Mild solutions to the dynamic programming equation for stochastic optimal control problems

We show via the nonlinear semigroup theory in $L^1(\mathbb{R})$ that the $1$-D dynamic programming equation associated with a stochastic optimal control problem with multiplicative noise has a unique mild solution $\varphi\in C([0,T];W^{1,\infty}(\mathbb{R}))$ with $\varphi_{xx}\in C([0,T];L^1(\mathbb{R}))$. The $n$-dimensional case is also investigated

Mean field games with controlled jump-diffusion dynamics: Existence results and an illiquid interbank market model

We study a family of mean field games with a state variable evolving as a multivariate jump diffusion process. The jump component is driven by a Poisson process with a time-dependent intensity function. All coefficients, i.e. drift, volatility and jump size, are controlled. Under fairly general conditions, we establish existence of a solution in a relaxed version of the mean field game and give conditions under which the optimal strategies are in fact Markovian, hence extending to a jump-diffusion setting previous results established in [30]. The proofs rely upon the notions of relaxed controls and martingale problems. Finally, to complement the abstract existence results, we study a simple illiquid inter-bank market model, where the banks can change their reserves only at the jump times of some exogenous Poisson processes with a common constant intensity, and provide some numerical results.Comment: 37 pages, 6 figure

Optimal choices: mean field games with controlled jumps and optimality in a stochastic volatility model

Decision making in continuous time under random influences is the leitmotif of this work. In the first part a family of mean field games with a state variable evolving as a jump-diffusion process is studied. Under fairly general conditions, the existence of a solution in a relaxed version of these games is established and conditions under which the optimal strategies are in fact Markovian are given. The proofs rely upon the notions of relaxed controls and martingale problems. Mean field games represent the limit, as the number of players tends to infinity, of nonzero-sum stochastic differential games. Under the assumption that the former admit a regular Markovian solution, an approximate Nash equilibrium for the corresponding n-player games is constructed, and the rate of convergence is provided. Finally, the general theory is applied to a simple illiquid inter-bank market model, where the banks can adjust their reserves only at the jump times of some given Poisson processes with a common constant intensity, and some numerical results are provided. In the second part a stochastic optimization problem is presented. Here the evolution of the state is modeled as in the Heston model, but with a further multiplicative control input in the volatility term. The main objective is to consider the possible role of an external actor, whose exogenous contribution is summarised in the control itself. The solvability of the Hamilton-Jacobi-Bellman equation associated to this optimal control problem is discussed

Default Contagion in Financial Networks

The preset work aims at giving insights about howthe theory behind the study of complex networks can be profitablyused to analyse the increasing complexity characterizinga wide number of current financial frameworks. In particularwe exploit some well known approaches developed within thesetting of the graph theory, such as, e.g., the Erd˝os and Rénymodel, and the Barab´asi-Albert model, as well as producingan analysis based on the evolving network theory. Numericalsimulations are performed to study the spread of financial peakevents, as in the case of the default of a single bank belonging toa net of interconnected monetary institutions, showing how theknowledge about the underlying graph theory can be effectivelyused to withstand a financial default contagion

Optimal Execution Strategy in Liquidity Framework Under Exponential Temporary Market Impact

In the present work we compute the optimal liquidation strategy for an investor who intends to entirely extinguish his position in an illiquid asset so as to minimize a criterion involving mean and variance of the strategies implementation shortfall. The market impact due to illiquidity is modeled by splitting it into two different component, namely the permanent market impact, which is assumed to be linear in the rate of trading, and the temporary market impact, which follows an exponential-type function

Optimal execution strategy in liquidity framework

A trader wishes to execute a given number of shares of an illiquid asset. Since the asset price also depends on the trading behaviour, the trader main aim is to find the execution strategy that minimizes the related expected costs. We solve this problem in a discrete time framework, by modeling the asset price dynamic as an arithmetic random walk with drift and volatility both modeled as Markov stochastic processes. The market impact is assumed to follow a Markov process. We found the unique execution strategy minimizing the implementation shortfall when short selling is allowed. This optimal strategy is given as solution of a forward-backward system of stochastic equations depending on conditional expectations of future values of model parameters. In the opposite case, namely when short selling is prohibited, we numerically obtain the solution for the associated Bellman equation that an optimal trading strategy must satisfy

Feedback Optimal Controllers for the Heston Model

We prove the existence of an optimal feedback controller for a stochastic optimization problem constituted by a variation of the Heston model, where a stochastic input process is added in order to minimize a given performance criterion. The stochastic feedback controller is found by solving a nonlinear backward parabolic equation for which one proves the existence and uniqueness of a martingale solution

Mean field games with controlled jump\u2013diffusion dynamics: Existence results and an illiquid interbank market model

We study a family of mean field games with a state variable evolving as a multivariate jump\u2013diffusion process. The jump component is driven by a Poisson process with a time-dependent intensity function. All coefficients, i.e. drift, volatility and jump size, are controlled. Under fairly general conditions, we establish existence of a solution in a relaxed version of the mean field game and give conditions under which the optimal strategies are in fact Markovian, hence extending to a jump\u2013diffusion setting previous results established in Lacker (2015). The proofs rely upon the notions of relaxed controls and martingale problems. Finally, to complement the abstract existence results, we study a simple illiquid inter-bank market model, where the banks can change their reserves only at the jump times of some exogenous Poisson processes with a common constant intensity, and provide some numerical results