NMOF

R package NMOF: Numerical Methods and Optimization in Finance. Functions, examples and data from the book ’Numerical Methods and Optimization in Finance’ by M. Gilli, D. Maringer and E. Schumann. The package provides implementations of several optimisation heuristics, such as Differential Evolution, Genetic Algorithms and Threshold Accepting. There are also functions for the valuation of financial instruments, such as bonds and options, and functions that help with stochastic simulations.

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References in zbMATH (referenced in 18 articles , 1 standard article )

Showing results 1 to 18 of 18.
Sorted by year (citations)

  1. Hosseinzadeh, Mehdi; Sinopoli, Bruno; Kolmanovsky, Ilya; Baruah, Sanjoy: ROTEC: robust to early termination command governor for systems with limited computing capacity (2022)
  2. Maringer, Dietmar; Craig, Ben; Paterlini, Sandra: Constructing banking networks under decreasing costs of link formation (2022)
  3. Capuozzo, Pietro; Panella, Emanuele; Schettini Gherardini, Tancredi; Vvedensky, Dimitri D.: Path integral Monte Carlo method for option pricing (2021)
  4. Di Francesco, Marco: Portfolio optimization under Solvency II: a multi-objective approach incorporating market views and real-world constraints (2021)
  5. Khodamoradi, Tahereh; Salahi, Maziar; Najafi, Ali Reza: Cardinality-constrained portfolio optimization with short selling and risk-neutral interest rate (2021)
  6. Singh, Vikas Vikram; Lisser, Abdel; Arora, Monika: An equivalent mathematical program for games with random constraints (2021)
  7. Jacquier, Antoine; Torricelli, Lorenzo: Anomalous diffusions in option prices: connecting trade duration and the volatility term structure (2020)
  8. Bilias, Yannis; Florios, Kostas; Skouras, Spyros: Exact computation of censored least absolute deviations estimator (2019)
  9. Ballestra, Luca Vincenzo; Cecere, Liliana: A fast numerical method to price American options under the Bates model (2016)
  10. Christoph Bergmeir and Daniel Molina and José Benítez: Memetic Algorithms with Local Search Chains in R: The Rmalschains Package (2016) not zbMATH
  11. Kapetanios, George; Marcellino, Massimiliano; Papailias, Fotis: Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods (2016)
  12. Reher, Gerrit; Wilfling, Bernd: A nesting framework for Markov-switching GARCH modelling with an application to the German stock market (2016)
  13. Andria, Joseph; di Tollo, Giacomo; Pesenti, Raffaele: Detection of local tourism systems by threshold accepting (2015)
  14. Katharine Mullen: Continuous Global Optimization in R (2014) not zbMATH
  15. Scozzari, Andrea; Tardella, Fabio; Paterlini, Sandra; Krink, Thiemo: Exact and heuristic approaches for the index tracking problem with UCITS constraints (2013)
  16. Gilli, Manfred; Schumann, Enrico: Heuristic optimisation in financial modelling (2012)
  17. Maringer, Dietmar (ed.); Paterlini, Sandra (ed.); Winker, Peter (ed.): The 3rd special issue on optimization heuristics in estimation and modelling problems (2012)
  18. Gilli, Manfred; Maringer, Dietmar; Schumann, Enrico: Numerical methods and optimization in finance (2011)