Technical paper/Risk management
Randomization of spectral risk measures and distributional robustness
The authors offer a means to describe a decision maker's risk preferences with a randomized spectral risk measure.
The future of risk and insurability in the era of systemic disruption, unpredictability and artificial intelligence
The authors demonstrate the fragile nature of traditional risk management techniques in the face of frequent high-impact shocks and advocate for a new approach that treats disruption as systemic rather than episodic.
The robot-labeling phenomenon: robot-ready modern operational risk management
The author highlights misuse of the term "robot" in banking practice and the literature, proposes the robot-labelling phenomenon and recommends a shift in approaches to operational risk management to address challenges of the synthetic era.
Navigating risk horizons: a comprehensive bibliometric analysis of corporate risk management
The authors conduct a bibliometric analysis of 100 research papers to identify trends within corporate risk management.
Incorporating financial reports and deep learning for financial distress prediction: empirical evidence from Chinese listed companies
The authors investigate the use of text information processing methods for financial distress prediction and how this method can be combined with traditional means to improve prediction accuracy.
Lessons for academic research from model risk management in financial institutions
The authors suggest that model risk management practices used in financial institutions can be applied to academic research and enhance research outcomes.
Operational risks: trends and challenges
The authors carry out a systematic literature review of operational risk research to determine the current state of operational risk research in financial institutions.
The prediction of mortgage prepayment risks in the early stages of loan origination: a machine learning approach
The authors put forward a machine learning model for the prediction of mortgage prepayment risks at the loan origination phase.
Distributionally robust optimization approaches to credit risk management of corporate loan portfolios
A new approach to manage credit risk in financial institutions - the empirical divergence-based distributionally robust optimization - is proposed and shown to alleviate the challenges of sample sparsity and data uncertainty in credit risk modeling.
A method of classifying imbalanced credit data based on the AC-CTGAN hybrid sampling algorithm
The authors put forward a novel method with which to identify risk in consumer credit data and demonstrate its enhanced generalization ability compared to commonly used methods.
Unraveling Lebanon’s financial crisis: the path from promise to peril, delving into a risk strategist’s own experience
The author investigates the causes of Lebanon's financial crisis which began in 2019 and puts forward suggestions with which to restore trust and stability.
Artificial intelligence in crisis management: a bibliometric analysis
The authors carry out a bibliometric analysis of academic papers in the field of artificial intelligence applications in crisis management and propose potential new directions for researchers in this field.
Machine learning prediction of loss given default in government-sponsored enterprise residential mortgages
The authors apply machine learning techniques to Loss Given Default estimation, identifying key variables in LGD prediction and evaluating the performance of various models.
Backtesting correlated quantities
A technique to decorrelate samples and reach higher discriminatory power is presented
How is risk culture conceptualized in organizations? The pan-industry risk culture (PIRC) model
This paper puts forward a pan-industry risk culture as a framework through which to proactively manage risk culture.
Credit risk management: a systematic literature review and bibliometric analysis
The authors undertake a literature review and bibliometric analysis of 774 credit risk research papers.
New proxy schemes for swing contracts
The authors investigate the valuation of swing contracts for energy markets and propose two methods which offer more accurate calculated prices than commonly used methods.
Dynamic margining long/short equity trading strategies
A repo haircut model extends a previous solution for long-only strategies
Better anti-procyclicality? From a critical assessment of anti-procyclicality tools to regulatory recommendations
The authors carry out quantitative and qualitative analysis of anti-procyclicality tools and suggest policy measures intended to make APC tools more effective.
Peak-to-valley drawdowns: insights into extreme path-dependent market risk
The authors investigate risk in relation to peak-to-valley market drawdowns and aim to gain insights into the drawdown behaviour of asset classes across time intervals.