We formulate the open-loop control framework for time-consistent mean-variance (TCMV) portfolio problems in incomplete markets with stochastic volatility (SV). We offer the existence and uniqueness results of the TCMV equilibrium controls for general SV models and derive explicit closed-form...

We investigate financial markets under model risk caused by uncertain volatilities. For this purpose we consider a financial market that features volatility uncertainty. To have a mathematical consistent framework we use the notion of G-expectation and its corresponding G-Brownian motion...

This paper treats the risk-averse optimal portfolio problem with consumption in continuous time for a stochastic-jump-volatility, jump-diffusion (SJVJD) model of the underlying risky asset and the volatility. The new developments are the use of the SJVJD model with...

The risky assets prices of the bi-variate model are reviewed under the hegemonize concentration filtered physical probability space. In the stochastic variance of the Cox-Ingersoll-Ross process. The Mean-variance hedging expanse on the Föllmer-Schweizer decomposition is stringent to the...

In this paper we study a portfolio execution problem in a discrete-time model in which orders can be submitted to a standard exchange and a dark pool. We model volatilities and correlations as stochastic processes and assume that trading at the standard exchange causes price impact. Orders sent...

Fractional Kelly portfolios are popular investment strategies in the market. In this paper, we improve the mean-variance efficiency of a fractional Kelly portfolio by minimizing the variance of the return of a portfolio subject to the constraint that the expected return rate of the portfolio is...

Calibrating option pricing models to market prices often leads to optimisation problems to which standard methods (like such based on gradients) cannot be applied. We investigate two models: Heston's stochastic volatility model, and Bates's model which also includes jumps. We discuss how to...

In this paper, we study a stochastic optimal control for max-min utility admitting volatility ambiguity. By standard assumptions, we establish the dynamic programming principle and the related Hamilton-Jacobi-Bellman (HJB) equation. Finally, we show that the value function is a viscosity...

The concept of model uncertainty is one of increasing importance in the field of Mathematical Finance. The main goal of this work is to explore model uncertainty in the specific area of algorithmic and high frequency trading. From a behavioural perspective, model uncertainty naturally leads to...