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 10 articles , 1 standard article )

Showing results 1 to 10 of 10.
Sorted by year (citations)

  1. Bilias, Yannis; Florios, Kostas; Skouras, Spyros: Exact computation of censored least absolute deviations estimator (2019)
  2. Ballestra, Luca Vincenzo; Cecere, Liliana: A fast numerical method to price American options under the Bates model (2016)
  3. Christoph Bergmeir and Daniel Molina and José Benítez: Memetic Algorithms with Local Search Chains in R: The Rmalschains Package (2016) not zbMATH
  4. Kapetanios, George; Marcellino, Massimiliano; Papailias, Fotis: Forecasting inflation and GDP growth using heuristic optimisation of information criteria and variable reduction methods (2016)
  5. Andria, Joseph; di Tollo, Giacomo; Pesenti, Raffaele: Detection of local tourism systems by threshold accepting (2015)
  6. Katharine Mullen: Continuous Global Optimization in R (2014) not zbMATH
  7. Scozzari, Andrea; Tardella, Fabio; Paterlini, Sandra; Krink, Thiemo: Exact and heuristic approaches for the index tracking problem with UCITS constraints (2013)
  8. Gilli, Manfred; Schumann, Enrico: Heuristic optimisation in financial modelling (2012)
  9. Maringer, Dietmar (ed.); Paterlini, Sandra (ed.); Winker, Peter (ed.): The 3rd special issue on optimization heuristics in estimation and modelling problems (2012)
  10. Gilli, Manfred; Maringer, Dietmar; Schumann, Enrico: Numerical methods and optimization in finance (2011)