In this paper, we present advanced analytical formulas for SABR model option pricing. The first technical result consists of a new exact formula for the zero correlation case. This closed form is a simple 2D integration of elementary functions, particularly attractive for numerical...

We propose a new methodology for obtaining arbitrage free European option prices from a SABR-like parameterisation. The method consists of specifying the joint distribution of the volatility and underlying at a given expiry and requires the calculation of a simple one-dimensional numerical...

We suggest a new way of setting up multifactor models with hidden variables. We claim that the standard initial condition, which assigns some fixed value to the stochastic volatility subprocess, is illogical and greatly underestimates the effect of the hidden variable. For instance, a stochastic...

Stochastic volatility models are widely used in interest rate modeling to match the option smiles -- the two most popular are the Heston model and the SABR one. These have been incorporated into arbitrage-free term structure frameworks, Heston-LMM and SABR-LMM respectively.In this paper we...

In the current low-interest-rate environment, extending option models to negative rates has become an important issue. In our previous paper, we introduced the Free SABR model, which is a natural and an attractive extension to the classical SABR model. In spite of its advantages over the Shifted...

In this paper we examine the Heston model in the limit of infinitely fast mean-reversion for the stochastic volatility process (CIR). We show that, under an appropriate scaling of the model parameters, the two-factor stochastic volatility Heston model can be exactly mapped to a one-factor...

We investigate predictive abilities of nonlinear models for stock returns when density forecasts are evaluated and compared instead of the conditional mean point forecasts. The aim of this paper is to show whether the in-sample evidence of strong nonlinearity in mean may be exploited for...

Policy makers constantly face optimal control problems: what controls allow to achieve certain targets in, e.g., GDP growth or inflation? Conventionally this is done by applying certain linear-quadratic optimization algorithms to dynamic econometric models. Several algorithms extend this...

Policy makers constantly face optimal control problems: what controls allow to achieve certain targets in, e.g., GDP growth or inflation? Conventionally this is done by applying certain linear- quadratic optimization algorithms to dynamic econometric models. Several algorithms extend this...

We consider optimal information acquisition for the control of linear discrete-time random systems with noisy observations and apply the findings to the problem of dynamically implementing emissions-reduction targets. The optimal policy, which is provided in closed form, depends on a single...