Use cases for new tech are piling up – from CVA to VAR. But so are the obstacles
Differential machine learning produces results “thousands of times faster and with similar accuracy”
ABN, ING and Rabobank working together; US quantum developer seeks patent for CCAR
A derivative pricing approximation method using neural networks and AAD speeds up calculations
Elliptical and Archimedean copula models: an application to the price estimation of portfolio credit derivatives
This paper explores the impact of elliptical and Archimedean copula models on the valuation of basket default swaps.
The heat potentials method is used to find the optimal profit-taking and stop-loss levels
In this study, the authors identify the three types of risks involved in an art-secured lending operation and present a framework to assess their combined effects via a Monte Carlo simulation.
In this work, we present a new Monte Carlo algorithm that is able to calculate the pathwise sensitivities for discontinuous payoff functions.
This paper proposes a new, flexible framework using Monte Carlo methods to price Parisian options not only with constant boundaries but also with general curved boundaries.
A generative neural network is proposed to create synthetic datasets that mantain the statistical properties of the original dataset
Interquartile distribution of VAR outputs highest for small banks, watchdog finds
Stephen Wilcox talks about getting pensions paid without the benefit of controlling ‘UK Plc’
A simulation-based model for optimal demand response load shifting: a case study for the Texas power market
This paper describes a case study of analyzing DR load-shifting strategies for a retail electric provider for the Texas (ERCOT) market using a Monte Carlo simulation with stochastic loads and settlement prices.
The authors propose a model for conduct risk losses, in which conduct risk losses are characterized by having a small number of extremely large losses (perhaps only one) with more numerous smaller losses.
Risk Awards 2020: Clearing house lures fund business with efficient new Monte Carlo methodology
In this paper, the author uses the mean–variance hedging criterion to value contracts in incomplete markets.
The main goal of this paper is to perform a comprehensive nonparametric jump detection model comparison and validation. To this end, the authors design an extensive Monte Carlo study to compare and validate these tests.
This paper derives an alternative fast Fourier transform-based computational approach for calculating the target capital of the SST that is more than 600 times faster than a Monte Carlo simulation.
Measuring 1-in-1,000 year loss events ‘unrealistic’, researchers say
In this paper, the authors present a multiperiod portfolio management strategy that can be used to directly manage the realized volatility over a long time horizon.
Quants are embracing the idea of ‘model free’ pricing and hedging
This paper develops a parsimonious model for evaluating portfolio credit derivatives dependent on aggregate loss.
Changing regulations and new accounting standards are creating enormous challenges for financial organisations. Thorsten Hein, principal product marketing manager, risk research and quantitative solutions at SAS, explores why, to successfully meet these…
Skewed target range strategy for multiperiod portfolio optimization using a two-stage least squares Monte Carlo method
In this paper, the authors propose a novel investment strategy for portfolio optimization problems.