Zobrazeno 1 - 10
of 116
pro vyhledávání: '"SHAW, WILLIAM T."'
Autor:
Shaw, William T.
We show how to reduce the problem of computing VaR and CVaR with Student T return distributions to evaluation of analytical functions of the moments. This allows an analysis of the risk properties of systems to be carefully attributed between choices
Externí odkaz:
http://arxiv.org/abs/1102.5665
Autor:
Shaw, William T.
We develop the idea of using Monte Carlo sampling of random portfolios to solve portfolio investment problems. In this first paper we explore the need for more general optimization tools, and consider the means by which constrained random portfolios
Externí odkaz:
http://arxiv.org/abs/1008.3718
Autor:
Shaw, William T.
In applied mathematics generally and fluid dynamics in particular, the role of complex variable methods is normally confined to two-dimensional motion and the association of points with complex numbers via the assignment w = x+i y. In this framework
Externí odkaz:
http://arxiv.org/abs/1005.4184
Autor:
Shaw, William T., McCabe, Jonathan
In mathematical finance and other applications of stochastic processes, it is frequently the case that the characteristic function may be known but explicit forms for density functions are not available. The simulation of any distribution is greatly
Externí odkaz:
http://arxiv.org/abs/0903.1592
Autor:
Shaw, William T.
This paper proposes a solution to Stokes' paradox for asymptotically uniform viscous flow around a cylinder. The existence of a {\it global} stream function satisfying a perturbative form of the two-dimensional Navier-Stokes equations for low Reynold
Externí odkaz:
http://arxiv.org/abs/0901.3621
This article presents differential equations and solution methods for the functions of the form $Q(x) = F^{-1}(G(x))$, where $F$ and $G$ are cumulative distribution functions. Such functions allow the direct recycling of Monte Carlo samples from one
Externí odkaz:
http://arxiv.org/abs/0901.0638
Autor:
Shaw, William T., Buckley, Ian R. C.
Motivated by the need for parametric families of rich and yet tractable distributions in financial mathematics, both in pricing and risk management settings, but also considering wider statistical applications, we investigate a novel technique for in
Externí odkaz:
http://arxiv.org/abs/0901.0434