Theory and Applications of Robust Optimization

In this paper we survey the primary research, both theoretical and applied, in the area of Robust Optimization (RO). Our focus is on the computational attractiveness of RO approaches, as well as the modeling power and broad applicability of the methodology. In addition to surveying prominent theoretical results of RO, we also present some recent results linking RO to adaptable models for multi-stage decision-making problems. Finally, we highlight applications of RO across a wide spectrum of domains, including finance, statistics, learning, and various areas of engineering.Comment: 50 page

Applying the Grinblatt-Titman and the Conditional (Ferson-Schadt) Performance Measures: The Case of Industry Rotation Via the Dynamic Investment Model.

Nearly any standard financial model concludes that two assets with identical cash flows must sell for the same price. Alas, closed-end mutual fund company share prices seem to violate this fundamental tenant. Even when one considers several standard frictions, such as taxes and agency costs, classical financial models cannot explain the large persistent discounts found within the data. While the standard financial markets model may not explain the existence of large closed-end fund discounts, this paper shows that a rather close version of it does. In an otherwise frictionless market, if asset supplies vary randomly over time and agents possess finite lives, a closed-end mutual fund's stock price may not track its net asset value. Furthermore, the analysis provides a number of conditions under which these discrepancies will lead to the existence of systematic discounts for the mutual fund's shares. In addition, the model provides predictions regarding the correlation between current closed-end fund discounts and current changes in stock prices and future changes in corporate productivity. As the analysis shows, the same parameter values that lead to systematic discounts also lead to other fund price characteristics that resemble many of the results found within empirical studies.

Precautionary saving and portfolio allocation: DP by GMM

There is much research on consumption-savings problems with risky labor income and a constant interest rate and also on portfolio allocation with risky returns but nonstochastic labor income. Less is known quantitatively about the interaction between the two forms of risk. Under CRRA utility, undiversifiable income risk should be reflected in both savings rates and portfolio allocations. To quantify these effects in a model of consumption and portfolio choice, we adopt a semi-parametric projection method for solving dynamic programmes, based on generalized method of moments estimation of the parameters of approximate decision rules. We find that background income risk does affect optimal portfolios but that this effect may be difficult to detect empirically.portfolio theory, precautionary saving

Linear vector optimization and European option pricing under proportional transaction costs

A method for pricing and superhedging European options under proportional transaction costs based on linear vector optimisation and geometric duality developed by Lohne & Rudloff (2014) is compared to a special case of the algorithms for American type derivatives due to Roux & Zastawniak (2014). An equivalence between these two approaches is established by means of a general result linking the support function of the upper image of a linear vector optimisation problem with the lower image of the dual linear optimisation problem

Optimal bank portfolio choice under fixed-rate deposit insurance

An analysis of the investment decisions of a bank whose deposits are fully insured under fixed-rate insurance, showing how banks dynamically adjust their investment portfolios in response to market information and how this flexibility affects both investment decisions and the fair cost of deposit insurance.Deposit insurance ; Bank investments

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.