Other packages > Find by keyword >

LSMRealOptions  

Value American and Real Options Through LSM Simulation
View on CRAN: Click here


Download and install LSMRealOptions package within the R console
Install from CRAN:
install.packages("LSMRealOptions")

Install from Github:
library("remotes")
install_github("cran/LSMRealOptions")

Install by package version:
library("remotes")
install_version("LSMRealOptions", "0.2.1")



Attach the package and use:
library("LSMRealOptions")
Maintained by
Thomas Aspinall
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-01-21
Latest Update: 2021-06-26
Description:
The least-squares Monte Carlo (LSM) simulation method is a popular method for the approximation of the value of early and multiple exercise options. 'LSMRealOptions' provides implementations of the LSM simulation method to value American option products and capital investment projects through real options analysis. 'LSMRealOptions' values capital investment projects with cash flows dependent upon underlying state variables that are stochastically evolving, providing analysis into the timing and critical values at which investment is optimal. 'LSMRealOptions' provides flexibility in the stochastic processes followed by underlying assets, the number of state variables, basis functions and underlying asset characteristics to allow a broad range of assets to be valued through the LSM simulation method. Real options projects are further able to be valued whilst considering construction periods, time-varying initial capital expenditures and path-dependent operational flexibility including the ability to temporarily shutdown or permanently abandon projects after initial investment has occurred. The LSM simulation method was first presented in the prolific work of Longstaff and Schwartz (2001) .
How to cite:
Thomas Aspinall (2021). LSMRealOptions: Value American and Real Options Through LSM Simulation. R package version 0.2.1, https://cran.r-project.org/web/packages/LSMRealOptions. Accessed 25 Jun. 2026.
Previous versions and publish date:
0.1.0 (2021-01-21 12:00), 0.2.0 (2021-05-04 09:20), 0.2.1 (2021-06-26 12:30)
Other packages that cited LSMRealOptions R package
View LSMRealOptions citation profile
Other R packages that LSMRealOptions depends, imports, suggests or enhances
Complete documentation for LSMRealOptions
Functions, R codes and Examples using the LSMRealOptions R package
Some associated functions: GBM_simulate . GOU_simulate . IGBM_simulate . LSM_american_option . LSM_real_option . LSM_real_option_OF . 
Some associated R codes: LSM_american_option.R . LSM_real_option.R . LSM_real_option_OF.R . SDE_simulate.R .  Full LSMRealOptions package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

sitmo  
Parallel Pseudo Random Number Generator (PPRNG) 'sitmo' Header Files
Provided within are two high quality and fast PPRNGs that may be used in an 'OpenMP' parallel enviro ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
foster  
Forest Structure Extrapolation with R
Set of tools to streamline the modeling of the relationship betweensatellite imagery time series or ...
Download / Learn more Package Citations See dependency  
edeaR  
Exploratory and Descriptive Event-Based Data Analysis
Exploratory and descriptive analysis of event based data. Provides methods for describing and select ...
Download / Learn more Package Citations See dependency  
airGRiwrm  
'airGR' Integrated Water Resource Management
Semi-distributed Precipitation-Runoff Modelling based on 'airGR' package models integrating human i ...
Download / Learn more Package Citations See dependency  

27,535

R Packages

236,180

Dependencies

73,223

Author Associations

27,536

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA