PerformanceAnalytics: Econometric tools for performance and risk analysis: Collection of econometric functions for performance and risk analysis. This package aims to aid practitioners and researchers in utilizing the latest research in analysis of non-normal return streams. In general, it is most tested on return (rather than price) data on a regular scale, but most functions will work with irregular return data as well, and increasing numbers of functions will work with P&L or price data where possible.
Keywords for this software
References in zbMATH (referenced in 9 articles )
Showing results 1 to 9 of 9.
- Boudt, Kris; Cornilly, Dries; Verdonck, Tim: Nearest comoment estimation with unobserved factors (2020)
- Knoll, Julian; Stübinger, Johannes; Grottke, Michael: Exploiting social media with higher-order factorization machines: statistical arbitrage on high-frequency data of the S&P 500 (2019)
- Fischer, Thomas; Krauss, Christopher: Deep learning with long short-term memory networks for financial market predictions (2018)
- Stübinger, Johannes; Endres, Sylvia: Pairs trading with a mean-reverting jump-diffusion model on high-frequency data (2018)
- Stübinger, Johannes; Mangold, Benedikt; Krauss, Christopher: Statistical arbitrage with vine copulas (2018)
- Clegg, Matthew; Krauss, Christopher: Pairs trading with partial cointegration (2017)
- Krauss, Christopher; Do, Xuan Anh; Huck, Nicolas: Deep neural networks, gradient-boosted trees, random forests: statistical arbitrage on the S&P 500 (2017)
- Chan, Stephen; Nadarajah, Saralees; Afuecheta, Emmanuel: An \textttRpackage for value at risk and expected shortfall (2016)
- Arratia, Argimiro: Computational finance. An introductory course with R (2014)