Managing Derivative Exposure

TL;DR

This paper introduces a derivative exposure management method that uses subjective and implied probabilities to optimize valuation differences while respecting risk constraints, with graphical solutions for low-dimensional cases.

Contribution

It proposes a novel approach combining subjective and implied probabilities for derivative risk management, including a graphical optimization method for simple cases.

Findings

Effective graphical optimization for 2D and 3D cases

Risk measures derived from subjective distributions

Maximizing valuation differences under risk constraints

Abstract

We present an approach to derivative exposure management based on subjective and implied probabilities. We suggest to maximize the valuation difference subject to risk constraints and propose a class of risk measures derived from the subjective distribution. We illustrate this process with specific examples for the two and three dimensional case. In these cases the optimization can be performed graphically.