ARTICLE

TRACING STOCK RETURNS ON QUARTERLY BASIS THE CASE OF KSE 100 INDEX

  1. HOME
  2. ARTICLE

26 Pages : 466-476

http://dx.doi.org/10.31703/gssr.2018(III-III).26      10.31703/gssr.2018(III-III).26      Published : Sep 2018

Tracing Stock Returns on Quarterly Basis: The Case of KSE-100 Index

Abstract

    The stock market index can be forecasted in two ways --- either through taking those external factors that influence movements in the index or by basing ones predictions on the previous values of the index. The current study has used the method described later by employing the Box-Jenkins methodology --- a method famously used by most researchers while conducting ARIMA modeling--- by taking past figures of KSE 100 Index. Quarterly figures of the Index were, therefore, taken for 22 years from August 1995 to October 2017 that translated into 90 observations. Results revealed that the forecasting model used in the study did well in anticipating returns in the shortrun. The findings of the study can be consumed by investors, particularly short-term, in deciding when, and when not, to risk their hard-earned funds at Pakistan Stock Exchange.

    ARIMA, BoxJenkins Methodology, PSX 100 Index, Prediction, Stationarity

    (1) Mustafa Afeef
    Assistant Professor, Department of Management Sciences,Islamia College Peshawar, KP, Pakistan.
    (2) Nazim Ali
    Assistant Professor, Department of Management Studies, University of Malakand, KP, Pakistan.
    (3) Adnan Khan
    Lecturer, Department of Management Studies,University of Malakand, KP, Pakistan.
Fulltext PDF

References

  • Adebiyi, A., Adewumi, A., & Ayo, C. (2014, March). Stock Price Prediction Using the ARIMA Model. Paper presented at the 2014 UKSim-AMSS 16th International Conference on Computer Modeling and Simulation, Cambridge University, United Kingdom. Retrieved from http://ijssst.info/Vol-15/No-4/data/4923a105.pdf.
  • Asteriou, D., & Hall S. (2007). Applied Econometrics, Revised Edition. Palgrave Macmillan, New York, USA.
  • Banerjee, D. (2014). Forecasting of Indian stock market using the time-series ARIMA model. Paper presented at the 2nd International Conference on Business & Information Management (pp. 131-135). Durgapur, India. IEEE.
  • Box, G., & Jenkins, G. (1970). Time Series Analysis: Forecasting and Control. San Francisco: Holden-Day, California, USA
  • Chatfield, C. (1996). The Analysis of Time Series, 5th ed., Chapman & Hall, New York.
  • Contreras, J., Espinola, R., Nogales, F., & Conejo, A. (2003). ARIMA Models to Predict Nextday Electricity Prices. IEEE Transactions on Power Systems, 18(3), 1014- 1020.
  • Gilbert, K. (2005). An ARIMA Supply Chain Model, Management Science, 51(2), 305-310.
  • Guha, B., &Bandyopadhyay, G. (2016). Gold Price Forecasting using ARIMA Model. Journal of Advanced Management Science, 4(2), 117-121.
  • Gujarati, D., & Porter, D. (2004). Basic Econometrics, Fourth Edition, McGraw-Hill, New York, USA.
  • Hamjah, M. (2014). Rice Production Forecasting in Bangladesh: An Application of Box-Jenkins ARIMA Model. Mathematical Theory and Modeling, 4(4), 1-11.
  • Jadhav, V., Reddy, B., & Gaddi, G. (2017). Application of ARIMA Model for Forecasting Agricultural Prices. Journal of Agricultural Science and Technology, 19(5), 981-992.
  • Manoj, K., & Madhu, A. (2014). An Application of Time Series ARIMA Forecasting Model for Predicting Sugarcane Production in India. Studies in Business and Economics, 9(1), 81-94.
  • Meyler, A., Kenny, G., & Quinn, T. (1998). Forecasting Irish inflation using ARIMA models. Central Bank and Financial Services Authority of Ireland Technical Paper Series, 1998(3), 1-48.
  • Mondal, P., Shit, L., & Goswami, S. (2014). Study of Effectiveness of Time Series Modeling (ARIMA) in Forecasting Stock Prices. International Journal of Computer Science, Engineering and Applications, 4(2), 13- 29.
  • Padhan, P. (2012). Application of ARIMA Model for Forecasting Agricultural Productivity in India. Journal of Agriculture & Social Sciences, 8(2), 50- 56.
  • Raymond Y. (1997). An Application of the ARIMA Model to Real-Estate Prices in Hong Kong. Journal of Property Finance, 8(2), 152-163.

Cite this article

APA

CHICAGO

    CHICAGO : Afeef, Mustafa, Nazim Ali, and Adnan Khan. 2018. "Tracing Stock Returns on Quarterly Basis: The Case of KSE-100 Index." Global Social Sciences Review, III (III): 466-476 doi: 10.31703/gssr.2018(III-III).26

HARVARD

    HARVARD : AFEEF, M., ALI, N. & KHAN, A. 2018. Tracing Stock Returns on Quarterly Basis: The Case of KSE-100 Index. Global Social Sciences Review, III, 466-476.

MHRA

    MHRA : Afeef, Mustafa, Nazim Ali, and Adnan Khan. 2018. "Tracing Stock Returns on Quarterly Basis: The Case of KSE-100 Index." Global Social Sciences Review, III: 466-476

MLA

    MLA : Afeef, Mustafa, Nazim Ali, and Adnan Khan. "Tracing Stock Returns on Quarterly Basis: The Case of KSE-100 Index." Global Social Sciences Review, III.III (2018): 466-476 Print.

OXFORD

    OXFORD : Afeef, Mustafa, Ali, Nazim, and Khan, Adnan (2018), "Tracing Stock Returns on Quarterly Basis: The Case of KSE-100 Index", Global Social Sciences Review, III (III), 466-476

TURABIAN

    TURABIAN : Afeef, Mustafa, Nazim Ali, and Adnan Khan. "Tracing Stock Returns on Quarterly Basis: The Case of KSE-100 Index." Global Social Sciences Review III, no. III (2018): 466-476. https://doi.org/10.31703/gssr.2018(III-III).26