This study sheds new light on the question of whether or not sentiment surveys, and the expectations derived from them, are relevant to forecasting economic growth and stock returns, and whether they contain information that is orthogonal to macroeconomic and financial data. I examine 16...

The Nelson-Siegel-Svensson model is widely-used for modelling the yield curve, yet many authors have reported ‘numerical difficulties' when calibrating the model. We argue that the problem is twofold: firstly, the optimisation problem is not convex and has multiple local optima. Hence standard...

This paper presents a framework to model correlated default events that can be used to price and hedge standard and exotic credit baskets whose values depend on the realized losses of a default portfolio. The model consists of parametric continuous time Markov chain and aims to accurately...

Artificial Neural Networks (ANNs) have recently been proposed as accurate and fast approximators in various derivatives pricing applications. ANNs typically excel in fitting functions they approximate at the input parameters they are trained on, and often are quite good in interpolating between...

Banks must manage their trading books, not just value them. Pricing includes valuation adjustments collectively known as XVA (at least credit, funding, capital and tax), so management must also include XVA. In trading book management we focus on pricing, hedging, and allocation of prices or...

When estimating higher-order derivatives of a partial differential equation, it is often essential to compute approximations for artificial boundaries. In this paper we formulate an explicit discretization model for approximation of beta-coefficient of Capital Asset Pricing Model (CAPM). The...

We develop two neo-classical methods for function approximations, the generalized stochastic sampling (gSS) and the functional tensor train (fTT) methods, that are high-performing alternatives to generic deep neural networks (DNNs) currently routinely proposed for function approximations in...

We present a data-driven proof of concept model capable of reproducing expected counterparty credit exposures from market and trade data. The model has its greatest advantages in quick single-contract exposure evaluations that could be used in front office xVA solutions. The data was generated...

Recent periods of market turbulence and stress have created considerable interest in credible alternatives to traditional asset allocation methodologies. It would be preferred if portfolios can be decomposed into components that can be directly connected to independent risks and individually...