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Interplay between Distributional and Temporal Dependence. An Empirical Study with High-frequency Asset Returns

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 References

  1. Alexander, C.: Market Models: A Guide to Financial Data Analysis. John Wiley and Sons (2001)

    Google Scholar 

  2. Andersen, T.G., Bollerslev, T., Diebold, F.X., Labys, P.: The distribution of exchange rate volatility. Journal of the American Statistical Association, 96, 42-55 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  3. Andersen, T.G., Bollerslev, T.: Intraday periodicity and volatility persistence in financial markets. Journal of Empirical Finance, 4(2-3), 115-158 (1997)

    Article  Google Scholar 

  4. Andersen, T. G., Bollerslev, T.: Deutsche Mark-Dollar volatility: intraday ac-tivity patterns, macroeconomic announcements, and longer run dependencies. Journal of Finance, 53(1), 219-265 (1998)

    Article  Google Scholar 

  5. Ané, T., Kharoubi, C.: Dependence Structure and Risk Measure. Journal of Business, 76(3), 411-438 (2003)

    Article  Google Scholar 

  6. Areal, N.P., Taylor, S.J.: The realised volatility of FTSE-100 futures prices. Forthcoming in Journal of Futures Markets, 22 (2002)

    Google Scholar 

  7. Bai, X., Russell, J.R., Tiao, G.C.: Beyond Merton’s utopia: effects of non-normality and dependence on the precision of variance estimates using high-frequency financial data. Graduate School of Business, University of Chicago (2000)

    Google Scholar 

  8. Baringhaus, L.: Testing for spherical symmetry of a multivariate distribution. Annals of Statistics 19, 899-917 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  9. Barndorff-Nielsen, O.E., Shephard, N.: Econometric analysis of realised volatil-ity and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society, Series B, 64, 253-280 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  10. Barndorff-Nielsen, O.E., Shephard, N.: Econometric analysis of realised covari-ation: high frequency covariance, regression and correlation in financial eco-nomics. Econometrica, 72, 885-925 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  11. Basel Committee on Banking Supervision: The New Basel Capital Accord. BIS Basel, Switzerland URL: http://www.bis.org/bcbs (2003)

  12. Beran, R.: Testing for ellipsoidal symmetry of a multivariate density. Annals of Statistics, 7, 150-162 (1979)

    Article  MATH  MathSciNet  Google Scholar 

  13. Bingham, N.H., Kiesel,R.: Modelling asset return with hyperbolic distribu-tions. In: Knight, J., Satchell, S. (eds.) Asset return distributions. Butterworth-Heinemann, pp. 1-20 (2001)

    Google Scholar 

  14. Bingham, N.H., Kiesel, R.: Semi-parametric modelling in finance: theoretical foundation. Quantitative Finance 2, 241-250 (2002)

    Article  MathSciNet  Google Scholar 

  15. Bingham, N.H., Kiesel, R., Schmidt, R.: Semi-parametric modelling in Finance: Econometric applications. Quantitative Finance, 3(6), 426-441 (2003)

    Article  MathSciNet  Google Scholar 

  16. Bluhm, C., Overbeck, L., Wagner, C.: An Introduction to Credit Risk Modelling. Chapman & Hall (2003)

    Google Scholar 

  17. Bollerslev, T., Engle, R.F., Wooldridge, J. M.: A Capital-Asset Pricing Model with Time-Varying Covariances. Journal of Political Economy, 96, 116-131 (1988)

    Article  Google Scholar 

  18. Bollerslev, T.: Generalized Autoregressive Conditional Heteroskedasticity. Jour- nal of Econometrics, 31, 307-327 (1986)

    MATH  MathSciNet  Google Scholar 

  19. Bouyé, E., Durrleman, V., Nikeghbali, A., Riboulet, G., Roncalli, T.: Copu-las for finance: A reading guide and some applications. Groupe de Recherche Opérationnelle, Crédit Lyonnais, Technical report (2000)

    Google Scholar 

  20. Breymann, W., Dias, A., Embrechts, P.: Dependence structures for multivariate high-frequency data in finance. Quantitative Finance, 3(1), 1-16 (2003)

    Article  MathSciNet  Google Scholar 

  21. Campbell, J., Lo, A., MacKinlay, C.: The Econometrics of Financial Markets. Princeton University Press, New Jersey (1997)

    MATH  Google Scholar 

  22. Campbell, R., Koedijk, K., Kofman, P.: Increased Correlation in Bear Markets. Financial Analysts Journal, Jan-Feb, 87-94 (2002)

    Google Scholar 

  23. Dacorogna, M.M., Gençay, R., Müller, U.A., Olsen, R.B., Pictet, O.V.: An In-troduction to HighFrequency Finance. Academic Press, San Diego (2001)

    Google Scholar 

  24. Darsow, W., Nguyen, B., Olsen, E.: Copulas and Markov Processes. Illinois Journal of Mathematics, 36, 600-642 (1992)

    MATH  MathSciNet  Google Scholar 

  25. De Haan, L., Stadtmüller, U.: Generalized regular variation of second order. Journal of the Australian Mathematical Society, 61, 381-395 (1996)

    Article  MATH  Google Scholar 

  26. Deheuvels, P.: La fonction de dépendance empirique et ses propriétés. Acad. Roy. Belg., Bull. C1 Sci. 5ième sér, 65, 274-292 (1979)

    MATH  MathSciNet  Google Scholar 

  27. Deheuvels, P.: A nonparametric test for independence. Pub. Inst. Stat. Univ. Paris, 26(2), 29-50 (1981)

    MATH  MathSciNet  Google Scholar 

  28. Dehling, H., Mikosch, T., Sörensen, M.: Empirical Process Techniques for De- pendent Data. Birkhäuser Verlag (2002)

    Google Scholar 

  29. Ding, Z., Granger, C.W.J.: Modeling Volatility Persistence of Speculative Re-turns: A New Approach. Journal of Econometrics, 73, 185-215 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  30. Eberlein, E.: Application of generalized hyperbolic Lévy motions to finance. In: Barndorff-Nielsen, O., Mikosch, T., Resnick, S. (eds.) Lévy Processes: Theory and Applications. Birkhäuser Verlag, pp. 319-337 (2001)

    Google Scholar 

  31. Embrechts, P., McNeil, A., Straumann, D.: Correlation and Dependency in Risk Management: Properties and Pitfalls. In: Dempster, M.A.H. (ed.) Risk Man-agement: Value at Risk and Beyond. Cambridge University Press, pp. 176-223 (2002)

    Google Scholar 

  32. Embrechts, P., Lindskog, F., McNeil, A.: Modelling Dependence with Copulas and Applications to Risk Management. In: Rachev, S. (ed.) Handbook of Heavy Tailed Distributions in Finance. Elsevier, pp. 329-384 (2001)

    Google Scholar 

  33. Fang, K.T., Kotz, S., Ng, K.W.: Symmetric multivariate and related distribu- tions. Chapman & Hall, London (1990)

    Google Scholar 

  34. Fermanian, J.D.: Goodness of fit tests for copulas, Working Paper CREST 2003

    Google Scholar 

  35. Forthcoming in J. Multivariate Analysis (2003)

    Google Scholar 

  36. Fermanian, J.D., Scaillet, O.: Some statistical pitfalls in copula modeling for financial applications. Technical report (2004)

    Google Scholar 

  37. Fermanian, J.D., Radulović, D., Wegkamp, M.: Weak convergence of empirical copula processes. Working Paper CREST 2002-06, Forthcoming in Bernoulli (2002)

    Google Scholar 

  38. Frahm, G., Junker, M., Schmidt, R.: Estimating the Tail Dependence Coeffi-cient. Caesar Center Bonn, URL: http://stats.lse.ac.uk/schmidt, Technical Re-port 38 (2003)

  39. Frey, R., McNeil, A.: Modelling dependent defaults. ETH Zuerich, http://e- collection.ethbib.ethz.ch/show?type=bericht&nr=273, Working Paper (2001)

  40. Gänssler, P., Stute, W.: Seminar on Empirical Processes. DMV Seminar 9, Birkhäuser, Basel (1987)

    Google Scholar 

  41. Genest, C., Rémillard, B.: Tests of Independence and Randomness Based on the Empirical Copula Process. Test, 12(1), in print (2004)

    Google Scholar 

  42. Genest, C., Rivest, L.P.: Statistical inference procedures for bivariate archimedean copulas. Journal of the American Statistical Association, 88, 1034-1043(1993)

    Article  MATH  MathSciNet  Google Scholar 

  43. Genest, C., Ghoudi, K., Rivest, L.P.: A semiparametric estimation procedure of dependence parameters in multivariate families of distributions. Biometrika, 82,543-552 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  44. Goorgergh, R.W.J., Genest, C., Werker, B.: Multivariate Option Pricing Using Dynamic Copula Models, Working Paper (2004)

    Google Scholar 

  45. Joe, H.: Multivariate Models and Dependence Concepts. Chapman and Hall, London (1997)

    MATH  Google Scholar 

  46. Junker, M., May, A.: Measurement of aggregate risk with copulas. Technical report, Caesar Center Bonn (2002)

    Google Scholar 

  47. Karolyi, G.A., Stulz, R.M.: Why Do Markets Move Together? An Investigation of U.S.-Japan Stock Return Comovements. Journal of Finance, 51, 951-989 (1996)

    Article  Google Scholar 

  48. Laurent, J.-P., Gregory, J.: Basket Default Swaps, CDO‘s and Factor Copulas. Working paper (2003)

    Google Scholar 

  49. Li, D.X.: On Default Correlation: A Copula Function Approach. Journal of Fixed Income, 9, 43-54 (2000)

    Article  Google Scholar 

  50. Longin, F., Solnik, B.: Extreme Correlation of International Equity Markets. Journal of Finance, LVI, 649-676 (2001)

    Google Scholar 

  51. Madan, D.B., Seneta, E.: The Variance-Gamma (VG) model for share market returns. Journal of Business, 511-524 (1990)

    Google Scholar 

  52. Maheu, J.M., McCurdy, T.H.: Nonlinear features of realised FX volatility., forth-coming in Economics and Statistics, 83 (2001)

    Google Scholar 

  53. Malevergne, Y., Sornette, D.: Minimizing Extremes. RISK, November issue, 129-133 (2002)

    Google Scholar 

  54. Manzotti, A., Perez, F.J., Quiroz, A.J.: A statistic for testing the null hypothesis of elliptical symmetry. Journal of Multivariate Analysis, 81, 274-285 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  55. Martens, M., Chang, Y.C., Taylor, S.J.: A comparison of seasonal adjustment methods when forecasting intraday volatility. Journal of Financial Res., 15(2), 283-299 (2002)

    Article  Google Scholar 

  56. Nelsen, R.B.: An Introduction to Copulas. Springer, New York (1999)

    MATH  Google Scholar 

  57. Ong, M.K.: Internal Credit Risk Models. Risk Books, Haymarket (1999)

    Google Scholar 

  58. Patton, A.: Modelling Time-Varying Exchange Rate Dependence Using the Con- ditional Copula. UCSD, Working Paper 2001-09 (2001)

    Google Scholar 

  59. Schmidt, R.: Tail dependence for elliptically contoured distributions. Mathe-matical Methods of Operations Research, 55(2), 301-327 (2002)

    Article  MATH  Google Scholar 

  60. Schmidt, R., Stadtmüller, U.: Nonparametric estimation of tail dependence. London School of Economics, www.lse.ac.uk/collections/statistics, Research re-port 101 (2003)

  61. Schönbucher, P.: Credit Derivatives Pricing Models. Wiley Publ. (2003)

    Google Scholar 

  62. Sklar, A.: Fonctions de répartition à n dimensions et leurs marges. Publ. Inst. Statist. Univ. Paris, 8, 229-231 (1959)

    MathSciNet  Google Scholar 

  63. Stute, W.: The oscillation behavior of empirical processes: The multivariate case. Annals of Probability, 12(2), 361-379 (1984)

    Article  MATH  MathSciNet  Google Scholar 

  64. Van der Vaart, A.W., Wellner, J.A.: Weak Convergence and Empirical Processes. Springer, New York (1996)

    MATH  Google Scholar 

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Bingham, N.H., Schmidt, R. (2006). Interplay between Distributional and Temporal Dependence. An Empirical Study with High-frequency Asset Returns. In: From Stochastic Calculus to Mathematical Finance. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30788-4_4

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