Bond yields and stock returns comparison using wavelet semblance analysis
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DOIhttp://dx.doi.org/10.21511/imfi.14(2-1).2017.12
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Article InfoVolume 14 2017, Issue #2 (cont. 1), pp. 281-289
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Various measures of resemblance are increasingly applied in confrontation of data samples obtained by different sources. Semblance analysis aims at comparison of two sets of data based on their phase and frequency. Conventional semblance analysis following the Fourier transform has several deficiencies resulting from the transform. To overcome these obstacles, another type of semblance analysis was developed applying the wavelet transform. This paper focuses on semblance analysis of stock prices and government bond yields of two major global economies using continuous wavelet transform regarding both scale and time.
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JEL Classification (Paper profile tab)C22, G1
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References28
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Tables0
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Figures4
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- Figure 1. German 10 year bond yield and DAX analysis
- Figure 2. US 10 year treasury yield and S&P500 analysis
- Figure 3. German 10 year bond and US 10 year treasury yield analysis
- Figure 4. DAX and S&P500 analysis
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- Afonso, A., & Nunes, A. S. (2015). Economic forecasts and sovereign yields. Economic Modelling, 44, 319-326.
- Ahmed, N., & Rao, K. R. (2012). Orthogonal transforms for digital signal processing. Springer Science & Business Media.
- Akoum, I., Graham, M., Kivihaho, J., Nikkinen, J., & Omran, M. (2012). Co-movement of oil and stock prices in the GCC region: A wavelet analysis. The Quarterly Review of Economics and Finance, 52(4), 385-394.
- Antonakakis, N., & Vergos, K. (2013). Sovereign bond yield spillovers in the Euro zone during the financial and debt crisis. Journal of International Financial Markets, Institutions and Money, 26, 258-272.
- Brémaud, P. (2013). Mathematical principles of signal processing: Fourier and wavelet analysis. Springer Science & Business Media.
- Chionis, D., Pragidis, I., & Schizas, P. (2014). Long-term government bond yields and macroeconomic fundamentals: Evidence for Greece during the crisis-era. Finance Research Letters, 11(3), 254-258.
- Cooper, G. R. J., & Cowan, D. R. (2008). Comparing time series using wavelet-based semblance analysis. Computers & Geosciences, 34(2), 95-102.
- Debnath, L. (Ed.). (2012). Wavelets and signal processing. Springer Science & Business Media.
- Diebold, F. X., & Li, C. (2006). Forecasting the term structure of government bond yields. Journal of econometrics, 130(2), 337-364.
- Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66.
- Ferrer, R., Bolós, V. J., & Benítez, R. (2016). Interest rate changes and stock returns: a European multi-country study with wavelets. International Review of Economics & Finance, 44, 1-12.
- Fujiwara, I., Körber, L. M., & Nagakura, D. (2013). Asymmetry in government bond returns. Journal of Banking & Finance, 37(8), 3218-3226.
- 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(5/6), 561-566.
- Hautsch, N., & Ou, Y. (2012). Analyzing interest rate risk: Stochastic volatility in the term structure of government bond yields. Journal of Banking & Finance, 36(11), 2988-3007.
- Jammazi, R., Tiwari, A. K., Ferrer, R., & Moya, P. (2015). Time-varying dependence between stock and government bond returns: International evidence with dynamic copulas. The North American Journal of Economics and Finance, 33, 74-93.
- Khalfaoui, R., Boutahar, M., & Boubaker, H. (2015). Analyzing volatility spillovers and hedging between oil and stock markets: Evidence from wavelet analysis. Energy Economics, 49, 540-549.
- Kiley, M. T. (2016). Monetary policy statements, treasury yields, and private yields: before and after the zero lower bound. Finance Research Letters.
- Kim, S., & In, F. (2007). On the relationship between changes in stock prices and bond yields in the G7 countries: Wavelet analysis. Journal of International Financial Markets, Institutions and Money, 17(2), 167-179.
- Koeda, J. (2013). Endogenous monetary policy shifts and the term structure: Evidence from Japanese government bond yields. Journal of the Japanese and International Economies, 29, 170-188.
- Lee, C. C., Huang, W. L., & Yin, C. H. (2013). The dynamic interactions among the stock, bond and insurance markets. The North American Journal of Economics and Finance, 26, 28-52.
- Mallat, S. (1999). A wavelet tour of signal processing. Academic press.
- Moessner, R. (2015). Reactions of US government bond yields to explicit FOMC forward guidance. The North American Journal of Economics and Finance, 33, 217- 233.
- Poghosyan, T. (2014). Long-run and short-run determinants of sovereign bond yields in advanced economies. Economic Systems, 38(1), 100-114.
- Reboredo, J. C., Rivera-Castro, M. A., & Ugolini, A. (2016). Wavelet-based test of co-movement and causality between oil and renewable energy stock prices. Energy Economics
- Samadder, S., Ghosh, K., & Basu, T. (2015). Search for the periodicity of the prime Indian and American stock exchange indices using date-compensated discrete Fourier transform. Chaos, Solitons & Fractals, 77, 149-157.
- Shahzad, S. J. H., Kumar, R. R., Ali, S., & Ameer, S. (2016). Interdependence between Greece and other European stock markets: A com¬parison of wavelet and VMD copula, and the portfolio implications. Physica A: Statistical Mechanics and its Applications, 457, 8-33.
- Teolis, A. (2012). Computational signal processing with wavelets. Springer Science & Business Media.
- Yang, L., & Hamori, S. (2015). Interdependence between the bond markets of CEEC-3 and Germany: A wavelet coherence analysis. The North American Journal of Economics and Finance, 32, 124-138.
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