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
Degree of influence: Regulatory policies drive quantitative research
Counterparty risk and market risk hold centre stage, data science moves up, quantum computing debuts
Hedging rate exotics, Bergomi-style
New paper by Nomura quant applies volatility model used in equities to exotic rate hedging
The swap market Bergomi model
The combination of two popular volatility models sharpens the hedging of exotic rate derivatives
Rising star in quant finance: Blanka Horvath, Aitor Muguruza and Mehdi Tomas
Risk Awards 2020: New machine learning techniques bring ‘rough volatility’ models to life
ADOL: Markovian approximation of a rough lognormal model
A variation of the rough volatility model is introduced by plugging in a different stochastic process
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: Mats Kjaer on how trades affect the balance sheet
Podcast: Acerbi on backtesting ES and FRTB’s patchwork rules
Podcast: McClelland on why you need a good MVA model
Podcast: Gregory and Chung on wrong-way risk modelling
Comment
Degree of influence: Regulatory policies drive quantitative research
Hedging rate exotics, Bergomi-style
Quants bring ‘triptych’ of variables to risk measurement
Game theory plays well for capital management