بررسی رابطه علیت گرنجری هشیائوی بازده شاخص 11 بورس جهان با بازده شاخص بورس تهران

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 استاد دانشکدۀ مدیریت و اقتصاد، دانشگاه تربیت مدرس، تهران، ایران

2 کارشناس‎ارشد گرایش مدیریت مالی، دانشگاه تربیت مدرس، تهران، ایران

چکیده

در عصر حاضر، بازارها محدود به مکان جغرافیایی خاصی نیستند. اهمیت این مسئله در به‌کارگیری تصمیمات اثربخش‏تر فعالان اقتصادی نمود پیدا می‏کند؛ زیرا بازارهای مالی جهانی اغلب راهنمای باارزشی برای بازارهای داخلی و خارجی به‎شمار می‏آیند. در این پژوهش با توجه به روابطی که میان بازارهای سهام در جهان وجود دارد، بازار سهام کشورهایی که بیشترین روابط تجاری را با ایران طی دورۀ زمانی 20011‌- 2005 داشته‏اند، همراه با بورس تهران انتخاب شده‏اند. این بازارهای سهام عبارت‌اند از بورس لندن، فرانکفورت، پاریس، میلان، سوئیس، توکیو، شانگهای، کره، بمبئی، استانبول و بازار مالی دبی. بازده شاخص بازارهای سهام مذکور طی دورۀ زمانی مورد نظر استخراج ‌و ارتباط علّی آن‏ها با بازده شاخص بورس تهران با استفاده از روش آزمون علیت گرنجری هشیائو برآورد شد. نتایج این پژوهش نشان داد که بازده شاخص بورس‏های لندن، فرانکفورت، پاریس، میلان، سوئیس، توکیو، کره و بمئبی علت گرنجری هشیائوی بازده شاخص بورس تهران هستند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Investigating the Hsiao’s Granger Causality among Returns of 11 World Stock Markets Indexes and Return of Tehran Stock Exchange Index

نویسندگان [English]

  • Ali Asghar Anvary Rostamy 1
  • Hossein Ghorbani Farmad 2
  • Adel Azar 1
1 Professor, Financial Management, Tarbiat Modares University, Tehran, Iran
2 MSc. in Financial Management, Tarbiat Modares University, Tehran, Iran
چکیده [English]

In today’s world, markets are no longer under the limitations of a specific location and the importance of this issue is illustrated in effective decision making of economic agents, because the world financial markets are considered often valuable guideline for domestic and foreign markets. In this research, due to the connections between world stock markets, stock markets in countries with the most commercial communications with Iran during the time period of study (2005-2011) have been selected. These markets include London, Tokyo, Shanghai, Frankfurt, Paris, Milan, SIX Swiss, Istanbul, Korea, Bombay Stock Exchanges, and Dubai Financial Market. The returns of these stock markets are extracted and their causal relationships with the returns of Tehran Stock Exchange are estimated by Hsiao’s Granger Causality method. The results show that returns of markets in London, Frankfurt, Frankfurt, Paris, Milan, SIX Swiss, Tokyo, Korea and Bombay Stock Exchanges are the Hsiao’s Granger Causality for index return of Tehran Stock Exchange.

کلیدواژه‌ها [English]

  • World Stock Markets"
  • Hsiao’s Granger Causality"
  • Stock Market Index Returns"
  • Tehran Stock Exchange
Awokuse, T.O., Chopra, A. & Bessler, D.A. (2009). Structural change and international stock market interdependence: Evidence from Asian emerging markets. Economic Modeling, 26(3): 549-559.
Burton, M., Nesiba, R. & Brown, B. (2009). An Introduction to Financial Markets and Institutions, 2 edition, M E Sharpe.
De Gooijer, J.G. & Sivarajasingham, S. (2008). Parametric and nonparametric Granger causality testing: Linkages between international stock markets. Physica A: Statistical Mechanics and its Applications, 387(1-2): 2547–2560.
Ercan Balaban & Asli Bayar & Robert Faff (2006). Forecasting stock market volatility: Further international evidence. European Journal of Finance 12(2): 171-188.
Fallahpour, S., Golarzi, G. & Fatourechian, N. (2013). Predicting Stock Price Movement Using Support Vector Machine Based on Genetic Algorithm in Tehran Stock Exchange Market. Journal of Financial Research 15(2): 269-288. (in Persian)
Filis, G., Degiannakis, S. & Floros, CH. (2011). Dynamic correlation between stock market and oil prices: The case of oil-importing and oil-exporting countries. International Review of Financial Analysis, 20(3): 152-164.
Granger, C.W.J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 37(3): 424-438.
Hsiao, C. (1981). Autoregressive modeling and money-income causality detection. Journal of Monetary Economics, 7(1): 85-106.
Huyghebaert, N. & Wang, L. (2010). The co-movement of stock markets in East Asia Did the 1997–1998 Asian financial crisis really strengthen stock market integration? China Economic Review 21(1): 98-112.
Jafarabdi, A. (2010). Examine the relationship between Tehran and Dubai Exchange Markets. Master's thesis, Tehran, Sharif University of Technology.
(in Persian)
Junior, L.S. & De Paula Franca, I. (2012). Correlation of financial markets in times of crisis. Physica A: Statistical Mechanics and its Applications, 391(1-2): 187-208.
Katsanos, M. (2010). Intermarket Trading Strategies: John Wiley & Sons.
Kenourgios, D., Samitas, A. & Paltalidis, N. (2011). Financial crises and stock market contagion in a multivariate time-varying asymmetric framework. International Financial Markets Institution & Money, 21(1): 92-106.
Mellyn, K. (2009). Financial Market Meltdown: Everything You Need to Know to Understand and Survive the Global Credit Crisis: Greenwood Publishing Group.
Murphy, J. J. (1991). Intermarket Technical Analysis: Trading Strategies for the Global Stock, Bond, Commodity, and Currency Markets: Wiley Finance.
Murphy, J. J. (2004). Intermarket Analysis: Profiting from Global Market Relationships: John Wiley & Sons.
Pakizeh, K. (2010). Volatility Modeling, Forecasting and Its relation with Stock Returns in Tehran and International Stock Exchanges. Doctoral dissertation, Tehran, University of Allameh Tabatabaee. (in Persian)
Raee, R., Mohmadi, S. & Saranj, A. (2014). Tehran Stock Exchange dynamics in a Markov regime switching EGARCH-in-mean model. Journal of Financial Research, 16(1): 77-98. (in Persian)
Raeyat, M. (2009). The relation between internal macroeconomic variables and some world stock index with Iran stock price index. Master's thesis, Tehran, Tarbiat Modares University. (in Persian)
Samarakoon, L. P. (2011). Stock market interdependence, contagion, and the U.S. financial crisis: The case of emerging and frontier markets. International Financial Markets Institution & Money, 21(1): 92-106.
Seyedhosseini, S. M. & Ebrahimi, S. B. (2013). Comparing of Volatility Transmission Model with Consideration of Long Memory Effect; Case Study: Three Selected Industry Index. Journal of Financial Research, 15(1): 51-74. (in Persian)
Tehrani, R., Namaki, A. & Hedayatifar, L. (2013). The Cross-correlation Structure of Tehran Stock Exchange Indexes by Multifractal Detrended Fluctuation Analysis. Journal of Financial Research, 14(1): 55-68. (in Persian)