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NMOF (version 2.3-1)

Numerical Methods and Optimization in Finance

Description

Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments such as bonds and options, for portfolio selection and functions that help with stochastic simulations.

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Install

install.packages('NMOF')

Monthly Downloads

1,235

Version

2.3-1

License

GPL-3

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Repository

https://github.com/enricoschumann/NMOF

Homepage

http://enricoschumann.net/NMOF.htm

Maintainer

Enrico Schumann

Last Published

January 19th, 2021

Functions in NMOF (2.3-1)

Constant-Proportion Portfolio Insurance

Numerical Methods and Optimization in Finance

Local-Search Information

Simple Moving Average

Computing Prices of European Calls with a Binomial Tree

Download Datasets from Kenneth French's Data Library

Optimisation with Differential Evolution

Internal NMOF functions

Stochastic Local Search

Optimisation with a Genetic Algorithm

Pricing Plain-Vanilla Bonds

Optimisation with Threshold Accepting

Threshold-Accepting Information

Zero Rates for Nelson--Siegel--Svensson Model

Optimisation with Simulated Annealing

Particle Swarm Optimisation

Download Robert Shiller's Data

Price a Plain-Vanilla Call with the Characteristic Function

Simulated-Annealing Information

Factor Loadings for Nelson--Siegel and Nelson--Siegel--Svensson

Zero-Bracketing

Mutual Fund Returns

Price of a European Call under the Heston Model

Price of a European Call under Merton's Jump--Diffusion Model

Full-rank Column Subset

Computing Mean--Variance Efficient Portfolios

Diversification Ratio

Resample with Specified Rank Correlation

Restart an Optimisation Algorithm

Repair an Indefinite Correlation Matrix

Minimum-Variance Portfolios

Create a Random Returns

Minimum Conditional-Value-at-Risk (CVaR) Portfolios

Prepare LaTeX Table with Quartile Plots

Put-Call Parity

trackingPortfolio

Compute a Tracking Portfolio

xtContractValue

Contract Value of Australian Government Bond Future

German Government Bond Data

Theoretical Valuation of Euro Bund Future

Option Pricing via Monte-Carlo Simulation

Display Code Examples

Classical Test Functions for Unconstrained Optimisation

Integration of Gauss-type

Partial Moments

vanillaOptionEuropean

Pricing Plain-Vanilla Options (European and American)