人民币汇率波动性特征的实证分析
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摘要
本文以人民币/美元、人民币/欧元、人民币/日元和人民币/英镑汇率为研究样本,对人民币汇率的收益率序列与绝对值收益率序列的基本统计特征、非对称性和长记忆性展开实证研究,得出如下结论:
对人民币汇率收益率与绝对值收益率序列均不服从独立同分布,不服从标准正态分布,具有典型的尖峰厚尾特征;收益率序列不存在或只存在极为微弱的短期自相关,而绝对值收益率序列都具有较强的短期自相关性;对人民币汇率收益率序列进行EGARCH-M模型估计,结果表明除了人民币/日元收益率有较强的非对称性,其余的三个序列的非对称效应都很微弱。信息冲击曲线也很清楚地表明了这一结论;使用R/S方法分别对人民币汇率收益率序列和绝对值收益率序列进行长记忆性检验与Hurst参数估计,结果表明除了人民币/美元收益率序列,其他收益率序列均不具备长记忆性,而绝对值收益率序列都具有较强的长记忆特征。
Taking RMB exchange rate against U.S. dollar, Euro, Yen and Pound as the sample, the paper analyzes basic statistics, non-symmetry and long memory in volatilities of the RMB exchange rate’s returns and its’absolute value of returns, drawing a follow conclusion:
Both of the RMB exchange rate of return and absolute value of returns are not subject to independent and identical distribution, do not obey the standard normal distribution, and have the typical characteristics of fat tails. Return series do not exist or exists only very weak short-term autocorrelation, while the absolute value series have strong short-term autocorrelation. The estimation results of EGARCH-M model indicate the returns of RMB exchange rate against Yen has a strong non-symmetry, but that of the other three are weak. It’s obviously to see that from their Information shock curves. We using the R / S method for the return series and the absolute value series to test the long memory and estimate the Hurst parameter, and the results indicating that except the return series of RMB exchange rate against U.S. dollar, all the return series have no long memory, while all the absolute value series have strong long memory characteristics.
对人民币汇率收益率与绝对值收益率序列均不服从独立同分布,不服从标准正态分布,具有典型的尖峰厚尾特征;收益率序列不存在或只存在极为微弱的短期自相关,而绝对值收益率序列都具有较强的短期自相关性;对人民币汇率收益率序列进行EGARCH-M模型估计,结果表明除了人民币/日元收益率有较强的非对称性,其余的三个序列的非对称效应都很微弱。信息冲击曲线也很清楚地表明了这一结论;使用R/S方法分别对人民币汇率收益率序列和绝对值收益率序列进行长记忆性检验与Hurst参数估计,结果表明除了人民币/美元收益率序列,其他收益率序列均不具备长记忆性,而绝对值收益率序列都具有较强的长记忆特征。
Taking RMB exchange rate against U.S. dollar, Euro, Yen and Pound as the sample, the paper analyzes basic statistics, non-symmetry and long memory in volatilities of the RMB exchange rate’s returns and its’absolute value of returns, drawing a follow conclusion:
Both of the RMB exchange rate of return and absolute value of returns are not subject to independent and identical distribution, do not obey the standard normal distribution, and have the typical characteristics of fat tails. Return series do not exist or exists only very weak short-term autocorrelation, while the absolute value series have strong short-term autocorrelation. The estimation results of EGARCH-M model indicate the returns of RMB exchange rate against Yen has a strong non-symmetry, but that of the other three are weak. It’s obviously to see that from their Information shock curves. We using the R / S method for the return series and the absolute value series to test the long memory and estimate the Hurst parameter, and the results indicating that except the return series of RMB exchange rate against U.S. dollar, all the return series have no long memory, while all the absolute value series have strong long memory characteristics.
引文
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[2] Blanchard, O. J. Speculative Bubbles, Crashes and rational expectations. Economic Letters, 1979, 3:387-89.
[3] Dornbusch, R. Exchange Rate Economics: Where do we stand? economic interdependence and flexible exchange rates. Bhandari J S, Bluford H P.(eds), The MIT Press, 1983.
[4] Huang, R. D. The monetary approach to exchange rate in an efficient foreign exchange market: tests based on volatility. Journal of Finance, 1981, 36: 31-41.
[5] Obstfeld, M. and Rogoff, K. The mirage of fixed exchange rate. NBER Working Papers 4952, National Bureau of Economic Research, Inc, 1995.
[6] Obstfeld, M. and Rogoff, K. The six major puzzles in international macroeconomics: Is there a common cause? NBER Macroeconomics Annual, Bernanke B, Rogoff K.(eds), Cambridge MA, 2000.
[7] Lyons, R. The microstructure approach to exchange rates. MIT Press, published December, 2001.
[8] Evans, M. and Lyons, R. Order flow and exchange rate dynamics. Journal of Political Economy, 2002a, 110: 170-180.
[9] Evans, M. and Lyons, R. Informational integration and FX trading. Journal of International Money and Finance, 2002b, 21: 807-831.
[10] Rime, D. U. S. exchange rates and currency flows. SIFR Research Report Series 4, Institute for Financial Research, 2001.
[11] Obstfeld, M. and Taylor, A.M. Nonlinear aspects of goods-market arbitrage and adjustment: heckscher’s commodity points revisited. Journal of the Japanese and International Economies, Elsevier, 1997, 11(4): 441-479.
[12] De Grauwe, P. and Dewachter, H. A chaotic monetary of the exchange rate. Credit and Capital, 1992, 25: 26-54.
[13] De Grauwe, P. , Dewachter, H. and Embrechts, M. Exchange rate theory: chaotic models of foreign exchange markets. Blackwell Publishers, 1993.
[14]莫世康,王文峰,《基于复杂系统和混沌理论的双重汇率模型》,南开经济研究,2004(6).
[15] Mandelbrot, B. The variation of certain speculative prices. The Journal of Business of the University of Chicago 1963, 36 : 394-419.
[16] Engle, R. E. Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation. Econometrica, 1982, 50: 987-1008.
[17] Bollerslev T. Generalized autoregressive conditional heteroskedasticity. Journal of Econometircs, 1986,31: 307-327.
[18] Taylor, S. T. Modeling financial time series. Wiley, New York, NY, 1986.
[19] Black F. Studies of stock market volatility changes. Proceedings of the American Statistical Association. Business and Economic Statistical, 1976, 99: 175-182.
[20] Koutmos, G. and Booth, G. G. Asymmetric volatility and risk return tradeoff in foreign stock markets. Journal of International Money and Finance, 1995, 14: 747-762.
[21] Koutmos, G. Modeling the dynamic interdependence of major European stock markets. Journal of Business Finance and Accounting 1996, 23:975-988.
[22] Ito, T. Foreign exchange rate expectations: micro survey data. American Economic Review, American Economic Association, 1990, 80(3): 434-449.
[23] Nelson, D. B. Conditional heteroskedasticity in asset returns: a new approach. Econometrica, 1991, 59: 347-370.
[24] Golsten, L.R., Jagannathan, R. and Runkle, D.E. On the relation between the expected value and the volatility of nominal excess return on stocks. Journal of Finance, 1993, 48: 1779-1801.
[25] Hurst, H. S. Long-term storage capacity of reservoirs. Transactions of the American Society of Civil Engineers, 1951,116: 770-779.
[26] Fama, E. F. and French, K. R. Dividend yields and expected stock returns. Journal of Financial Economics, Elsevier, 1988, 22(1): 3-25.
[27] Poterba, J. M. and Summers, L. H. Mean reversion in stock prices: evidence and implications. Journal of Financial Economics, Elsevier, 1988, 22(1): 27-59.
[28] Dacorogna, M. M. , Muller, U. A. , Nagler, R. J. , Olsen, R. B. and Pictet, O. V. A geographical model for the daily and weekly seasonal volatility in the foreign exchange market. Journal of International Money and Finance, Elsevier, 1993, 12(4): 413-438.
[29] Lo, A. W. Long-term memory in stock market prices. Econometrica, 1991, 59(5): 1279-1313.
[30] Kwiatkowski, D. , Phillips, P. C. B. , Schmidt, P. , Shin, Y. Testing the null hypothesis of stationarity against the alternative of a unit root: how sure are we that economic time series have a unit root? Journal of Econometrics, 1992, 54: 159-178.
[31] Lee, D. , Schmidt, P. On the power of the KPSS test of stationarity against fractionally-integrated alternatives. Journal of Econometrics. 1996, 73: 285-302.
[32] Granger, C. W. J. Long memory relationships and the aggregation of dynamic models. Journal of Econometrics. 1980, 14: 227-238.
[33] Hosking, J. R. M. Fractional differencing. Biometrika. 1981, 68: 165-176.
[34] Gray, H. L. , Nien-Fan Zhang, and Woodward, W. A. On generalized fractional processes. Journal ofTime Series Analysis. 1989, 10(3): 233-257.
[35] Beran, J. Maximum likelihood estimation of differencing parameter for invertible short and long memory autoregressive integrated moving average models. Journal of the Royal Statistical Society, Series B. 1995, 57(4): 659-672.
[36] Engle, R. E. , Bollerslev, T. Modeling the persistence of conditional variances. Econometric Reviews, 1986, 5: 81-87.
[37] Baillie, R. T. , Bollerslev, T. , Mikkelsen, H. Fractional integrated generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 1996, 74: 3-30.
[38] Breidt, F. J. , Crato, N. , de Lima, P. Modeling long-memory stochastic volatility. Working paper in Economics No. 323, Johns Hopkins University, 1994.
[39] Peter E. A chaotic attractor for the S&p500 index. Financial Analyst, 1991, 47: 55-81.
[40] Bajo-Rubio O. , Fernández-Rodriguez F. and Sosvilla-Rivera. Chaotic behavior in exchange rate series: first result for the peseta-U.S. Dollar case. Economics Letters, 1992, 39(2): 207-211.
[41] De Grauwe P. and Grimaldi, M. Complexity in the foreign exchange market. In J. Barkley and Rosser, Jr. , (eds), Complexity in Economics II. Northampton, MA: Edward Elgar Pub,2004.
[42]陈彬,《我国证券市场收益波动度及相关性分析》,现代财经,2001(11)
[43]李亚静,何跃,朱宏泉,《中国股市收益率与波动性长记忆性的实证研究》,系统工程理论与实践,2003(1)
[44]张兵,《证券市场波动不对称性的动态研究》,管理学报,2006(3)
[45]何晓光,朱永军,《中国A股市场收益波动的非对称性研究》,数理统计与管理,2007(26)
[46]池启水,刘晓雪,《人民币汇率波动特征实证研究》,统计与决策,2007(23)
[47]朱新玲,黎鹏,《汇率波动非对称效应的计量检验——基于非对称ARCH类模型》,统计教育,2008(7)
[48] Shah, Ajay, Zeileis, Achim, Patnaik, Ila. What is the new Chinese currency regime? Research Report Series / Department of Statistics and Mathematics,2005(23).
[49]徐剑刚,邵华,唐国兴,《人民币参考一篮子货币机制的实证分析》,上海财经大学学报,2007(1)
[50]周雅瑞,赵晓波,《基于GJR-GARCH模型的港币汇率波动不对称研究》,湖南工业大学学报,2009(6)
[51] Fama, E. F. The behavior of stock-market prices. Journal of Business, 1965, 38(1): 34-105.
[52] Zakoian, J. M. Threshold heteroskedastic model. Journal of Economic Dynamics and Control, 1994, 18: 931-955.
[53] Ding Zhuanxin, Granger. C. W. J, Engle, R. E. A long memory property of stock market returns and a new model. Journal of Empirical Finance, 1993, 1: 83-106.
[54] Brockwell, P. J. , Davis, R. A. Time series: theory and methods. Springer-Verlag, 1991.
[55] Granger, C. W. J. and Joyeux, R. An introduction to long-memory time series models and fractional differencing. Journal of Time Series Analysis, 1980, 1: 15-30.
[56] Hiemstra, C. J. and Jones, D. Another look at long memory in common stock returns. Journal of Empirical Finance, 1997, 4: 373-401.
[57] Andersen, T. G. and Bollerslev, T. Heterogeneous information arrivals and return volatility dynamics: uncovering the long-run in high frequency returns. Journal of Finance, American Finance Association, 1997, 52(3): 975-1005.
[58]陈梦根,《中国股市长期记忆效应的实证研究》,经济研究,2003
[59]刘纪显,陈建梁,张宗益,《汇率定价模型及人民币兑美元汇率研究》,管理科学学报,2005(6).
[2] Blanchard, O. J. Speculative Bubbles, Crashes and rational expectations. Economic Letters, 1979, 3:387-89.
[3] Dornbusch, R. Exchange Rate Economics: Where do we stand? economic interdependence and flexible exchange rates. Bhandari J S, Bluford H P.(eds), The MIT Press, 1983.
[4] Huang, R. D. The monetary approach to exchange rate in an efficient foreign exchange market: tests based on volatility. Journal of Finance, 1981, 36: 31-41.
[5] Obstfeld, M. and Rogoff, K. The mirage of fixed exchange rate. NBER Working Papers 4952, National Bureau of Economic Research, Inc, 1995.
[6] Obstfeld, M. and Rogoff, K. The six major puzzles in international macroeconomics: Is there a common cause? NBER Macroeconomics Annual, Bernanke B, Rogoff K.(eds), Cambridge MA, 2000.
[7] Lyons, R. The microstructure approach to exchange rates. MIT Press, published December, 2001.
[8] Evans, M. and Lyons, R. Order flow and exchange rate dynamics. Journal of Political Economy, 2002a, 110: 170-180.
[9] Evans, M. and Lyons, R. Informational integration and FX trading. Journal of International Money and Finance, 2002b, 21: 807-831.
[10] Rime, D. U. S. exchange rates and currency flows. SIFR Research Report Series 4, Institute for Financial Research, 2001.
[11] Obstfeld, M. and Taylor, A.M. Nonlinear aspects of goods-market arbitrage and adjustment: heckscher’s commodity points revisited. Journal of the Japanese and International Economies, Elsevier, 1997, 11(4): 441-479.
[12] De Grauwe, P. and Dewachter, H. A chaotic monetary of the exchange rate. Credit and Capital, 1992, 25: 26-54.
[13] De Grauwe, P. , Dewachter, H. and Embrechts, M. Exchange rate theory: chaotic models of foreign exchange markets. Blackwell Publishers, 1993.
[14]莫世康,王文峰,《基于复杂系统和混沌理论的双重汇率模型》,南开经济研究,2004(6).
[15] Mandelbrot, B. The variation of certain speculative prices. The Journal of Business of the University of Chicago 1963, 36 : 394-419.
[16] Engle, R. E. Autoregressive conditional heteroskedasticity with estimates of the variance of UK inflation. Econometrica, 1982, 50: 987-1008.
[17] Bollerslev T. Generalized autoregressive conditional heteroskedasticity. Journal of Econometircs, 1986,31: 307-327.
[18] Taylor, S. T. Modeling financial time series. Wiley, New York, NY, 1986.
[19] Black F. Studies of stock market volatility changes. Proceedings of the American Statistical Association. Business and Economic Statistical, 1976, 99: 175-182.
[20] Koutmos, G. and Booth, G. G. Asymmetric volatility and risk return tradeoff in foreign stock markets. Journal of International Money and Finance, 1995, 14: 747-762.
[21] Koutmos, G. Modeling the dynamic interdependence of major European stock markets. Journal of Business Finance and Accounting 1996, 23:975-988.
[22] Ito, T. Foreign exchange rate expectations: micro survey data. American Economic Review, American Economic Association, 1990, 80(3): 434-449.
[23] Nelson, D. B. Conditional heteroskedasticity in asset returns: a new approach. Econometrica, 1991, 59: 347-370.
[24] Golsten, L.R., Jagannathan, R. and Runkle, D.E. On the relation between the expected value and the volatility of nominal excess return on stocks. Journal of Finance, 1993, 48: 1779-1801.
[25] Hurst, H. S. Long-term storage capacity of reservoirs. Transactions of the American Society of Civil Engineers, 1951,116: 770-779.
[26] Fama, E. F. and French, K. R. Dividend yields and expected stock returns. Journal of Financial Economics, Elsevier, 1988, 22(1): 3-25.
[27] Poterba, J. M. and Summers, L. H. Mean reversion in stock prices: evidence and implications. Journal of Financial Economics, Elsevier, 1988, 22(1): 27-59.
[28] Dacorogna, M. M. , Muller, U. A. , Nagler, R. J. , Olsen, R. B. and Pictet, O. V. A geographical model for the daily and weekly seasonal volatility in the foreign exchange market. Journal of International Money and Finance, Elsevier, 1993, 12(4): 413-438.
[29] Lo, A. W. Long-term memory in stock market prices. Econometrica, 1991, 59(5): 1279-1313.
[30] Kwiatkowski, D. , Phillips, P. C. B. , Schmidt, P. , Shin, Y. Testing the null hypothesis of stationarity against the alternative of a unit root: how sure are we that economic time series have a unit root? Journal of Econometrics, 1992, 54: 159-178.
[31] Lee, D. , Schmidt, P. On the power of the KPSS test of stationarity against fractionally-integrated alternatives. Journal of Econometrics. 1996, 73: 285-302.
[32] Granger, C. W. J. Long memory relationships and the aggregation of dynamic models. Journal of Econometrics. 1980, 14: 227-238.
[33] Hosking, J. R. M. Fractional differencing. Biometrika. 1981, 68: 165-176.
[34] Gray, H. L. , Nien-Fan Zhang, and Woodward, W. A. On generalized fractional processes. Journal ofTime Series Analysis. 1989, 10(3): 233-257.
[35] Beran, J. Maximum likelihood estimation of differencing parameter for invertible short and long memory autoregressive integrated moving average models. Journal of the Royal Statistical Society, Series B. 1995, 57(4): 659-672.
[36] Engle, R. E. , Bollerslev, T. Modeling the persistence of conditional variances. Econometric Reviews, 1986, 5: 81-87.
[37] Baillie, R. T. , Bollerslev, T. , Mikkelsen, H. Fractional integrated generalized autoregressive conditional heteroskedasticity. Journal of Econometrics, 1996, 74: 3-30.
[38] Breidt, F. J. , Crato, N. , de Lima, P. Modeling long-memory stochastic volatility. Working paper in Economics No. 323, Johns Hopkins University, 1994.
[39] Peter E. A chaotic attractor for the S&p500 index. Financial Analyst, 1991, 47: 55-81.
[40] Bajo-Rubio O. , Fernández-Rodriguez F. and Sosvilla-Rivera. Chaotic behavior in exchange rate series: first result for the peseta-U.S. Dollar case. Economics Letters, 1992, 39(2): 207-211.
[41] De Grauwe P. and Grimaldi, M. Complexity in the foreign exchange market. In J. Barkley and Rosser, Jr. , (eds), Complexity in Economics II. Northampton, MA: Edward Elgar Pub,2004.
[42]陈彬,《我国证券市场收益波动度及相关性分析》,现代财经,2001(11)
[43]李亚静,何跃,朱宏泉,《中国股市收益率与波动性长记忆性的实证研究》,系统工程理论与实践,2003(1)
[44]张兵,《证券市场波动不对称性的动态研究》,管理学报,2006(3)
[45]何晓光,朱永军,《中国A股市场收益波动的非对称性研究》,数理统计与管理,2007(26)
[46]池启水,刘晓雪,《人民币汇率波动特征实证研究》,统计与决策,2007(23)
[47]朱新玲,黎鹏,《汇率波动非对称效应的计量检验——基于非对称ARCH类模型》,统计教育,2008(7)
[48] Shah, Ajay, Zeileis, Achim, Patnaik, Ila. What is the new Chinese currency regime? Research Report Series / Department of Statistics and Mathematics,2005(23).
[49]徐剑刚,邵华,唐国兴,《人民币参考一篮子货币机制的实证分析》,上海财经大学学报,2007(1)
[50]周雅瑞,赵晓波,《基于GJR-GARCH模型的港币汇率波动不对称研究》,湖南工业大学学报,2009(6)
[51] Fama, E. F. The behavior of stock-market prices. Journal of Business, 1965, 38(1): 34-105.
[52] Zakoian, J. M. Threshold heteroskedastic model. Journal of Economic Dynamics and Control, 1994, 18: 931-955.
[53] Ding Zhuanxin, Granger. C. W. J, Engle, R. E. A long memory property of stock market returns and a new model. Journal of Empirical Finance, 1993, 1: 83-106.
[54] Brockwell, P. J. , Davis, R. A. Time series: theory and methods. Springer-Verlag, 1991.
[55] Granger, C. W. J. and Joyeux, R. An introduction to long-memory time series models and fractional differencing. Journal of Time Series Analysis, 1980, 1: 15-30.
[56] Hiemstra, C. J. and Jones, D. Another look at long memory in common stock returns. Journal of Empirical Finance, 1997, 4: 373-401.
[57] Andersen, T. G. and Bollerslev, T. Heterogeneous information arrivals and return volatility dynamics: uncovering the long-run in high frequency returns. Journal of Finance, American Finance Association, 1997, 52(3): 975-1005.
[58]陈梦根,《中国股市长期记忆效应的实证研究》,经济研究,2003
[59]刘纪显,陈建梁,张宗益,《汇率定价模型及人民币兑美元汇率研究》,管理科学学报,2005(6).