Cutting Edge is the quantitative finance section of Risk.net. It publishes exclusive peer-reviewed papers selected for their originality, relevance and applicability to financial markets. It also publishes podcasts with leading quants on the most topical issues, and comments from practitioners and our editorial team.
Latest Cutting Edge
Quantifying systemic risk using Bayesian networks
Creditworthiness of individual entities may offer an insight into systemic risk of financial markets
No silver bullet for AI explainability
No single approach to interpreting a neural network’s outputs is perfect, so it’s better to use them all
Interpretability of neural networks: a credit card default model example
Recently developed techniques aimed at answering interpretability issues in neural networks are tested and applied to a retail banking case
Podcast: Kondratyev and Schwarz on generating data
Market generator models may aid areas of finance where data is limited or sensitive
The market generator
A generative neural network is proposed to create synthetic datasets that mantain the statistical properties of the original dataset
Investments
Research papers on the buy-side industry, providing quantitative solutions for portfolio management, trading, machine learning applications for investment firms
Banking
Research papers on the derivatives business, banks’ risk management, machine learning applications for dealers
Podcasts
Podcast: Kondratyev and Schwarz on generating data
Podcast: Andrew Dickinson on CCPs’ defence mechanisms
Comment
No silver bullet for AI explainability
Small, speculative clearing members – are they worth the risk?