In a general jump-diffusion Radon-Nikodym setup with stochastic Girsanov processes, we derive optimal equivalent probability measures. Optimality is measured in terms of minimum relative entropy and also by more general divergence concepts. We further prove an anticipative sufficient stochastic...

In this article we provide a new definition of concave conditional performance measures. We prove a duality to conditional risk measures. New dynamic performance measures based on dynamic risk measures are established. We are able to derive dynamic bid and ask prices with respect to a stochastic...

Under mild assumptions, we recover the model-free conditional minimum variance projection of the pricing kernel on various tradeable realized moments of market returns. Recovered conditional moments predict future realizations and give insight into the cyclicality of equity premia, variance risk...

In this paper, we study the out-of-sample properties of robust empirical optimization and develop a theory for data-driven calibration of the “robustness parameter” for worst-case maximization problems with concave reward functions. Building on the intuition that robust optimization reduces...

We formulate a distributionally robust optimization problem where the deviation of the alternative distribution is controlled by a φ-divergence penalty in the objective, and show that a large class of these problems are essentially equivalent to a mean-variance problem. We also show that while...

In terms of regulatory and economic capital, credit risk is the most significant risk faced by banks. We implement a credit risk model - based on publicly available information - with the aim of developing a tool to monitor credit risk in a sample of large and complex banking groups (LCBGs) in...

In this paper we show how risk-averse reinforcement learning can be used to hedge options. We apply a state-of-the-art risk-averse algorithm: Trust Region Volatility Optimization (TRVO) to a vanilla option hedging environment, considering realistic factors such as discrete time and transaction...

The aim of this paper is to illustrate the determination of the Economic Order Quantity (EOQ) or Economic Number of Orders (ENO) when the Total Ordering Cost (TOC) and Total Handling Cost (THC) are not equally the same. For this purpose, two assumptions of the basic EOQ model - (a) the constant...

The paper addresses the problem of providing a framework and an algorithm to evaluate super and sub replicating prices, for European options, having interesting risk-reward characteristics. A general operational framework is put forward and illustrated by an algorithmic construction of...

We approach the continuous-time mean-variance (MV) portfolio selection with reinforcement learning (RL). The problem is to achieve the best tradeoff between exploration and exploitation, and is formulated as an entropy-regularized, relaxed stochastic control problem. We prove that the optimal...