Andersen's quadratic-exponential scheme is used for simulations of rough volatility models
This paper discusses several methods to estimate fVaR or margin requirements and their expected time evolution, from simple options to more complex interest swaps.
This paper compares two methods to calibrate two popular models that are widely used for stochastic volatility modeling (ie, the SABR and Heston models) with the time series of options written on the Nasdaq 100 index to examine the regularization effect…
In this paper the authors present a dependence model for non-life insurance risk based on risk factors, analogous to those generally used for life insurance or asset risk.
This paper proposes a credit risk model based on purchase order information to address the deficiencies of monitoring methods that use only financial statements.
An accurate data-driven and model-agnostic method to compute conditional expectations is presented
This study explores banks’ internal credit risk estimates and the associated banksourced transition matrixes.
In this paper, the European Association of CCP Clearing Houses discusses several aspects of climate risk, including how climate risk is currently integrated into central counterparty stress testing, the metrics within climate risk and how central…
A cost–benefit analysis of anti-procyclicality: analyzing approaches to procyclicality reduction in central counterparty initial margin models
In this paper, the authors suggest how margin setters and policy makers might measure procyclicality and target particular levels of it by recalibrating parameters in a margin model to reduce its procyclicality or by applying an anti-procyclicality tool.
In this paper the authors use block-level data from the Bitcoin blockchain to estimate the impact of congestion and the US dollar price on fee rates.
Using multivariate portfolio sorts, firm-level cross-sectional regressions and spanning tests, this paper shows that, in the cross section of stock returns, most commonly used risk measures in academia and in practice are separate return predictors with…
Volatility models and SPX/VIX joint dynamics are calibrated using optimal transport theory
A risk decomposition by fund manager, factor or instrument is proposed
This paper finds that the derivations in a previous paper by Yang et al (2019) are erroneous, and analyzes the risk model model correctly using the matrix analytic method.
This study continues the author’s examination and forecasts as to the impact of Covid-19 on the US credit cycle after one and a half years since the pandemic first began.
Customer churn prediction for commercial banks using customer-value-weighted machine learning models
In this paper the authors propose a framework to address the issue of customer churn prediction, and they quantify customer values with the use of an improved customer value model.
Test for fractional degree stochastic dominance with applications to stock preferences for China and the United States
This paper develops the test statistics for fractional degree stochastic dominance and introduces a bootstrap method for determining the critical values of the tests.
This paper analyses the components of central counterparty (CCP) capital requirements and makes several observations on the potential for loss absorption.
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.
In this paper the author's develop theoretical concepts of optimal injecting and withdrawing for a capacitated commodity storage and give case studies in natural gas.
This paper adds to the literature on factors driving distress risk and the economic consequences of economic policy uncertainty, and it provides a basis for enterprises to respond to changes in policies.
This paper presents a stochastic optimization framework for integrating time-varying factor covariance models in a risk-based portfolio optimization setting.
This paper examines the CBOE VIX, the VIX options’ implied volatility and the smirks associated with these options.
This paper proposes a methodology for estimating loss given default (LGD) that accounts for small default sample sizes.