A Guide to Modeling Credit Term Structures

We give a comprehensive review of credit term structure modeling methodologies. The conventional approach to modeling credit term structure is summarized and shown to be equivalent to a particular type of the reduced form credit risk model, the fractional recovery of market value approach. We argue that the corporate practice and market observations do not support this approach. The more appropriate assumption is the fractional recovery of par, which explicitly violates the strippable cash flow valuation assumption that is necessary for the conventional credit term structure definitions to hold. We formulate the survival-based valuation methodology and give alternative specifications for various credit term structures that are consistent with market observations, and show how they can be empirically estimated from the observable prices. We rederive the credit triangle relationship by considering the replication of recovery swaps. We complete the exposition by presenting a consistent measure of CDS-Bond basis and demonstrate its relation to a static hedging strategy, which remains valid for non-par bonds and non-flat term structures of interest rates and credit risk.Comment: 54 pages, 13 figures (references fixed

The History of the Quantitative Methods in Finance Conference Series. 1992-2007

This report charts the history of the Quantitative Methods in Finance (QMF) conference from its beginning in 1993 to the 15th conference in 2007. It lists alphabetically the 1037 speakers who presented at all 15 conferences and the titles of their papers.

Mathematics of Quantitative Finance

The workshop on Mathematics of Quantitative Finance, organised at the Mathematisches Forschungsinstitut Oberwolfach from 26 February to 4 March 2017, focused on cutting edge areas of mathematical finance, with an emphasis on the applicability of the new techniques and models presented by the participants

Symmetry reductions of some non-linear 1+1 D and 2+1 D black-scholes models

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of requirements for the degree of Master of Science. May 30, 2016.In this dissertation, we consider a number of modi ed Black-Scholes equations being either non-linear or given in higher dimensions. In particular we focus on the non-linear Black-Scholes equation describing option pricing with hedging strategies in one case, and two dimensional models in the other. Classical Lie point symmetry techniques are employed in an attempt to construct exact solutions. Some large symmetry algebras are admitted. We proceeded by determining the one dimensional optimal systems of sub-algebras for the admitted Lie algebras. The elements of the optimal systems are used to reduce the number of variables by one. In some cases, exact solutions are constructed. For the cases for which exact solutions are di cult to construct, we employed the numerical solutions. Some simulations are observed and interpretedMT201

Discounting when income is stochastic and climate change policies

We introduce stochastic income into the standard exponential discounting model and study dependence of effective discount rates on the type of the underlying stochastic process and agent's current income level. If the income follows a process with i.i.d. increments effective discounting is exponential. If the income follows a mean reverting process, the shape of discount rate curves depends on the margin between the agent's current income and the long-run average. The model is used to study how the willingness to pay for investments in abatement technologies depends on the current wealth of a country

A Celebration of the Ties That Bind Us: Connections Between Actuarial Science and Mathematical Finance

The articles in this volume are contributed by scholars who are not only experts in areas of Actuarial Science (AS) and Mathematical Finance (MF), but also those who present diverse perspectives from both industry and academia. Topics from multiple areas, such as Stochastic Modeling, Credit Risk, Monte Carlo Simulation, and Pension Valuation, among others, that were maybe thought to be the domain of one type of risk manager, are shown time and again to have deep value to other areas of risk management as well. The articles in this collection, in my opinion, contribute techniques, ideas, and overviews of tools that folks in both AS and MF will find useful and interesting to implement in their work. It is also my hope that this collection will inspire future collaboration between those who seek an interdisciplinary approach to risk management

Glosarium Matematika

273 p.; 24 cm