Carlos A. Braumann

Prof. Dr. Carlos A. Braumann

Departamento de Matemática, Escola de Ciências e Tecnologia, Universidade de Évora
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orcid

Research Focus & Metrics

Academic Career Length

47Years (1980-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2010 in Computers & Mathematics with Applications
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Journal Article
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LVL. Villafuerte
L. Villafuerte
Carlos A. BraumannCarlos A. Braumann
Carlos A. Braumann
JCJ.-C. Cortés
J.-C. Cortés
LJL. Jódar
L. Jódar



1 March 2007 in Mathematical Biosciences
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Journal Article
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Carlos A. BraumannCarlos A. Braumann
Carlos A. Braumann

1 March 1980 in Systematic Biology
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Journal Article
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RSRobert R. Sokal
Robert R. Sokal
Carlos A. BraumannCarlos A. Braumann
Carlos A. Braumann
Significance tests for coefficients of variation and variability profiles. Syst. Zool. 29:50–66.—The distribution of sample estimates of the coefficient of variation is studied analytically and by Monte Carlo simulation. Derivations are given for the expected value of a coefficient of variation and for its standard error. Various proposed standard errors for coefficients of variation are evaluated. Standard errors are derived for differences between coefficients of variation for samples of independent and correlated characters. Methods are proposed for testing the homogeneity of sets of independent and correlated coefficients of variation. Tests of homogeneity of variability profiles as well as for parallelism of such profiles are furnished.

16 May 2013 in Quantitative Finance
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Journal Article
Closed access
MLManuela Coelho Larguinho
Manuela Coelho Larguinho
JDJosé Carlos Dias
José Carlos Dias
Carlos A. BraumannCarlos A. Braumann
Carlos A. Braumann
Pricing options and evaluating Greeks under the constant elasticity of variance (CEV) model requires the computation of the non-central chi-square distribution function. In this article, we compare the performance, in terms of accuracy and computational time, of alternative methods for computing such probability distributions against an externally tested benchmark. In addition, we present closed-form solutions for computing Greek measures under the unrestricted CEV option pricing model, thus being able to accommodate direct leverage effects as well as inverse leverage effects that are frequently observed in options markets.