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
Dynamically controlled kernel estimation
An accurate data-driven and model-agnostic method to compute conditional expectations is presented
What quant finance can learn from a 240-year-old problem
Optimal transport theory offers a data-driven way to calibrate derivatives pricing models
Optimal transport for model calibration
Volatility models and SPX/VIX joint dynamics are calibrated using optimal transport theory
Podcast: Matthew Dixon on decomposition of portfolio risk
New approach calculates contributions to value-at-risk for nonlinear portfolios
Nonlinear risk decomposition for any type of fund
A risk decomposition by fund manager, factor or instrument is proposed
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: Matthew Dixon on decomposition of portfolio risk
Podcast: Man Group’s Zohren on forecasting prices with DeepLOB
Comment
What quant finance can learn from a 240-year-old problem
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