NMOF (version 1.2-2)

NMOF-package: Numerical Methods and Optimization in Finance

Description

Functions, data and other R code from the book ‘Numerical Methods and Optimization in Finance’. Comments/corrections/remarks/suggestions are very welcome (please contact the maintainer directly).

Details

The package contains implementations of several optimisation heuristics: Differential Evolution (DEopt), Genetic Algorithms (GAopt), (Stochastic) Local Search (LSopt), Particle Swarm (PSopt) and Threshold Accepting (TAopt). The term heuristic is meant in the sense of general purpose optimisation method.

Dependencies: The package is completely written in R. A number of packages are suggested, but they are not necessary to use the NMOF package. More specifically, package MASS is needed to run the complete example for PSopt and also in one of the vignettes (PSlms). Package parallel is optional for functions bracketing, GAopt, gridSearch and restartOpt, and may become an option for other functions. Package quadprog is needed for a vignette (TAportfolio) and some tests. Finally, RUnit is needed to run the tests in subdirectory ‘unitTests’.

Version numbering: package versions are numbered in the form major-minor-patch. The patch level is incremented with any published change, which means that a new version has been pushed to http://enricoschumann.net/R/packages/NMOF/. Minor version numbers are incremented when a feature is added or an existing feature is substantially revised. (Such changes will be reported in the NEWS file.) The major version number will only be increased if there were a new edition of the book.

The source code of the NMOF package is also hosted at https://github.com/enricoschumann/NMOF/.

Optimisation

There are functions for Differential Evolution (DEopt), Genetic Algorithms (GAopt), (Stochastic) Local Search (LSopt), Particle Swarm (PSopt) and Threshold Accepting (TAopt).

Pricing Financial Instruments

For options: See vanillaOptionEuropean, vanillaOptionAmerican, putCallParity. For pricing methods that use the characteristic function, see callCF.

For bonds and bond futures: See vanillaBond, bundFuture and xtContractValue.

Simulation

See resampleC and mc.

Data

See bundData, fundData and optionData.

References

Gilli, M., Maringer, D. and Schumann, E. (2011) Numerical Methods and Optimization in Finance. Elsevier. https://www.elsevier.com/books/numerical-methods-and-optimization-in-finance/gilli/978-0-12-375662-6

Schumann, E. (2017) Financial Optimisation with R (NMOF Manual). http://enricoschumann.net/NMOF.htm#NMOFmanual

Examples

# NOT RUN {
library("NMOF")

## overview
packageDescription("NMOF")
help(package = "NMOF")

## code from the book
showExample("equations.R")
showExample("exampleLS.R", chapter = 13)

## show NEWS file
news(Version >= "0.40-0", package = "NMOF")

## vignettes
vignette(package = "NMOF")
nss <- vignette("DEnss", package = "NMOF")
print(nss)
edit(nss)

## book website
browseURL("http://nmof.net")
browseURL("http://enricoschumann.net/NMOF/")

## more examples
file.show(system.file("NMOFex/README",   package = "NMOF"))
file.show(system.file("NMOFex/NMOFman.R", package = "NMOF"))

## unit tests
file.show(system.file("unitTests/test_results.txt",   package = "NMOF"))
# }
# NOT RUN {
test.rep <- readLines(system.file("unitTests/test_results.txt",   package = "NMOF"))
nt <- gsub(".*\\(([0-9]+) checks?\\).*", "\\1",
           test.rep[grep("\\(\\d+ checks?\\)", test.rep)])
message("Number of unit tests: ", sum(as.numeric(nt)))

# }