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Forward-backward stochastic differential equations (FBSDEs) have received more and more attention in the past two decades. FBSDEs can be applied to many fields, such as economics and finance, engineering control, population dynamics analysis, and so on. In most cases, FBSDEs are nonlinear and high-dimensional and cannot be obtained as analytic solutions. Therefore, it is necessary and important to design their numerical approximation methods. In this paper, a novel numerical method of multi-dimensional coupled FBSDEs is proposed based on a fractional Fourier fast transform (FrFFT) algorithm, which is used to compute the Fourier and inverse Fourier transforms. For the forward component of FBSDEs, time discretization is used as well as the backward equation to yield a recursive system with terminal conditions. For the numerical experiments to be successful, three types of numerical methods were used to solve the problem, which ensured the efficiency and speed of computation. Finally, the numerical methods for different examples are verified.

In this article, we account for the liquidity risk in the underlying assets when pricing European exchange options, which has not been considered in the literature. An Ornstein-Uhlenbeck process with the mean -reversion property is selected to model the market liquidity risk, whose impacts on the underlying assets are assumed to be imposed with a liquidity discount factor. Under this framework, we develop a simplified approach to obtain the pricing formula, a distinguishing feature of which is that it does not require any numeraire change. We first transform the exchange option's pricing PDE into a pricing PDE of the European vanilla option, which is then solved in closed-form using the characteristic function approach. Finally, we present accuracy tests and sensitivity analysis to demonstrate the correctness of the formula and the influence of introducing the liquidity risk on exchange options, respectively.

We analyze the valuation partial differential equation for European contingent claims in a general framework of stochastic volatility models where the diffusion coefficients may grow faster than linearly and degenerate on the boundaries of the state space. We allow for various types of model behavior: the volatility process in our model can potentially reach zero and either stay there or instantaneously reflect, and the asset-price process may be a strict local martingale. Our main result is a necessary and sufficient condition on the uniqueness of classical solutions to the valuation equation: the value function is the unique nonnegative classical solution to the valuation equation among functions with at most linear growth if and only if the asset-price is a martingale., Comment: Keywords: Stochastic volatility models, valuation equations, Feynman-Kac theorem, strict local martingales, necessary and sufficient conditions for uniqueness

In this paper, we take into account a very general setting with : (i) a set of stochastic investment opportunities, (ii) a set of risky assets, (iii) a riskless asset paying a stochastic interest rate, (iv) a stochastic inflation risk, (v) stochastic labor income , and (vi) HARA preferences. We compute a quasi-explicit solution for both the optimal consumption and asset allocation. This solution is based on two changes in the probability measure. We also show that the investor behaves as if he could rely on his wealth augmented by the expected value of all his “forward real labor incomes”

In this paper we take into account a very general setting with: (i)a set of stochastic investment opportunities, (ii) a set of risky assets, (iii) a riskless asset paying a stochastic interest rate, (iv) a stochastic inflation risk, (v) stochastic labor income, and (vi) HARA preferences. We compute a quasi-explicit solution for both the optimal consumption and asset allocation. This solution is based on two changes in the probability measure. We also show that the investor behaves as if he could rely on his wealth augmented by the expected value of all his ?forward real labor incomes?.

This paper analyses the portfolio problem of an investor who whants to maximize the expected utility of his terminal real wealth in an incomplete financial market. The investor must cope with a set of stochastic investment opportunities and inflation risk following a jump-diffusion process. We investigate how the inflation risk affects the optimal portfolio composition and, at this aim, we present an approximated analytical solution to the portfolio choice problem based on the Feynman-Kac representation theorem. Finally, we compare our approximated solution with some exact solutions available in the literature and we find that the main qualitative results are maintained.