This article reviews several frameworks commonly used in modelling heavy-tailed densities and distributions in economics, finance, risk management, econometrics and statistics. The results and conclusions discussed in the article indicate that the presence of heavy tails can either reinforce or reverse the implications of a number of models in these fields, depending on the degree of heavy-tailedness.
KeywordsHeavy-tailed densities Heavy-tailed distributions Power laws Stable distributions Mean Variance Moments Semi-heavy tails Diversification Portfolio choice Value at risk Linear estimators Sample mean Efficiency Regression Robustness Dependence α-symmetric distributions Models with common shocks
JEL ClassificationC10 C13 C16 G11
The author gratefully acknowledges partial support by NSF grant SES-0821024, a Harvard Academy Junior Faculty Department grant and the Warburg Research Funds (Department of Economics, Harvard University).
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