Gaussian distributions can sharpen one of the most commonly used tools in quant finance
A data-driven approach to computing expectations for the pricing and hedging of exotics
A novel optimal execution approach via continuous-time stochastic processes is introduced
Independent component analysis is proposed as an alternative to principal component analysis
An accurate data-driven and model-agnostic method to compute conditional expectations is presented
In this paper, the authors propose to approach the calibration problem of local volatility with Bayesian statistics to infer a conditional distribution over functions given observed data.
This paper develops a method for estimating value-at-risk and conditional value-at-risk when the underlying risk factors follow a beta distribution in a univariate and a matrix-variate setting.
An optimal hedging strategy for options in discrete time using a reinforcement learning technique
Gaussian process regression for derivative portfolio modeling and application to credit valuation adjustment computations
The authors present a multi-Gaussian process regression approach, which is well suited for the over-the-counter derivative portfolio valuation involved in credit valuation adjustment (CVA) computation.
In this paper, the author uses the mean–variance hedging criterion to value contracts in incomplete markets.
This paper seeks to shed light on one critical area of such frameworks: model risk tiering, or the rating of risk inherent in the use of individual models, which can benefit a firm’s resource allocation and overall risk management capabilities.
Quant grads should be taught follies of LTCM, Gaussian copula and London Whale, writes UBS’s Gordon Lee
This paper discusses and derives the extremum of the expectation of permanent impact and realized impact by constructing several special trading trajectories in the Chinese market.
In this paper, the authors propose several flexible families of models to manage the market and/or the counterparty risk of portfolios of financial assets.
In this paper, the authors study factor-based subordinated Lévy processes in their variance gamma (VG) and normal inverse Gaussian (NIG) specifications, and focus on their ability to price multivariate exotic derivatives.
This paper assesses the model risk associated with the copula choice for the calculation of the Default Risk Charge (DRC) measure.
This paper describes a simple model that can be used for risk management.
Thomas Roos derives model-independent bounds for amortising and accreting Bermudan swaptions
This paper presents a natural extension of the LGM that keeps the affine structure and generates an implied volatility smile.
This paper aims to build novel measures of systemic risk that take the multivariate nature of the problem into account by means of network models.
Greater use of models means risk "has significantly increased", says HSBC's Bhaskar
Negative rates causing pricing model rethink
This paper analyzes the theoretical properties and statistical behavior of credit default swap (CDS) premiums over time.