On the controversy over tailweight of distributions

Although understanding tail behavior of distributions is important in many areas, such as telecommunications network analysis and finance, there is considerable controversy about distinctions between exponential-type and power-type tails. This paper explains why the distinctions are surprisingly difficult for popular methods in the literature, and why particularly large samples are needed for clear discrimination.

[1]  Luc Devroye,et al.  On the impossibility of estimating densities in the extreme tail , 1999 .

[2]  M Kac,et al.  Some mathematical models in science. , 1969, Science.

[3]  C. Heyde A RISKY ASSET MODEL WITH STRONG DEPENDENCE THROUGH FRACTAL ACTIVITY TIME , 1999 .

[4]  S. Rachev,et al.  Stable Paretian Models in Finance , 2000 .

[5]  Karl Sigman Editorial Introduction - Queues with Heavy-Tailed Distributions. , 1999 .

[6]  Azer Bestavros,et al.  Self-similarity in World Wide Web traffic: evidence and possible causes , 1997, TNET.

[7]  Adrian Pagan,et al.  The econometrics of financial markets , 1996 .

[8]  E CrovellaMark,et al.  Self-similarity in World Wide Web traffic , 1996 .

[9]  David R. Cox,et al.  Role of Models in Statistical Analysis , 1990 .

[10]  Jun Pan,et al.  Analytical value-at-risk with jumps and credit risk , 2001, Finance Stochastics.

[11]  P. Glasserman,et al.  Stochastic networks : stability and rare events , 1997 .

[12]  N. L. Johnson,et al.  Continuous Univariate Distributions. , 1995 .

[13]  A. M. Walker A Note on the Asymptotic Distribution of Sample Quantiles , 1968 .

[14]  Steven Kou,et al.  A Jump Diffusion Model for Option Pricing , 2001, Manag. Sci..

[15]  N. Shephard,et al.  Non‐Gaussian Ornstein–Uhlenbeck‐based models and some of their uses in financial economics , 2001 .

[16]  M. Crovella,et al.  Heavy-tailed probability distributions in the World Wide Web , 1998 .

[17]  Paul Glasserman,et al.  Portfolio Value‐at‐Risk with Heavy‐Tailed Risk Factors , 2002 .

[18]  Peter W. Glynn,et al.  Parametric estimation of tail probabilities for the single-server queue , 1998 .

[19]  Karl Sigman,et al.  Appendix: A primer on heavy-tailed distributions , 1999, Queueing Syst. Theory Appl..

[20]  E. Eberlein,et al.  Hyperbolic distributions in finance , 1995 .

[21]  S. Kou,et al.  Modeling growth stocks via birth-death processes , 2003, Advances in Applied Probability.

[22]  R. Adler,et al.  A practical guide to heavy tails: statistical techniques and applications , 1998 .

[23]  Jin Cao,et al.  Internet Traffic Tends Toward Poisson and Independent as the Load Increases , 2003 .

[24]  E. Platen,et al.  Subordinated Market Index Models: A Comparison , 1997 .

[25]  V. Plerou,et al.  A theory of power-law distributions in financial market fluctuations , 2003, Nature.

[26]  P. Praetz,et al.  The Distribution of Share Price Changes , 1972 .

[27]  S. Resnick Heavy tail modeling and teletraffic data: special invited paper , 1997 .

[28]  Shuangzhe Liu,et al.  EMPIRICAL REALITIES FOR A MINIMAL DESCRIPTION RISKY ASSET MODEL. THE NEED FOR FRACTAL FEATURES , 2001 .

[29]  Sidney I. Resnick,et al.  Heavy Tail Modelling and Teletraffic Data , 1995 .

[30]  P. Glasserman,et al.  Variance Reduction Techniques for Estimating Value-at-Risk , 2000 .

[31]  Mark A. McComb A Practical Guide to Heavy Tails , 2000, Technometrics.

[32]  C. Klüppelberg,et al.  Modelling Extremal Events , 1997 .