Journals
Researching new financial products: using survey evidence to gain insight into buy now, pay later
The authors investigate early adopters of "buy now, pay later" payments and how the use of this service may effect a person's credit.
Did fintech loans default more during the Covid-19 pandemic? Were fintech firms “cream-skimming” the best borrowers?
The authors propose a model which can be used to identify the "invisible prime" consumers from the nonprime pool for fintech loans.
Investment decisions driven by fine-tuned large language models and uniform manifold approximation and projection-supported clustering and hierarchical density-based spatial clustering
The author proposes an investment strategy using LLMs and text from social media posts and business and economic news and demonstrate that the strategy outperforms the chosen benchmark.
Deciphering bankruptcy risk in fintech firms: exploring key factors and implications
The authors delve into bankruptcy risk of Indian fintech firms, identifying the factors that most impact bankruptcy risk.
Skin in the game: risk analysis of central counterparties
This paper proposes a novel framework to design the capital contribution of a central counterparty (CCP) to its default waterfall - CCP "skin in the game".
Timing minimum-variance investment in the Canadian stock market
This paper proposes a novel explanation of the variation in idiosyncratic volatility anomaly return and its use in minimum-variance investing in the Canadian stock market.
Digital money and finance: a critical review of terminology
The authors put forward an etymology of key concepts and review key terminology and definitions within the sphere of decentralized finance to facilitate discussions about their merits and use cases/
Till def(ault) do us part: reassessing counterparty risk between global systemically important banks and central counterparties
The authors investigate how far liquidity at G-SIBs may be available to CCPs prior to a G-SIB resolution beginning and before a forced closeout is necessary, allowing the G-SIB to continue trading with a CCP until a payment default occurs.
Examining intersector risk synchronization in the Indian stock market: evidence from a time-varying connectedness approach
The authors investigate volatility spillover across the Covid-19 pandemic, Russia-Ukraine conflict and the collapse of Silicon Valley Bank and demonstrate how different sectors act as shock absorbers and transmitters.
Survival analysis in credit risk management: a review study
This paper offers a systematic literature review of survival analysis in credit risk assessment and suggests potential future avenues for research.
Uncertainty in the macroeconomic environment, corporate tax avoidance and corporate credit financing: evidence from high-tech listed companies in China
Using data from Chinese high-tech enterprises, the authors investigate links between corporate tax avoidance and bank credit financing.
Default risk in the era of environmental, social and governance ratings: a comparative analysis of divergence
The authors investigate links between ESG ratings divergence and default risk, finding firms demonstrating better ESG performance show lower default risk.
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.
Enhancing organizational sustainability through human resource analytics: examining the moderating effect of organizational culture
Focussing on information-technology-based organizations, the authors investigate links between human resources analytics and organizational sustainability, finding HR analytics to enhance organizational sustainability.
Operational risk, capital regulation and model risk
The author proposes seven basic properties for operational risk modelling to form an operational risk management framework.
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.
Approximate risk parity with return adjustment and bounds for risk diversification
The authors approach diversifying risk contributions to improve returns by satisfying approximate risk parity and providing bounds on a risk spread (RS) metric that quantifies risk diversification and takes returns into account.
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.
The power of neural networks in stochastic volatility modeling
The authors apply stochastic volatility models to real-world data and demonstrate how effectively the models calibrate a range of options.
A tale of two tail risks
This paper investigates the relationship between banking credit risk and the financial market jump hazard rate, finding the two risks to have opposing behaviors.
The impact of divergence in communication tone on investors’ willingness to invest in eurozone small- to medium-sized enterprises
The authors analyze the tone of central bank communications and how this can impact investor readiness to invest in euro areas SMEs.
Fintech lending and firm bankruptcies
The authors use data from small business bankruptcy at a county level in California to investigate the impact of fintech lending.
Dissecting initial margin forecasts: models, limitations and backtesting
The authors demonstrate that initial margin is not value-at-risk, but its approximation, and suggest a generic backtesting and verification framework that accommodates both forecasting limitations and existing models.
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.