Causal Loop Modeling of Macroeconomic Determinants of Stock Market Volatility

Prof. Sonam Bhadauriya

doi:https://doi.org/10.51976/gla.prastuti.v3i2.321406

Submit Manuscript Login / Register Subscribe

Home Page

Editorial Advisory Board

Mission, Aims & Scope

Current Issue

Causal Loop Modeling of Macroeconomic Determinants of Stock Market Volatility

Sonam Bhadauriya

Vol 3 , Issue 2 , July - December 2014 | Pages: 64-71 | Research Paper

https://doi.org/10.51976/gla.prastuti.v3i2.321406

Published Online: January 20, 2015

Author Details ( * ) denotes Corresponding author

1. * Sonam Bhadauriya, Assistant Professor , Department of Humanities, NIMS University, Jaipur, Rajasthan, India (sbhadauriya@live.in)

Stock market is one of the most important sources for companies to raise money. It allows businesses to be publicly traded, or raise additional capital for expansion by selling shares of ownership of the company in a public market. History has shown that the price of shares and other assets is an important part of the dynamics of economic activity, and can influence or be an indicator of social mood. An economy where the stock market is on the rise is considered to be an upcoming economy.

Stock market dynamics or volatility refers to the variation in the stock price changes during a period of time. The volatility of stock market indicators goes beyond anyone’s reasonable explanations. Generally, variations in stock market are caused by the fluctuations in the performance of the economy or the macroeconomic indicators of an economy. The modeling of stock market volatility is one of the key areas of present financial research as stock market is the main determinant of economic development of a country. The present paper is intended at developing a dynamic model of macroeconomic determinants of stock market volatility via a causal loop diagramming.

Keywords

Stock market volatility, macroeconomic determinants, causal loop diagram

Adam, A. M, and Tweneboah, G. (2008). Do macroeconomic variables play any role in the stock market movement in Ghana?,"MPRA Paper 9357, University Library of Munich, Germany, revised 2008 Online at http://mpra.ub.uni-muenchen.de/9357/.
Aksoy, H., and Leblebicioglu, K. (2004). Modeling ISE100 index through fuzzy logic, Eleventh Annual MFS Conference Proceedings, Turkey.
Ali, I., Rehman, K. U., Yilmaz, A. K., Khan, M. A., and Afzal, H. (2010). Causal relationship between macro- economic indicators and stock exchange prices in Pakistan. African Journal of Business Management. 4(3), 312-319.
Binder, T., Vox, A., Belyazid, S., Haraldsson, H., and Svensson, M. (2004). Developing system dynamics model from causal loop diagrams. In proceedings of the 22nd International Conference of the System Dynamics Society, Oxford, UK.
Chowdhury, S. S., Mollik, A. T. & Akhter, M.S. (2006). Does predicted macroeconomic volatility influence stock market volatility? Evidence from the Bangladesh capital market, Working Paper, Department of Finance and Banking, University of Rajshahi, Bangladesh.
Cioni, L. (2009). The good and the bad of system dynamics. Draft paper, University of Pisa, Italy. Retrieved from http://www.di.unipi.it/~lcioni/ listofpapers/2009.html.
Engle, R. F. & Rangel, J. G. (2008).The Spline - GARCH model for low frequency volatility and its global macroeconomic causes, Review of Financial Studies, 21, 1187-1222.
Gileva, T. (2010). Econometrics of crude oil markets, Thesis submitted to the Department of Economics, University of Paris.
Goonatilake, R. & Herath, S. (2007). The volatility of stock Market & News, International Research Journal of Finance & Economics, 11.
Halper, J. and Perl, J. (2005). Causes and explanations: a structural-model approach. Part I: Causes, British Journal of Philosophy of Science, 56, 843-887.
Haron, K. & Maiyastri (2004).Principal component analysis in modeling stock market returns, Matematika, 20 (1), 31–41.
Humpe, A . & Macmillan, P. ( 2007 ) . Can macroeconomic variables explain long term stock market movements? A comparison of the US and Japan, CDMA Working Paper No. 07/20.
Kerby, A. & James, L. (2004).A multivariate statistical analysis of stock trends, Joint Statistical Meetings, Toronto, Ontario, Canada, August 8-12.
Kumar, S. (2009).“Investigating Causal Relationship Between Stock Return with Respect to Exchange Rate And FII: Evidence from India”, Birla Institute of Technology & Science, Pilani.
Liu, H. & Jun, W. (2011).Integrating independent component analysis and principal component analysis with neural network to predict Chinese stock market, Institute of Financial Mathematics and Financial Engineering, College of Science, Beijing Jiaotong University, Beijing, China.
Loretan, M. (1997).Generating market risk scenarios u s i n g p r i n c i p a l co m p o n e n t s a n a l y s i s : methodological and practical considerations, Federal Reserve Board, March.
Maysami, R. C., Lee, C. H. &Mohamad, A. H. (2004). Relationship between macroeconomic variablesand stock market indices: cointegrationevidence from stock exchange of Singapore’s All-S sector indices, Journal Pengurusan, 24, 47-77.
Schaffernicht, M. (2007). Causality and diagrams for system dynamics. Actas de la 50th International Conference of the System Dynamics Society Proceedings, Boston.