Mathematics and Financial Economics最新文献

Motivated by optimal allocation models with relative performance criteria, we introduce a mean field game in which the terminal expected utility of the representative agent depends on her own state as well as the average of her peers. We derive the master equation, which, in view of the presence of controls in the volatility, needs to be coupled with a compatibility condition for the mean field optimal feedback control. We concentrate on the class of separable payoffs under both general utilities and couplings. We derive a solution to the master equation and find the associated optimal feedback control expressed via the value function in the absence of competition and a dynamic coupling function solving a non-local quasilinear equation. In turn, we construct the related optimal state and control processes, and give representative examples. Projecting the mean field solutions on finite dimensions, we recover the solution of the N-game for linear couplings and arbitrary utilities, and we study the proximity of these approximations to their N-player game counterparts.

This paper considers the issue of optimal investment and reinsurance strategies for an insurer with regime-switching. In our mathematical model, a risk-free asset and a risky asset are assumed to rely on a continuous time-homogeneous, finite-state, observed Markov chain, and the latter’s price dynamics is described by a general regime-switching jump-diffusion process. We are extending the classical claim process to a Markov-modulated compound Poisson process. The insurer faces the decision-making problem of choosing to invest his/her surplus in the financial market and purchase reinsurance such that the expected power utility of his/her terminal wealth is maximized. We apply dynamic programming principle to derive the regime-switching Hamilton–Jacobi–Bellman (HJB) equation. Then, by analysing the solutions of the HJB equation, the optimal investment and reinsurance strategies are obtained and given in the verification theorem. Finally, the numerical analysis based on a two-state Markov chain is presented to illustrate our results.

We propose a model in which, in exchange to the payment of a fixed transaction cost, an insurance company can choose the retention level as well as the time at which subscribing a perpetual reinsurance contract. The surplus process of the insurance company evolves according to the diffusive approximation of the Cramér-Lundberg model, claims arrive at a fixed constant rate, and the distribution of their sizes is general. Furthermore, we do not specify any particular functional form of the retention level. The aim of the company is to take actions in order to minimize the sum of the expected value of the total discounted flow of capital injections needed to avoid bankruptcy and of the fixed activation cost of the reinsurance contract. We provide an explicit solution to this problem, which involves the resolution of a static nonlinear optimization problem and of an optimal stopping problem for a reflected diffusion. We then illustrate the theoretical results in the case of proportional and excess-of-loss reinsurance, by providing a numerical study of the dependency of the optimal solution with respect to the model’s parameters.

This study analyzes robust strategic asset allocation under a quadratic security market model with stochastic volatility and inflation rates assuming “age-dependent robust utility” in which relative ambiguity aversion is a decreasing function of age. We show that, unlike homothetic robust utility, age-dependent robust utility cannot be interpreted as homothetic stochastic differential utility. We consider the finite-time consumption-investment problem and derive a linear approximate optimal robust portfolio candidate decomposed into myopic, intertemporal hedging, and inflation–deflation hedging demands. Our numerical analysis of the approximate optimal allocation to the S &P500 shows modest hump-shaped age effects, similar to the results of a previous empirical analysis, and that the upswing is due to the increase in myopic demand, while the downswing is due to the decrease in intertemporal hedging demand.

This paper analyzes the robust long-term growth rate of expected utility and expected return from holding a leveraged exchange-traded fund. When the Markovian model parameters in the reference asset are uncertain, the robust long-term growth rate is derived by analyzing the worst-case parameters among an uncertainty set. We compute the growth rate and describe the optimal leverage ratio maximizing the robust long-term growth rate. To achieve this, the worst-case parameters are analyzed by the comparison principle, and the growth rate of the worst-case is computed using the Hansen–Scheinkman decomposition. The robust long-term growth rates are obtained explicitly under a number of models for the reference asset, including the geometric Brownian motion, Cox–Ingersoll–Ross, 3/2, and Heston and 3/2 stochastic volatility models. Additionally, we demonstrate the impact of stochastic interest rates, such as the Vasicek and inverse GARCH short rate models. This paper is an extended work of Leung and Park (Int J Theor Appl Finance 20(6):1750037, 2017).

In a Mean Field Game (MFG) each decision maker cares about the cross sectional distribution of the state and the dynamics of the distribution is generated by the agents’ optimal decisions. We prove the uniqueness of the equilibrium in a class of MFG where the decision maker controls the state at optimally chosen times. This setup accommodates several problems featuring non-convex adjustment costs, and complements the well known drift-control case studied by Lasry–Lions. Examples of such problems are described by Caballero and Engel in several papers, which introduce the concept of the generalized hazard function of adjustment. We extend the analysis to a general “impulse control problem” by introducing the concept of the “Impulse Hamiltonian”. Under the monotonicity assumption (a form of strategic substitutability), we establish the uniqueness of equilibrium. In this context, the Impulse Hamiltonian and its derivative play a similar role to the classical Hamiltonian that arises in the drift-control case.

We study a mean-field zero-sum Dynkin game (MF-ZSDG) with time-inconsistent performance functionals adapted to the Brownian filtration. Despite the time-inconsistency of the MF-ZSDG, we show that it admits a value and that the pair of first times the value process hits the upper and lower obstacles, respectively, is a saddle point for the game. We solve the problem by approximating the associated lower and upper value processes with a sequence of value processes of interacting time-consistent zero-sum Dynkin games for which the saddle point of each of the value processes is the pair of first times each of those value processes hits the associated upper and lower obstacles, respectively. Under mild assumptions, we show that this sequence of saddle points converges in probability to the pair of first hitting times of the value process of the upper and lower obstacles, respectively, and that the limit is a saddle point for the time-inconsistent MF-ZSDG.

Within the one-factor capital asset pricing model (CAPM), the minimum-variance portfolio (MVP) is known to have long positions in those assets of the underlying investment universe whose betas are less than a well-defined long-short threshold beta. We study the structure of MVPs in more general multi-factor asset pricing models and clarify the low-beta puzzle for multi-factor models: For multi-factor models we derive a similar criterion in terms of the betas with explicit closed-form formulas. But the structural relationship is now more involved and the long-short threshold turns out to be asset-specific. The results rely on recursive inverse-free formulas for the precision matrix, which hold for multi-factor models and allow quick computation of that inverse matrix without the need to invert matrices going beyond diagonal ones. We illustrate our findings by analyzing S &P 500 asset returns. Our empirical results of the S &P 500 constituents between 2019 and 2022 confirm the theoretical findings and shows that the minimum variance portfolio is long in low-beta assets when applying estimates of the established asset-specific thresholds.

In the dynamic discrete-time trading setting of Kyle (Econometrica 53:1315–1336, 1985), we prove that Kyle’s equilibrium model is stable when there are one or two trading times. For three or more trading times, we prove that Kyle’s equilibrium is not stable. These theoretical results are proven to hold irrespectively of all Kyle’s input parameters.