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.
In this paper, the authors construct a Heath-Platen-type Monte Carlo estimator that performs extraordinarily well compared with the crude Monte Carlo estimation.
Banks have built ways to calculate CVA more quickly, but neural networks could offer more accurate method
Henry-Labordere proposes a neural networks-based technique to price counterparty risk and initial margin
Igor Halperin proposes new approach to compute probabilities of heavy-tailed distributions
Fast stochastic forward sensitivities in Monte Carlo simulations using stochastic automatic differentiation (with applications to initial margin valuation adjustments)
In this paper, the author applies stochastic (backward) automatic differentiation to calculate stochastic forward sensitivities.
In this paper, the authors give a preprocessing step for Fourier methods that involves projecting the Green’s function onto the set of linear basis functions.
Pricing fast-responding electric storage assets in the presence of negative prices and price spikes: a simulation-and-regression approach
This study focuses on the use of batteries for real-time power trading and proposes a simulation-and-regression-based valuation model.
In this paper, the authors develop a new local correlation model that uses a generic function 'g' to describe the correlation between all asset–asset pairs for a basket of underlyings.
In this paper, the authors construct strategies for an American option portfolio by exercising options at optimal timings with optimal weights determined concurrently.
CCP aims for Q1 2019 roll-out of new Monte Carlo-based methodology as it plans launch of index swaptions
This paper proposes a methodology to quantify capital charges for concentration risk when economic capital calculations are conducted within a multifactor Merton framework.
This study reviews the various statistical methodologies that are in place to test multiple systematic trading strategies and implements these methodologies under simulation with known artificial trading rules in order to critically compare and evaluate…
Vibrato and automatic differentiation for high-order derivatives and sensitivities of financial options
This paper deals with the computation of second-order or higher Greeks of financial securities. It combines two methods, vibrato and automatic differentiation (AD), and compares these with other methods.
StanChart quant proposes new technique to compute MVA quicker