Cutting Edge
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.
To publish with us, see our submissions guidelines and contact us.
Choosing trading strategies using importance sampling
- Importance sampling is a Monte Carlo-based method to approximate statistical distributions
- A-B testing may be inefficient in selecting trading strategies
- Importance sampling, combined with reinforcement learning, displays attractive features over standard methods
Quants dive into FX fixing windows debate
Longer fixing windows may benefit clients, but predicting how dealers will respond is tough
Podcast: Piterbarg and Nowaczyk on running better backtests
Quants discuss new way to extract independent samples from correlated datasets
Backtesting correlated quantities
A technique to decorrelate samples and reach higher discriminatory power is presented
A comparison of FX fixing methodologies
FX fixing outcomes are mostly driven by length of calculation window
