Original research
Using option prices to trade the underlying asset
The authors propose strategies with which to trade the underlying assets of options based on large data sets generated by options trading.
Financial performance in electricity and gas markets: some empirical evidence from a cluster analysis
The authors undertake a cluster analysis of energy companies in Italy and the UK for the period 2008-2017.
Assessing the efficiency of pure-play internet banks in South Korea, Japan and China with data envelopment analysis
The authors investigate the efficiency of pure-play internet banks in China, Japan and South Korea, recommending they focus on the management of noninterest expenses and income to ensure stable profts.
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.
Option pricing under the normal stochastic alpha–beta–rho model with Gaussian quadratures
The authors integrate a Gaussian quadrature for option pricing under the normal alpha–beta–rho model, which they demonstrate to calculate accurate, arbitrage-free price and delta.
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.
Sustainable power purchase contracts for local industries from floating-solar and pumped-hydro integration
The authors put forward both business and technical cases for the provision of baseload power to local industrial and commercial users by hybrid floating-solar and pumped-hydro facilities.
Cyber risk assessment model for information assets: a tailored approach for the financial and banking sector
The authors present a novel model risk assessment model designed specifically for cyber risks and information assets,
Research on the multifractal volatility of Chinese banks based on the synthetic minority oversampling technique, edited nearest neighbors and long short-term memory
The authors propose the SMOTEENN-LSTM method to predict risk warnings for Chinese banks, demonstrating the improved performance of their model relative to commonly used methods.
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.
A qualitative study of operational resilience in financial institutions
The authors analyze data from a qualitative survey of senior G-SIB employees to identify recommendations for organisations looking to improve their operational resilience.
The fundamental role of the repo market and central clearing
The authors evaluate different economic functions of repo contracts and offer a summary of the structure of government bond repo markets in core advanced economies.
Can tax evasion be reduced by fostering cashless payments? A systematic literature review
This paper offers a review of literature on how different payment methods impact tax evasion, finding cash to facilitate tax evasion and digital methods of payment to make evasion more difficult.
On par: a money view of stablecoins
The authors apply a money view analysis to stablecoins, revealing the character if existing on-chain liquidity mechanisms that support the premise of par settlement and finding liquidity rather than solvency to be the factor confronted by par settlement.
A model combining Optuna and the light gradient-boosting machine algorithm for credit default forecasting
The authors put forward a default prediction model designed to make the analysis of complex, highly dimensional and imbalanced real-world bank data easier.
Litigation risk assessment: a novel quantitative recency–frequency–monetary model
The authors assess litigation risk and credit risk of companies and investigate interrelationships between these risks, finding a correlation between them.
Unveiling multiscale dynamics: exploring financial risk spillover and influencing factors among Chinese financial institutions
The authors investigate financial risk spillover in Chinese financial institutions, identifying the important role played by such institutions in the transmission of network risk as well as the conditions which increase and decrease risk spillover.
Cumulative accuracy profile curves for correlating collateralized debt obligations to systematic factors
This paper proposes a means to calibrate the correlation for paper issued by a collateralized debt obligation is included in a general credit portfolio of corporate bonds.
Converting a covariance matrix from local currencies to a common currency
The authors put forward a simple means to translate a covariance matrix estimated in local currencies into a covariance matrix expressed in a common currency.
Analyzing credit risk model problems through natural language processing-based clustering and machine learning: insights from validation reports
The authors use clustering and machine learning techniques to analyze validation reports, providing insights to the development, implementation and maintenance of credit risk models.
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.