Option pricing when correlations are stochastic: an analytical framework

In this paper we develop a novel market model where asset variances–covariances evolve stochastically. In addition shocks on asset return dynamics are assumed to be linearly correlated with shocks driving the variance–covariance matrix. Analytical tractability is preserved since the model is linear-affine and the conditional characteristic function can be determined explicitly. Quite remarkably, the model provides prices for vanilla options consistent with observed smile and skew effects, while making it possible to detect and quantify the correlation risk in multiple-asset derivatives like basket options. In particular, it can reproduce and quantify the asymmetric conditional correlations observed on historical data for equity markets. As an illustrative example, we provide explicit pricing formulas for rainbow “Best-of” options.     

Estimating stochastic volatility models using integrated nested Laplace approximations

Volatility in financial time series is mainly analysed through two classes of models; the generalized autoregressive conditional heteroscedasticity (GARCH) models and the stochastic volatility (SV) ones. GARCH models are straightforward to estimate using maximum-likelihood techniques, while SV models require more complex inferential and computational tools, such as Markov Chain Monte Carlo (MCMC). Hence, although provided with a series of theoretical advantages, SV models are in practice much less popular than GARCH ones. In this paper, we solve the problem of inference for some SV models by applying a new inferential tool, integrated nested Laplace approximations (INLAs). INLA substitutes MCMC simulations with accurate deterministic approximations, making a full Bayesian analysis of many kinds of SV models extremely fast and accurate. Our hope is that the use of INLA will help SV models to become more appealing to the financial industry, where, due to their complexity, they are rarely used in practice.     

Probabilistic technological forecasts using precursor events

A critical issue in avoiding technological surprise is to identify new technologies which present threats or opportunities at an early stage in their development. Currently, technological forecasters use the method of precursors to provide this early identification. However, the information provided by the method of precursors is purely qualitative. This paper describes the use of the method of maximum entropy for generating a probability distribution for the time lag between demonstration of a device and its market introduction. Examples from the aerospace and automotive industries are used to illustrate the technique.     

Smiles all around: FX joint calibration in a multi-Heston model

We introduce a novel multi-factor Heston-based stochastic volatility model, which is able to reproduce consistently typical multi-dimensional FX vanilla markets, while retaining the (semi)-analytical tractability typical of affine models and relying on a reasonable number of parameters. A successful joint calibration to real market data is presented together with various in- and out-of-sample calibration exercises to highlight the robustness of the parameters estimation. The proposed model preserves the natural inversion and triangulation symmetries of FX spot rates and its functional form, irrespective of choice of the risk-free currency. That is, all currencies are treated in the same way.     

No more discount under enhanced fair value hierarchy

We use an integrated approach to analyse the reasons behind the discount on the balance-sheet fair value of illiquid financial instruments held by European banks and classified into the Level 3 Fair Value hierarchy under IFRS 7. We believe that the potential sources of misalignment are (1) the lack of disclosure, (2) earnings management, and (3) the lack of liquidity. We show that the discount implicit in market values is linked to the lack of mandatory additional disclosure required by IFRS 7 and that this result supports the strong enforcement activity made by national authorities.