Self-similarity in World Wide Web traffic: evidence and possible causes
IEEE/ACM Transactions on Networking (TON)
Heavy-tailed probability distributions in the World Wide Web
A practical guide to heavy tails
Appendix: A primer on heavy-tailed distributions
Queueing Systems: Theory and Applications
A Jump-Diffusion Model for Option Pricing
Management Science
Variance Reduction Techniques for Estimating Value-at-Risk
Management Science
Simulating Sensitivities of Conditional Value at Risk
Management Science
Quantile Sensitivity Estimation
NET-COOP '09 Proceedings of the 3rd Euro-NF Conference on Network Control and Optimization
Test of fit for a Laplace distribution against heavier tailed alternatives
Computational Statistics & Data Analysis
Queueing Systems: Theory and Applications
Option Pricing Under a Mixed-Exponential Jump Diffusion Model
Management Science
Conditional value-at-risk in portfolio optimization: Coherent but fragile
Operations Research Letters
Tailweight, quantiles and kurtosis: A study of competing distributions
Operations Research Letters
Pricing double-barrier options under a flexible jump diffusion model
Operations Research Letters
Interfaces
External Risk Measures and Basel Accords
Mathematics of Operations Research
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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.