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Adjoints and Automatic (Algorithmic) Differentiation in Computational Finance
Adjoints and Automatic Differentiation Computational Finance
2011/7/19
Two of the most important areas in computational finance: Greeks and, respectively, calibration, are based on efficient and accurate computation of a large number of sensitivities. This paper gives an...
Developing countries ?trends, differentiation
developing countries classification differentiation trends of development
2014/2/27
Socio-economic backwardness is usually defined by common characteristics or classification. The differences between the DMEs and DCs in the case of resources (prevalence of DCs) and in the case of out...
Fast Correlation Greeks by Adjoint Algorithmic Differentiation
Algorithmic Di erentiation Monte Carlo Simulations Derivatives Pricing Credit Derivatives
2010/10/19
We show how Adjoint Algorithmic Differentiation (AAD) allows an extremely efficient calculation of correlation Risk of option prices computed with Monte Carlo simulations. A key point in the construct...
Fast Correlation Greeks by Adjoint Algorithmic Differentiation
Algorithmic Dierentiation Monte Carlo Simulations Derivatives Pricing Credit Derivatives
2010/4/28
We show how Adjoint Algorithmic Differentiation (AAD) allows an extremely efficient calculation of correlation Risk of option prices computed with Monte Carlo simulations. A key point in the construct...
Emergence of product differentiation from consumer heterogeneity and asymmetric information
Emergence product differentiation consumer heterogeneity asymmetric information
2010/12/17
We introduce a fully probabilistic framework of consumer product choice based on quality assessment. It allows us to capture many aspects of marketing such as partial information asymmetry, quality di...