAS home Printed from https://ideas.repec.org/a/rfh/bbejor/v13y2024i2p436-447.html
   My bibliography  Save this article

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

Author

Listed:
  • Abdul Karim

    (PhD Scholar, Institute of Business Administration, Khwaja Fareed University of Engineering and Information Technology, Pakistan)

  • Abdul Rasheed

    (Assistant Professor, Institute of Business Administration, Khwaja Fareed University of Engineering and Information Technology, Pakistan)

Abstract

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.

Suggested Citation

  • Abdul Karim & Abdul Rasheed, 2024. "Forecasting Modeling of Day of the Week Calendar Anomalies in Pakistan Stock Exchange: An Artificial Intelligence Perspective," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 13(2), pages 436-447.
    • Handle: RePEc:rfh:bbejor:v:13:y:2024:i:2:p:436-447
    DOI: https://doi.org/10.61506/01.00351
    as

    Download full text from publisher

    File URL: https://bbejournal.com/BBE/article/view/861/856
    Download Restriction: no
    File URL: https://bbejournal.com/BBE/article/view/861
    Download Restriction: no
    File URL: https://libkey.io/https://doi.org/10.61506/01.00351?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sadia Anjum, 2020. "Impact of market anomalies on stock exchange: a comparative study of KSE and PSX," Future Business Journal, Springer, vol. 6(1), pages 1-11, December.
    2. John Fender, 2020. "Beyond the efficient markets hypothesis: Towards a new paradigm," Bulletin of Economic Research, Wiley Blackwell, vol. 72(3), pages 333-351, July.
    3. Mumtaz Hussain & Salma Sadiq & Muhammad Haroon Rasheed & Khurram Amin, 2022. "Exploring the Dynamics of Investors’ Decision Making in Pakistan Stock Market: A Study of Herding Behavior," Journal of Economic Impact, Science Impact Publishers, vol. 4(1), pages 165-173.
    4. Vilija Aleknevičienė & Vaida Klasauskaitė & Eglė Aleknevičiūtė, 2022. "Behavior of calendar anomalies and the adaptive market hypothesis: evidence from the Baltic stock markets," Journal of Baltic Studies, Taylor & Francis Journals, vol. 53(2), pages 187-210, April.
    5. Sidra Riaz & Yusen Xu & Shahid Hussain, 2019. "Workplace Ostracism and Knowledge Hiding: The Mediating Role of Job Tension," Sustainability, MDPI, vol. 11(20), pages 1-16, October.
    6. Bahrawar Said & Shafiq Ur Rehman & Rizwan Ullah & Javed Khan & David McMillan, 2021. "Investor overreaction and global financial crisis: A case of Pakistan stock exchange," Cogent Economics & Finance, Taylor & Francis Journals, vol. 9(1), pages 1966195-196, January.
    7. Sakhr Miss & Michel Charifzadeh & Tim A. Herberger, 2020. "Revisiting the monday effect: a replication study for the German stock market," Management Review Quarterly, Springer, vol. 70(2), pages 257-273, May.
    8. El Mehdi Ferrouhi & Omar Kharbouch & Samir Aguenaou & Muhammad Naeem & David McMillan, 2021. "Calendar anomalies in African stock markets," Cogent Economics & Finance, Taylor & Francis Journals, vol. 9(1), pages 1978639-197, January.
    9. Khushboo Aggarwal & Mithilesh Kumar Jha, 2023. "Stock returns seasonality in emerging asian markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 30(1), pages 109-130, March.
    10. Badal Khan & Muhammad Aqil & Syed Hasnain Alam Kazmi & Syed Imran Zaman, 2023. "Day‐of‐the‐week effect and market liquidity: A comparative study from emerging stock markets of Asia†," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 544-561, January.
    11. Wen, Fenghua & Xu, Longhao & Ouyang, Guangda & Kou, Gang, 2019. "Retail investor attention and stock price crash risk: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 65(C).
    12. Bengü Yardımcı & Sabri Erdem, 2020. "The day of the week effects in stock markets of countries with predominantly Muslim populations," International Journal of Islamic and Middle Eastern Finance and Management, Emerald Group Publishing Limited, vol. 13(2), pages 195-218, February.
    13. Muhammad Sarmad Irtiza & Shahbaz Khan & Nida Baig & Syed Muhammad Ali Tirmizi & Ilyas Ahmad, 2021. "The turn-of-the-month effect in Pakistani stock market," Future Business Journal, Springer, vol. 7(1), pages 1-11, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Naz Farah & Lutfullah Tooba & Zahra Kanwal, 2024. "COVID-19 and Seasonality in Monthly Returns: a Firm Level Analysis of PSX," Zagreb International Review of Economics and Business, Sciendo, vol. 27(1), pages 201-230.
    2. Leonard Grebe & Dirk Schiereck, 2024. "Day-of-the-week effect: a meta-analysis," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 14(4), pages 1057-1094, December.
    3. Badal Khan & Muhammad Aqil & Syed Hasnain Alam Kazmi & Syed Imran Zaman, 2023. "Day‐of‐the‐week effect and market liquidity: A comparative study from emerging stock markets of Asia†," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 544-561, January.
    4. Aaryan Gupta & Vinya Dengre & Hamza Abubakar Kheruwala & Manan Shah, 2020. "Comprehensive review of text-mining applications in finance," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-25, December.
    5. Roman Mestre, 2021. "A wavelet approach of investing behaviors and their effects on risk exposures," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-37, December.
    6. Keming Li, 2021. "The effect of option trading," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-32, December.
    7. Zhang, Hua & Chen, Jinyu & Shao, Liuguo, 2021. "Dynamic spillovers between energy and stock markets and their implications in the context of COVID-19," International Review of Financial Analysis, Elsevier, vol. 77(C).
    8. François-Éric Racicot & Raymond Théoret, 2022. "Tracking market and non-traditional sources of risks in procyclical and countercyclical hedge fund strategies under extreme scenarios: a nonlinear VAR approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-56, December.
    9. Ning Ding & Kalimullah Bhat & Khalil Jebran, 2020. "Debt choice, growth opportunities and corporate investment: evidence from China," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    10. Yueyang Zhao & Jinzhou Mao, 2023. "Mixed ownership reforms and the transparency of nonstate‐owned enterprises: Evidence from China," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(1), pages 271-284, January.
    11. Fenghua Wen & Yujie Yuan & Wei‐Xing Zhou, 2021. "Cross‐shareholding networks and stock price synchronicity: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(1), pages 914-948, January.
    12. Geng, Yuedan & Ye, Qiang & Jin, Yu & Shi, Wen, 2022. "Crowd wisdom and internet searches: What happens when investors search for stocks?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    13. Yu, Haixu & Liang, Chuanyu & Liu, Zhaohua & Wang, He, 2023. "News-based ESG sentiment and stock price crash risk," International Review of Financial Analysis, Elsevier, vol. 88(C).
    14. Narasingha Das & Partha Gangopadhyay, 2023. "Did weekly economic index and volatility index impact US food sales during the first year of the pandemic?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    15. Hardeep Singh Mundi, 2023. "Risk neutral variances to compute expected returns using data from S&P BSE 100 firms—a replication study," Management Review Quarterly, Springer, vol. 73(1), pages 215-230, February.
    16. Peng-Fei Dai & Xiong Xiong & Zhifeng Liu & Toan Luu Duc Huynh & Jianjun Sun, 2021. "Preventing crash in stock market: The role of economic policy uncertainty during COVID-19," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-15, December.
    17. He, Feng & Yan, Yulin & Hao, Jing & Wu, Ji (George), 2022. "Retail investor attention and corporate green innovation: Evidence from China," Energy Economics, Elsevier, vol. 115(C).
    18. Hong, Ziyang & Liu, Qingfu & Tse, Yiuman & Wang, Zilu, 2023. "Black mouth, investor attention, and stock return," International Review of Financial Analysis, Elsevier, vol. 90(C).
    19. Zhang, Lipai & Li, Biao, 2022. "Mutual supervision or conspiracy? The incentive effect of multiple large shareholders on audit quality requirements," International Review of Financial Analysis, Elsevier, vol. 83(C).
    20. Tahira Alam & Zia Ullah & Fatima Saleh AlDhaen & Esra AlDhaen & Naveed Ahmad & Miklas Scholz, 2021. "Towards Explaining Knowledge Hiding through Relationship Conflict, Frustration, and Irritability: The Case of Public Sector Teaching Hospitals," Sustainability, MDPI, vol. 13(22), pages 1-15, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rfh:bbejor:v:13:y:2024:i:2:p:436-447. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Muhammad Irfan Chani (email available below). General contact details of provider: https://edirc.repec.org/data/rffhlpk.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.