00fOptions-package: Basic Option Valuation

In fOptions: Rmetrics - Pricing and Evaluating Basic Options

Basic Option Valuation

Description

The Rmetrics "Options" package is a collection of functions to valuate basic options.

Details

Package:	fOptions
Type:	Package
Version:	R 3.0.1
Date:	2014
License:	GPL Version 2 or later
Copyright:	(c) 1999-2014 Rmetrics Assiciation
URL:	https://www.rmetrics.org

1 Introduction

The fOptions package provides function for pricing and evaluationg basic options.

2 Plain Vanilla Option

This section provides a collection of functions to valuate plain vanilla options. Included are functions for the Generalized Black-Scholes option pricing model, for options on futures, some utility functions, and print and summary methods for options.

    GBS*                      the generalized Black-Scholes option
    BlackScholesOption        a synonyme for the GBSOption
    Black76Option             options on Futures
    MiltersenSchwartzOption   options on commodity futures
    

    NDF, CND, CBND  distribution functions
    

    print                     print method for Options
    summary                   summary method for Options
    

3 Binomial Tree Options

This section offers a collection of functions to valuate options in the framework of the Binomial tree option approach.

    CRRBinomialTreeOption     CRR Binomial Tree Option
    JRBinomialTreeOption      JR Binomial Tree Option
    TIANBinomialTreeOption    TIAN Binomial Tree Option
    BinomialTreeOption        Binomial Tree Option
    BinomialTreePlot          Binomial Tree Plot
    

4 Monte Carlo Options

In this section we provide functions to valuate options by Monte Carlo methods. The functions include beside the main Monte Carlo Simulator, example functions to generate Monte Carlo price paths and to compute Monte Carlo price payoffs.

    sobolInnovations          Example for scrambled Sobol innovations
    wienerPath                Example for a Wiener price path
    plainVanillaPayoff        Example for the plain vanilla option's payoff
    arithmeticAsianPayoff     Example for the arithmetic Asian option's payoff
    MonteCarloOption          Monte Carlo Simulator for options
    

5 Low Discrepancy Sequences

This section provides three types of random number generators for univorm and normal distributed deviates. These area pseudo random number generator and a halton and sobol generator for low discrepancy sequences.

    runif.pseudo    Uniform pseudo random numbers
    rnorm.pseudo    Normal pseudo random numbers
    

    runif.halton    Uniform Halton sequence
    rnorm.halton    Normal Halton sequence
    

    runif.sobol     Uniform scrambled Sobol sequence
    rnorm.sobol     Normal scrambled Sobol sequence
    

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6 Heston Nandi Garch Fit

Her we provide functions to model the GARCH(1,1) price paths which underly Heston and Nandi's option pricing model. The functions are:

  
    hngarchSim           simulates a Heston-Nandi Garch(1,1) process
    hngarchFit           fits parameters of a Heston Nandi Garch(1,1) model
    

    hngarchStats         returns true moments of the log-Return distribution
    

    print.hngarch        print method, \cr
    summary.hngarch      diagnostic summary
    

7 Heston Nandi Garch Options

This section comes with functions to valuate Heston-Nandi options. Provided are functions to compute the option price and the delta and gamma sensitivities for call and put options.

    HNGOption            Heston-Nandi GARCH(1,1) option price
    HNGGreeks            Heston-Nandi GARCH(1,1) option sensitivities
    HNGCharacteristics   combines option prices and sensitivities
    

About Rmetrics

The fOptions Rmetrics package is written for educational support in teaching "Computational Finance and Financial Engineering" and licensed under the GPL.

fOptions documentation built on Sept. 9, 2022, 3:10 p.m.