Robust Efficient Frontier Analysis with a Separable Uncertainty Model

Mean-variance (MV) analysis is often sensitive to model mis-specification or uncertainty, meaning that the MV efficient portfolios constructed with an estimate of the model parameters (i.e., the expected return vector and covariance of asset returns) can give very poor performance for another set of parameters that is similar and statistically hard to distinguish from the … Read more

A Minimax Theorem with Applications to Machine Learning, Signal Processing, and Finance

This paper concerns a fractional function of the form $x^Ta/\sqrt{x^TBx}$, where $B$ is positive definite. We consider the game of choosing $x$ from a convex set, to maximize the function, and choosing $(a,B)$ from a convex set, to minimize it. We prove the existence of a saddle point and describe an efficient method, based on … Read more

Sample Average Approximation of Expected Value Constrained Stochastic Programs

We propose a sample average approximation (SAA) method for stochastic programming problems involving an expected value constraint. Such problems arise, for example, in portfolio selection with constraints on conditional value-at-risk (CVaR). Our contributions include an analysis of the convergence rate and a statistical validation scheme for the proposed SAA method. Computational results using a portfolio … Read more

Operations Risk Management by Planning Optimally the Qualified Workforce Capacity

Operational risks are defined as risks of human origin. Unlike financial risks that can be handled in a financial manner (e.g. insurances, savings, derivatives), the treatment of operational risks calls for a “managerial approach”. Consequently, we propose a new way of dealing with operational risk, which relies on the well known aggregate planning model. To … Read more

Satisficing measures for analysis of risky positions

In this work we introduce a class of measures for evaluating the quality of financial positions based on their ability to achieve desired financial goals. In the spirit of Simon (1959), we call these measures satisficing measures and show that they are dual to classes of risk measures. This approach has the advantage that aspiration … Read more

An estimation-free, robust conditional value-at-risk portfolio allocation model

We propose a novel optimization model for risk-averse investors to obtain robust solutions for portfolio allocation problems. Unlike related models in the literature, no historical data or statistical estimation techniques are used to compute the parameters of the model. Instead, the parameters are directly obtained from current prices of options on the assets being considered. … Read more

The Variational Inequality Approach for Solving Spatial Auction Problems with Joint Constraints

We consider a problem of managing a system of spatially distributed markets under capacity and balance constraints and show that solutions of a variational inequality enjoy auction principle properties implicitly. This enables us to develop efficient tools both for derivation of existence and uniqueness results and for creation of solution methods. Citation Kazan University, Kazan, … Read more

REVERSE-ENGINEERING COUNTRY RISK RATINGS: COMBINATORIAL NON-RECURSIVE MODEL

The central objective of this paper is to develop a transparent, consistent, self-contained, and stable country risk rating model, closely approximating the country risk ratings provided by Standard and Poor’s (S&P). The models should be non-recursive, i.e., they should not rely on the previous years’ S&P ratings. The selected set of variables includes not only … Read more

Pricing A Class of Multiasset Options using Information on Smaller Subsets of Assets

In this paper, we study the pricing problem for the class of multiasset European options with piecewise linear convex payoff in the asset prices. We derive a simple upper bound on the price of this option by constructing a static super-replicating portfolio using cash and options on smaller subsets of assets. The best upper bound … Read more

Covering models with time-dependent demand

In this paper a covering model for locating facilities with time-dependent demand is introduced. Not only the facility locations, but also the instants at which such facilities become operative, are considered as decision variables in order to determine the maximal-profit decision. Expressed as a mixed nonlinear integer program, structural properties are derived for particular demand … Read more