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Dynamic asset (and liability) management under market and credit risk
We introduce a modelling paradigm which integrates credit risk and market
risk in describing the random dynamical behaviour of the underlying fixed income assets.
We then consider an asset and liability management (ALM) problem and develop a mul-
tistage stochastic programming model which focuses on optimum risk decisions. These
models exploit the dynamical multiperiod structure of credit risk and provide insight
into the corrective recourse decisions whereby issues such as the timing risk of default is
appropriately taken into consideration. We also present a index tracking model in which
risk is measured (and optimised) by the CVaR of the tracking portfolio in relation to the
index. Both in- and out-of-sample (backtesting) experiments are undertaken to validate
our approach. In this way we are able to demonstrate the feasibility and flexibility of
the chosen framework
Moody's Correlated Binomial Default Distributions for Inhomogeneous Portfolios
This paper generalizes Moody's correlated binomial default distribution for
homogeneous (exchangeable) credit portfolio, which is introduced by Witt, to
the case of inhomogeneous portfolios. As inhomogeneous portfolios, we consider
two cases. In the first case, we treat a portfolio whose assets have uniform
default correlation and non-uniform default probabilities. We obtain the
default probability distribution and study the effect of the inhomogeneity on
it. The second case corresponds to a portfolio with inhomogeneous default
correlation. Assets are categorized in several different sectors and the
inter-sector and intra-sector correlations are not the same. We construct the
joint default probabilities and obtain the default probability distribution. We
show that as the number of assets in each sector decreases, inter-sector
correlation becomes more important than intra-sector correlation. We study the
maximum values of the inter-sector default correlation. Our generalization
method can be applied to any correlated binomial default distribution model
which has explicit relations to the conditional default probabilities or
conditional default correlations, e.g. Credit Risk, implied default
distributions. We also compare some popular CDO pricing models from the
viewpoint of the range of the implied tranche correlation.Comment: 29 pages, 17 figures and 1 tabl
Portfolio selection problems in practice: a comparison between linear and quadratic optimization models
Several portfolio selection models take into account practical limitations on
the number of assets to include and on their weights in the portfolio. We
present here a study of the Limited Asset Markowitz (LAM), of the Limited Asset
Mean Absolute Deviation (LAMAD) and of the Limited Asset Conditional
Value-at-Risk (LACVaR) models, where the assets are limited with the
introduction of quantity and cardinality constraints. We propose a completely
new approach for solving the LAM model, based on reformulation as a Standard
Quadratic Program and on some recent theoretical results. With this approach we
obtain optimal solutions both for some well-known financial data sets used by
several other authors, and for some unsolved large size portfolio problems. We
also test our method on five new data sets involving real-world capital market
indices from major stock markets. Our computational experience shows that,
rather unexpectedly, it is easier to solve the quadratic LAM model with our
algorithm, than to solve the linear LACVaR and LAMAD models with CPLEX, one of
the best commercial codes for mixed integer linear programming (MILP) problems.
Finally, on the new data sets we have also compared, using out-of-sample
analysis, the performance of the portfolios obtained by the Limited Asset
models with the performance provided by the unconstrained models and with that
of the official capital market indices
A global optimization problem in portfolio selection
“The original publication is available at www.springerlink.com”. Copyright Springer. DOI: 10.1007/s10287-006-0038-4This paper deals with the issue of buy-in thresholds in portfolio optimization using the Markowitz approach. Optimal values of invested fractions calculated using, for instance, the classical minimum-risk problem can be unsatisfactory in practice because they lead to unrealistically small holdings of certain assets. Hence we may want to impose a discrete restriction on each invested fraction y i such as y i > y min or y i = 0. We shall describe an approach which uses a combination of local and global optimization to determine satisfactory solutions. The approach could also be applied to other discrete conditions—for instance when assets can only be purchased in units of a certain size (roundlots).Peer reviewe