Technical paper
The variance-Hawkes process and its application to energy markets
The authors put forward a new model using as a Hawkes process as a subordinator in a standard Brownian motion which is applies to TWI crude oil and NYMEX natural gas futures.
Tailoring tails within the mixture model framework
Introducing a data generator mixing Gaussian and Student-t distributions to capture fat tails
The impact of environmental, social and governance scores on corporate risk: evidence from Chinese listed companies
The authors investigate how changes in ESG performance can impact firms' marker-based risk exposures.
Operational risk measurement: integrating the amplification effects of reputational risk
This paper puts forward a means to measure operational risk losses which integrates reputational and operational risks.
Differential machine learning with a difference
A technique to improve approximations for pricing derivatives with discontinuous payoffs is introduced
Managing the risks of generative AI: a framework for enterprise risk management
The authors put forward a conceptual framework to mitigate risks associated with generative-AI in enterprise risk management.
The role of business and IT alignment in cyber security risk management
The authors investigate how business and information technology alignment can improve cyber risk management.
The unreasonable effectiveness of randomised quasi-Monte Carlo in finance
An analysis of simulation methods shows which works best for Asian options
The key role of accounting intelligence and risk management in the practical economy: a new insight into company profitability
The authors examine impact enterprise risk management on financial and nonfinancial performance suing data from the Malaysian financial industry.
Investigating the relationship between liquidity creation and credit risk, with the moderating role of loan concentration: Islamic versus conventional banks in Pakistan and Malaysia
The authors investigate links between liquidity creation and credit risk in Islamic banks and conventional banks, with loan concentration as a moderating effect.
MI9: runtime governance for agentic AI systems
A real-time telemetry system for banks to control and authorise for agentic AI actions
All models are wrong. Some might be OK!
The authors investigate three key sources of model uncertainty and potential difficulties in addressing them.
Non-maturity deposit risk under interest rate stress: a behavioral modeling framework
The authors propose a behavioral framework with which to model non-maturity deposit risk under interest rate stress within an interest rate risk in the banking book (IRRBB) context.
The creation, credit risk and performance of fintech credit: peer-to-peer lending in Canada
The author analyzes the trade-off between credit risk and financial performance within the Canadian peer-to-peer lending market, examining how borrower characteristics and platform-assigned credit grades influence loan survival outcomes.
Forecasting Chinese crude oil futures’ volatility: a heterogeneous volatility spillover-conditional autoregressive range model
This paper offers a new model with which to model and forecast the volatility of Chinese crude oil futures.
Addressing class imbalance in probability-of-default modeling: a comparative study of SMOTE, ensemble learning and explainable artificial intelligence
The author puts forward s a governance-aligned framework for probability of default modeling under class imbalance, combining domain-informed feature engineering, resampling, ensemble learning and explainable artificial intelligence
Determinants of enterprise risk management implementation: evidence from multinational corporations across the three lines of defense
The authors identify and investigate factors influencing the implementation of enterprise risk management in multinational corporations.
Capturing smile dynamics with the quintic volatility model: SPX, SSR and VIX
A new model captures the term structure of SPX & VIX implied volatilities, ATM skew, and the skew-stickiness ratio
Responsible use of artificial intelligence in financial market infrastructures
The author investigates current and prospective role of AI in FMIs and develops a principled framework for the responsible use of AI based on the principles of explainability, data stewardship, governance and ethics.
A novel budget-based C+SVM model for credit risk prediction
The authors propose a modified support vector machine model based on load budget with which to predict credit risk.
Graph neural networks for credit default prediction: robustness and model evaluation
The authors evaluate the robustness and performance of graph-based models in credit default prediction.
FX market-making with internal liquidity
A model to optimally manage clients’ orders to internal liquidity pools is presented
An econometric investigation on the stability of stablecoins: are these coins stable or is their stability just a flip of the coin?
The authors investigate the volatility dynamics of US-dollar-backed stablecoins, challenging the assumption of inherent stability using a multilevel econometric framework.
Instant payments as the new normal: how much more money do the banks need?
The authors assess how the transition towards instant payment schemes and systems affects banks' liquidity needs.