Tiwari, Aviral Kumar (2012): Decomposing Time-Frequency Relationship between Interest Rates and Share Prices in India through Wavelets.
Download (370kB) | Preview
The study analyzed Granger-causality between interest rate (IR) and share prices (SP) for the India by using monthly data covering the period of 1990M1 to 2009M3. The time-frequency relationship between IR and SP was decomposed through continuous wavelet approach for the first time in the study. We found that for the Indian economy the causal and reverse causal relations between SP and IR vary across scale and period viz., during the late 1993 and early 1994, in 1-4 year scale, IR is lagging with cycle effects from SP, whereas during 1998-2001, in 8~12 year scale, IR is leading with cyclical effects on the SP. Further, results show that during 2003 to early 2005 (in 1~6 year scale) and again after late 2006 (in 9~14 year scale) IR is lagging and receiving anti-cyclical effects from SP.
|Item Type:||MPRA Paper|
|Original Title:||Decomposing Time-Frequency Relationship between Interest Rates and Share Prices in India through Wavelets|
|English Title:||Decomposing Time-Frequency Relationship between Interest Rates and Share Prices in India through Wavelets|
|Keywords:||cyclical effects, anti-cyclical effects, Granger-causality, phase difference, cross wavelets, wavelet coherency|
|Subjects:||C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles
|Depositing User:||aviral tiwari|
|Date Deposited:||27. Jun 2012 11:14|
|Last Modified:||10. Sep 2015 20:39|
Aguiar-Conraria, L., Azevedo, N., Soares, M. J. (2008), “Using Wavelets to Decompose the Time-Frequency Effects of Monetary Policy”, Phys A Stat Mech Appl, 387: 2863–2878.
Aguiar-Conraria, L., Soares, M. J. (2011), “Oil and the Macroeconomy: Using Wavelets to Analyze Old Issues”, Empirical Economics, 40: 645–655.
Almasri, A., Shukur, G. (2003), “An Illustration of the Causality Relationship Between Government Spending and Revenue Using Wavelets Analysis on Finnish Data,” Journal of Applied Statistics, 30(5): 571-584.
Cifter, A. (2006), “Wavelets Methods in Financial Engineering: An Application to ISE-30(Turkish), Graduation Project, Institute of Social Sciences, Marmara University.
Cifter, A., Ozun, A. (2008a), “Estimating the Effects of Interest Rates on Share Prices in Turkey Using a Multi-Scale Causality Test”, Review of Middle East Economics and Finance, 4(2): Article 2.
Cifter, A., Ozun, A. (2008b), “A Signal Processing Model for Time Series Analysis: The Effects of International F/X Markets on Domestic Currencies Using Wavelet Networks,” International Review of Electrical Engineering, 3(3).
Dalkır, M. (2004), “A New Approach to Causality in the Frequency Domain”, Economics Bulletin, 3(44), 1-14.
Gabor, D. (1946), “Theory of Communication”, J Inst Electr Eng, 93: 429–457.
Gallegati, M. (2005), “A Wavelet Analysis of MENA Stock Markets, Mimeo, Universita Politecnica Delle Marche, Ancona, Italy.
Gencay, R., Selcuk, F. (2004), “Extreme Value Theory and Value at Risk: Relative Performance in Emerging Markets”, International Journal of Forecasting, 20: 287-303.
Gencay, R., Selcuk, F., Whitcher, B. (2002), “An Introduction to Wavelets and Other Filtering Methods in Finance and Economics”, Academic Press.
Grinsted, A., Moore, J. C., Jevrejeva, S. (2004), “Application of the Cross Wavelet Transform and Wavelet Coherence to Geophysical Time Series”, Nonlinear Processes in Geophysics, 11: 561–566.
Hudgins, L., Friehe, C., Mayer, M. (1993), “Wavelet Transforms and Atmospheric Turbulence”, Physical Review Letters, 71(20): 3279–3282.
Kim, S., In, H.F. (2003), “The Relationship between Financial Variables and Real Economic Activity: Evidence from Spectral and Wavelet Analyses”, Studies in Nonlinear Dynamic & Econometrics, 7(4): Article 4.
Mitra, S. (2006), “A Wavelet Filtering Based Analysis of Macroeconomic Indicators: The Indian Evidence”, Applied Mathematics and Computation, 175: 1055–1079
Norsworty, J., Li, D., Gorener, R. (2000), “Wavelet-Based Analysis of Time Series: An Export from Engineering to Finance”, IEEE International Engineering Management Society Conference, Albuquerque, New Mexico.
Raihan, S., Wen, Y., Zeng, B. (2005), “Wavelet: A New Tool for Business Cycle Analysis”, Working Paper 2005-050A, Federal Reserve Bank of St. Louis.
Ramsey, J.B., Lampart, C. (1998), “Decomposition of Economic Relationships by Timescale Using Wavelets: Money and Income”, Macroeconomic Dynamics, 2: 49-71.
Torrence, C., Compo, G.P. (1998), “A Practical Guide to Wavelet Analysis”, Bulletin of the American Meteorological Society, 79: 605–618.
Torrence, C., Webster, P. (1999), “Interdecadal Changes in the ESNOM on soon System”, J. Clim, 12: 2679–2690.
Zhang, C., Farley, A. (2004), “A Multiscaling Test of Causality Effects Among International Stock Markets”, Neural, Parellel and Scientific Computations, 12(1): 91-112.