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Upper Tail (upper + tail)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	50%

Selected Abstracts

Tail-dependence in stock-return pairs

INTELLIGENT SYSTEMS IN ACCOUNTING, FINANCE & MANAGEMENT, Issue 2 2002
Ines Fortin
The empirical joint distribution of return pairs on stock indices displays high tail-dependence in the lower tail and low tail-dependence in the upper tail. The presence of tail-dependence is not compatible with the assumption of (conditional) joint normality. The presence of asymmetric tail-dependence is not compatible with the assumption of a joint student-t distribution. A general test for one dependence structure versus another via the profile likelihood is described and employed in a bivariate GARCH model, where the joint distribution of the disturbances is split into its marginals and its copula. The copula used in the paper is such that it allows for the existence of lower tail-dependence and for asymmetric tail-dependence, and is such that it encompasses the normal or t-copula, depending on the benchmark tested. The model is estimated using bivariate data on a set of European stock indices. We find that the assumption of normal or student-t dependence is easily rejected in favour of an asymmetrically tail-dependent distribution. Copyright © 2002 John Wiley & Sons, Ltd. [source]

On the Rank-Size Distribution for Human Settlements

JOURNAL OF REGIONAL SCIENCE, Issue 1 2002
William J. Reed
An explanation for the rank-size distribution for human settlements based on simple stochastic models of settlement formation and growth is presented. Not only does the analysis of the model explain the rank-size phenomenon in the upper tail, it also predicts a reverse rank-size phenomenon in the lower tail. Furthermore it yields a parametric form (the double Pareto-lognormal distribution) for the complete distribution of settlement sizes. Settlement-size data for four regions (two in Spain and two in the U.S.) are used as examples. For these regions the lower tail rank-size property is seen to hold and the double Pareto-lognormal distribution shown to provide an excellent fit, lending support to the model and to the explanation for the rank-size law. [source]

The Distributional Heterogeneity of Growth Effects: Some Evidence

THE MANCHESTER SCHOOL, Issue 4 2003
Brendan M. Cunningham
This paper applies quantile regression and non-parametric density estimation techniques to international data on long-run economic growth. The approach reveals that previously identified drivers of growth vary in their impact across the conditional distribution of international growth. Specifically, these factors display disparate effects in conditional low-growth and high-growth contexts. The results suggest that there is a general bias underlying prior research. The incumbent drivers of growth exhibit relatively larger coefficients, in absolute value, on the upper tail of the conditional growth distribution. This set of stylized facts identifies factors that might alter the international distribution of growth. [source]

Decadal-scale changes in the tails of probability distribution functions of climate variables in Switzerland

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 10 2009
Martin Beniston
Abstract An analysis of several Swiss climatological sites reveals that a substantial change in the behaviour of pressure, minimum and maximum temperature extremes has occurred in the past two decades. Extreme cold tails defined by the 10% quantiles of temperature drop by a factor of 2 or 3, while the upper tails (beyond the 90% quantile) exhibit a four- or five-fold increase in all seasons. Pressure shows contrasting behaviour, with increases in wintertime highs and summertime lows, while precipitation shows little change. On the basis of the observed datasets, temperature biases related to extremes of pressure or precipitation have been computed, as well as for joint combinations of precipitation and pressure extremes. The most dominant bias is associated with periods without rainfall, during which temperatures are at least 1 °C warmer than otherwise. Changes in the behaviour of joint combinations of extreme pressure and precipitation regimes also have a discernible influence on temperatures. Copyright © 2008 Royal Meteorological Society [source]