Dynamic conditional correlation and volatility distributions in Tokyo, London, and New York gold markets
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DOIhttp://dx.doi.org/10.21511/imfi.16(4).2019.13
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Article InfoVolume 16 2019, Issue #4, pp. 146-155
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This study investigates the volatility and co-movement of gold prices across Tokyo, London, and New York gold markets. Using a dynamic conditional correlation (DCC) model, the authors estimate the cross-correlation and volatility of gold in each pair among three markets over the period from 1993 to 2012. Both the time-varying correlations and realized distributions are explored. After estimating the DCC as well as the corresponding distributions of the DCC among the three markets, the results suggest that: (i) the DCC probability distribution of London and New York shows a higher volatility associated with a higher DCC value; (ii) the DCC probability distribution between London and New York as well as between Tokyo and London both express the similar and overlapping pattern, implying that these markets are almost equal, and neither dominates; and (iii) New York exhibits a spillover effect of Tokyo’s variance, while the latter does not influence New York’s variance. The shapes of the distributions show that the distribution of high DCC is wider than that of low DCC, meaning that risk increases with the dynamic correlation. The implications of these gold DCC probability distributions encourage investors to diversify their global portfolios and manage latent risks in different gold markets effectively. Besides, the volatility-threshold DCC model suggests that the correlations are more sensitive to extreme volatility thresholds in London and New York markets, whereas the correlation is significantly affected by all levels of volatility at 50%, 75%, 90%, and 95% thresholds in Tokyo and London markets. Investors may not be able to diversify portfolio risk by choosing London and New York at the same time once gold becomes volatile as a high correlation is observed in the extreme thresholds.
- Keywords
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JEL Classification (Paper profile tab)C23, G15
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References45
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Tables6
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Figures4
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- Figure 1. Distributions of dynamic conditional correlations for the Tokyo, London, and New York gold markets over the sample period
- Figure 2(a). Distributions of DCC between Tokyo and London gold markets on low and high volatility days
- Figure 2(b). Distributions of DCC between London and New York gold markets on low and high volatility days
- Figure 2(c). Distributions of DCC between New York and Tokyo gold markets on low and high volatility days
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- Table 1. Summary statistics of daily gold returns in Tokyo, London, and New York
- Table 2. The correlation of gold among Tokyo, London, and New York
- Table 3. DCC conditional correlation estimates: three markets
- Table 4. Estimation results from DCC-GARCH model
- Table 5. DCC distributions of gold among Tokyo, London, and New York markets
- Table 6. Volatility threshold and dynamic conditional correlation
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- Andersen, T. G., Bollerslev, T., Diebold, F. X., & Ebens, H. (2001a). The distributions of realized stock return volatility. Journal of Financial Economics, 61(1), 43-76.
- Andersen, T. G., Bollerslev, T., Diebold, F. X., & Labys, P. (2001b). The distribution of realized exchange rate volatility. Journal of the American Statistical Association, 96(453), 42-55.
- Bakaert, G., & Harvey, C. R. (1997). Emerging equity market volatility. Journal of Financial Economics, 43(1), 29-77.
- Baruník, J., Kočenda, E., & Vácha, L. (2016). Gold, oil, and stocks: Dynamic correlations. International Review of Economics & Finance, 42, 186-201.
- Baur, D., & Lucey, B. (2010). Is gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financial Review, 45(2), 217-229.
- Baur, D., & McDermott, T. (2010). Is gold a safe haven? International evidence. Journal of Banking and Financial, 34(8), 1886-1898.
- Becker, K. G., Finnerty, J. E., & Gupta, M. (1990). The intertemporal relation between the U.S. and Japanese stock markets. Journal of Finance, 45(4), 1297-1306.
- Bollerslev, T. (1986). Generalized autoregressive conditional heteroscedasticity. Journal of Econometrics, 31(3), 307-327.
- Bollerslev, T. (1990). Modeling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH. Review of Economics and Statistics, 72(3), 498-505.
- Booth, G. G., Teppo, M., & Tse, Y. (1997). Price and volatility spillovers in Scandinavian stock markets. Journal of Banking and Finance, 21(6), 811-823.
- Bowman, R., Chan, K. F., & Comer, M. (2010). Diversification, rationality and Asian economic crisis. Pacific Basin Financial Journal, 18(1), 1-23.
- Cappiello, L, Engle, R. F., & Sheppard, K. (2006). Asymmetric dynamics in the correlations of global equity and bond returns. Journal of Financial Econometrics, 4(4), 537-572.
- Chang, C-L., McAleer, M., & Tansuchat, R. (2009a). Modeling conditional correlations for risk diversification in crude oil markets. Journal of Energy Markets, 2, 29-51.
- Chang, C-L., McAleer, M., & Tansuchat, R. (2010). Analyzing and forecasting volatility spillovers, asymmetries and hedging in major oil markets. Energy Economic, 32(6), 1445-1455.
- Chiang, T. C., Jeon, B. N., & Li, H. M. (2007). Dynamic correlation analysis of financial contagion: evidence from Asian markets. Journal of International Money and Finance, 26(7), 1206-1228.
- Chiang, T. C., Tan, L., & Li, H. M. (2007). Empirical analysis of dynamic correlations of stock returns: evidence from Chinese A-share and B-share market. Quantitative Finance, 7(6), 651-667.
- Chiang, T. C., Yu, H.-C., & Wu, M. C. (2009). Statistical properties, dynamic conditional correlation and scaling analysis: Evidence from Dow Jones and Nasdaq high-frequency data. Physica A, 388, 1555-1570.
- Chu, L. P. (2006). Dynamic conditional correlation, probability distribution, co-movement and spillover in Tokyo, London and New York yen/dollar FX markets (Unpublished master thesis, Institute of International Business, Chung Yuan Christian University).
- Ciner, C., Gurdgiev, C., & Lucey, B. M. (2013). Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates. International Review of Financial Analysis, 29, 202-211.
- Das, S. R., & Uppal, R. (2004). Systemic risk and international portfolio choice. The Journal of Finance, 59(6), 2809-2834.
- Doong, S. C., Yang, S. Y., & Wang, A. T. (2005). The dynamic relationship and pricing of stocks and exchange rates: Empirical evidence from Asian emerging markets. Journal of American Academy of Business, 7(1), 118-123.
- Engle, R. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of U.K. inflation. Econometrica, 50(4), 987-1008.
- Engle, R. (2002). Dynamic conditional correlation: A simple class of multivariate GARCH models. Journal of Business and Economic Statistics, 20(3), 339-350.
- Eun, C. S., & Shim, S. (1989). International transmission of stock market movements. Journal of Financial and Quantitative Analysis, 24(2), 241-256.
- Fleming, J., Kirby, C., & Ostdiek, B. (1998). Information and volatility linkages in the stock, bond, and money markets. Journal of Financial Economics, 49(1), 111-137.
- Hilliard, J. E. (1979). The relationship between equity indices on world exchanges. Journal of Finance, 34(1), 103-114.
- Hood, M., & Malik, F. (2013). Is gold the best hedge and a safe haven under changing stock market volatility? Review of Financial Economics, 22(2), 47-52.
- Jaffe, J., & Westerfield, R. (1985). The Weekend effect in common stock returns: The international evidence. Journal of Finance, 40(2), 433-454.
- Kanas, A. (1998). Linkages between the US and European equity markets: further evidence from co-integration tests. Applied Financial Economics, 8(6), 607-614.
- Kasch, M., & Caporin M. (2013). Volatility threshold dynamic conditional correlations: An international analysis. Journal of Financial Econometrics, 11(4), 706-742.
- Kasch-Haroutounian, M. (2005). Volatility threshold dynamic conditional correlations: Implications for international portfolio diversification (Presented at the Journal of Applied Econometrics Conference on Changing Structures in International and Financial Markets and the Effects on Financial Decision Making). Venice, Italy.
- Kearney, A. A., & Lombra, R. E. (2009). Gold and platinum: Toward solving the price puzzle. The Quarterly Review of Economics and Finance, 49(3), 884-892.
- King, M. A., & Wadhwani, S. (1990). Transmission of volatility between stock markets. The Review of Financial Studies, 3(1), 5-33.
- Lanza, A., Manera, M., & McAleer, M. (2006). Modeling dynamic conditional correlations in WTI oil forward and futures returns. Finance Research Letters, 3(2), 114-132.
- Lin, W. L., Engle, R., & Ito, T. (1994). Do bulls and bears move across borders? International transmission of stock returns and volatility. Review of Financial Studies, 7, 507-538.
- Ling, S., & McAleer, M. (2003). Asymptotic theory for a vector ARMA-GARCH model. Econometric Theory, 19(2), 280-310.
- Ng, A. (2000). Volatility spillover effects from Japan and the US to the pacific basin. Journal of International Money and Finance, 19(2), 207-233.
- Pérez-Rodríguez, J. (2006). The euro and other major currencies floating against the U.S. dollar. Atlantic Economic Journal, 34(4), 367-384.
- Piplack, J., & Straetmans, S. (2009). Comovements of different asset classes during market stress. Pacific Economic Review, 15(3), 385-400.
- Poshakwale, S. S., & Mandal, A. (2016). Determinants of asymmetric return co-movements of gold and other financial assets. International Review of Financial Analysis, 47, 229-242.
- Reboredo, J. C. (2013). Is gold a safe haven or a hedge for the US dollar? Implications for risk management. Journal of Banking & Finance, 37(8), 2665-2676.
- Reboredo, J. C., & Rivera-Castro, M. A. (2014). Can gold hedge and preserve value when the US dollar depreciates? Economic Modelling, 39, 168-173.
- Ripley, D. M. (1973). Systematic elements in the linkage of national stock market indices. Review of Economics and Statistics, 55(3), 356-361.
- Sonlinik, B., Boucrelle, C., & LeFur, Y. (1996). International market correlation and volatility. Financial Analysts Journal, 52(5), 17-34.
- Tastan, H. (2006). Estimating time-varying conditional correlations between stock and foreign exchange markets. Physica A, 360(2), 445-458.