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
What quants can learn from the Covid crisis
More nowcasting, less backtesting, and strategies that adapt to new regimes: a manifesto from Lipton and López de Prado
Three adjustments in calibrating models with neural networks
New research addresses fundamental issues with ANN approximation of pricing models
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
Podcast: Horvath and Lee on market generator models
Quants explain the application of the latest techniques
Outsmarting counterparty risk with smart contracts
A digital transaction system developed by quants at DZ Bank could slash margin costs for derivatives
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: Horvath and Lee on market generator models
Podcast: Kondratyev and Schwarz on generating data
Comment
What quants can learn from the Covid crisis
Three adjustments in calibrating models with neural networks