This paper introduces a nonlinear certainty equivalent approximation method for dynamic stochastic problems. We first use a novel, stable and efficient method for computing the optimal policy functions for deterministic dynamic optimization problems, and then use them as certainty-equivalent...

We want to purpose and introduce a method that we name Geometrical Approximation (G.A.), by which it is possible to study the stochastic volatility market models (as Heston and SABR). The G.A. intends to be an alternative method useful to obtain the price of Vanilla options, this is less...

We show that the standard Value Function Iteration (VFI) algorithm has difficulties approximating models with jump discontinuities in policy functions. We find that VFI fails to accurately identify the location and size of jump discontinuities while other methods - such as the Endogenous Grid...

This paper proposes an approximation to the consumption function in the buffer-stock model. The approximation is based on the analytic properties of the consumption function in the buffer-stock model. In such model, the consumption function is increasing and concave and its derivative is bounded...

We consider the saddlepoint approximation methods for pricing derivatives whose payoffs depend on the discrete realized variance of the underlying price process of a risky asset. Most of the earlier pricing models of variance products and volatility derivatives use the quadratic variation...