Technical paper/Artificial intelligence
From use cases to a big data benchmarking framework in clearing houses and exchanges
In this paper, we propose a conceptual framework that links the technical and business benchmarks in the domain of clearing houses and securities exchanges.
A hybrid model for credit risk assessment: empirical validation by real-world credit data
This paper examines which hybridization strategy is more suitable for credit risk assessment in the dynamic financial world.
Toward reducing the operational risk of emerging technologies adoption in central counterparties through end-to-end testing
This paper discusses the software-testing challenges of traditional central counterparties as well as the risks, biases and problems related to new technologies. It also outlines a set of requirements for an end-to-end validation and verification…
An alternative statistical framework for credit default prediction
This study compares the gradient-boosting model with four other well-known classifiers, namely, a classification and regression tree (CART), logistic regression (LR), multivariate adaptive regression splines (MARS) and a random forest (RF).
Deep learning calibration of option pricing models: some pitfalls and solutions
Addressing model calibration and the issue of no-arbitrage in a deep learning approach
Yield curve fitting with artificial intelligence: a comparison of standard fitting methods with artificial intelligence algorithms
In this paper, the author expands standard yield curve fitting techniques to artificial intelligence methods.
Global perspectives on operational risk management and practice: a survey by the Institute of Operational Risk (IOR) and the Center for Financial Professionals (CeFPro)
This paper presents survey results which represent comprehensive perspectives on operational risk practice, obtained from practitioners in a wide range of countries and sectors.
Machine learning for trading
Gordon Ritter applies reinforcement learning to dynamic trading strategies with market impact