Technical paper
The impacts of financial and macroeconomic factors on financial stability in emerging countries: evidence from Turkey’s nonperforming loans
The authors assess the impacts of financial and macroeconomic factors on financial stability in emerging economies, using Turkey's banking sector in the period 2005 Q1 to 2020 Q3 as their example.
Asymmetric risk spillovers between oil and the Chinese stock market: a Beta-skew-t-EGARCH-EVT-copula approach
The author uses the marginal expected shortfall method alongside the Beta-skew-t-exponential generalized autoregressive conditional heteroscedasticity-extreme value theory model and the CoVaR model to investigate risk spillover between the crude oil…
Least squares Monte Carlo methods in stochastic Volterra rough volatility models
The authors offer a VIX pricing algorithm for stochastic Volterra rough volatility models where the volatility is dependent of the vol-of-vol which reproduces key features of real-world data.
Collateralised exposure modelling: bridging the gap risk
Concentration, leverage and correlations may affect a collateralised equity swap portfolio
Pricing in the gap risk of mini-futures
Mini-futures need to be priced and hedged taking sudden jumps into account
Pricing options using expected profit and loss measures
The authors investigate the pricing of options using an EP-EL approach, finding that this methodology generates large amounts of useful information for option traders.
Dynamic rebalancing of a risk parity investment portfolio
The authors examine the All-Weather portfolio in relation to other popular portfolios and investigate the impact of various static and dynamic portfolio-rebalancing strategies on the All-Weather portfolio.
Dynamic signal selection strategies
The authors use eight models of pairwise dependency to select predictors that offer a high level of dependency in stock returns.
Trading the vol-of-vol risk premium
Applications of the vol-of-vol parameter for cross-asset derivatives are presented
Machine learning for categorization of operational risk events using textual description
The authors summarise ways that machine learning can help categorize textual descriptions of operational loss events into Basel II event types.
Systemic operational risk in the Australian banking system: the Royal Commission
The author investigates the Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry and its most prominent cases, as well as detailing examples of operational risk events that the commission did not cover.
Looking beyond SA-CCR
An alternative calculation of exposure at default that handles complex portfolios is presented
Forecasting the loss given default of bank loans with a hybrid multilayer LGD model by extending multidimensional signals
The authors employ signaling theory and machine learning methods to investigate loss given default predictions of commercial banks and propose a method to improve the accuracy of these predictions.
Performance validation of representative sample-balancing methods in loan credit-scoring scenarios
The authors validate 12 of the most representative sample-balancing methods used for credit-scoring models, finding that a combined SMOTE and Editor Nearest Neighbor method is optimal.
Scenario design for macrofinancial stress testing
The author presents an empirical approach to scenario design for selecting a stress scenario for international macrofinancial variables and compares this approach with a historical scenario approach.
Modeling maxima with a regime-switching Fréchet model
The authors identify a regime-switching Fréchet model which can be used to identify the behavior of extreme values in financial series.
Assessing systemic fragility: a probabilistic perspective
Using new measure of systemic fragility, the author ranks euro area banks and sovereigns and according to their systemic risk contribution.
Asset allocation with inverse reinforcement learning
Using reinforcement learning to help replicate asset managers' allocation strategy
Falling use of cash and population age structure
The authors investigate the reduction of cash use across 25 countries, using three means of measurement and argue that one method is more appropriate than the others.
Imbalanced data issues in machine learning classifiers: a case study
The author outlines characteristics of machine learning classifiers, compares methods for dealing with imbalanced data issues, and proposes terms of best practice in model development, evaluation, and validation.
Semiparametric GARCH models with long memory applied to value-at-risk and expected shortfall
The authors introduce and apply new semiparametric GARCH models with long memory to obtain rolling one-step ahead forecasts for the value-at-risk and expected shortfall (ES) for market risk assets.
Modeling very large losses. II
This paper presents a means to estimate very large losses by supposing the event is the result of a succession of factors and estimating the probability of each factor.
Vega decomposition for the LV model: an adjoint differentiation approach
Introducing an algorithm for computing vega sensitivities at all strikes and expiries
Enhanced expected impact cost model under abnormally high volatility
The authors extend their impact cost model beyond the typical factors to address the larger transaction costs brought on by stock market crowding effects in times of market turbulence.