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Dowd (version 0.12)

Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's Book Measuring Market Risk

Description

'Kevin Dowd's' book Measuring Market Risk is a widely read book in the area of risk measurement by students and practitioners alike. As he claims, 'MATLAB' indeed might have been the most suitable language when he originally wrote the functions, but, with growing popularity of R it is not entirely valid. As 'Dowd's' code was not intended to be error free and were mainly for reference, some functions in this package have inherited those errors. An attempt will be made in future releases to identify and correct them. 'Dowd's' original code can be downloaded from www.kevindowd.org/measuring-market-risk/. It should be noted that 'Dowd' offers both 'MMR2' and 'MMR1' toolboxes. Only 'MMR2' was ported to R. 'MMR2' is more recent version of 'MMR1' toolbox and they both have mostly similar function. The toolbox mainly contains different parametric and non parametric methods for measurement of market risk as well as backtesting risk measurement methods.

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Version

Install

install.packages('Dowd')

Monthly Downloads

309

Version

0.12

License

GPL

Maintainer

Dinesh Acharya

Last Published

March 10th, 2016

Functions in Dowd (0.12)

Plots cumulative density for AD test and computes confidence interval for AD test stat.

BootstrapESFigure

Plots figure of bootstrapped ES

Plots cumulative density for KS test and computes confidence interval for KS test stat.

AmericanPutVaRBinomial

Estimates VaR of American vanilla put using binomial tree.

DefaultRiskyBondVaR

VaR for default risky bond portfolio

ChristoffersenBacktestForUnconditionalCoverage

Christoffersen Backtest for Unconditional Coverage

Estimates VaR with Box-Cox transformation

Plots log-t ES against confidence level and holding period

GumbelESPlot2DCl

CdfOfSumUsingGaussianCopula

Derives prob ( X + Y < quantile) using Gaussian copula

BlancoIhleBacktest

Blanco-Ihle forecast evaluation backtest measure

Monte Carlo VaR for DB pension

AmericanPutESBinomial

Estimates ES of American vanilla put using binomial tree.

AdjustedNormalESHotspots

Hotspots for ES adjusted by Cornish-Fisher correction

Frechet Expected Shortfall

Value at Risk of a portfolio using Historical Estimator

Bootstrapped ES for specified confidence level

FilterStrategyLogNormalVaR

Log Normal VaR with filter strategy

CornishFisherES

Frechet Value at Risk

VaR for Generalized Pareto

FrechetVaRPlot2DCl

Plots Frechet Value at Risk against Cl

BootstrapESConfInterval

Bootstrapped ES Confidence Interval

AdjustedVarianceCovarianceVaR

Cornish-Fisher adjusted variance-covariance VaR

Monte Carlo VaR for DC pension

GumbelVaRPlot2DCl

AmericanPutPriceBinomial

Binomial Put Price

Plots historical simulation VaR against confidence level

BootstrapVaRConfInterval

Bootstrapped VaR Confidence Interval

JarqueBeraBacktest

Jarque-Bera backtest for normality.

Expected Shortfall of a portfolio using Historical Estimator

NormalESPlot2DCL

Plots normal ES against confidence level

BlackScholesCallESSim

ES of Black-Scholes call using Monte Carlo Simulation

Expected Shortfall for Generalized Pareto

ES for normally distributed P/L

BlackScholesPutESSim

ES of Black-Scholes put using Monte Carlo Simulation

ShortBlackScholesCallVaR

Derives VaR of a short Black Scholes call option

R-version of Kevin Dowd's MATLAB Toolbox from book "Measuring Market Risk".

BootstrapVaRFigure

Plots figure of bootstrapped VaR

Percentile of historical simulation ES distribution function

ES for normally distributed geometric returns

NormalVaRConfidenceInterval

Generates Monte Carlo 95% Confidence Intervals for normal VaR

Plots historical simulation ES against confidence level

LogNormalESDFPerc

Percentiles of ES distribution function for normally distributed geometric returns

KernelESBoxKernel

Calculates ES using box kernel approach

CornishFisherVaR

Corn-Fisher VaR

Percentiles of VaR distribution function for Student-t

Percentiles of ES distribution function for Student-t

GParetoMultipleMEFPlot

Plot of Emperical and 2 Generalised Pareto mean excess functions

Percentile of historical simulation VaR distribution function

Plot of Emperical and Generalised Pareto mean excess functions

Student's T Quantile - Quantile Plot

PickandsEstimator

Pickands Estimator

AdjustedNormalVaRHotspots

Hotspots for VaR adjusted by Cornish-Fisher correction

CdfOfSumUsingGumbelCopula

Derives prob ( X + Y < quantile) using Gumbel copula

Plots cummulative density for Kuiper test and computes confidence interval for Kuiper test stat.

ES for t distributed geometric returns

Plots log-t ES against confidence level

KernelVaREpanechinikovKernel

Calculates VaR using epanechinikov kernel approach

NormalVaRPlot3D

Plots normal VaR in 3D against confidence level and holding period

HillQuantileEstimator

Hill Quantile Estimator

KernelVaRBoxKernel

Calculates VaR using box kernel approach

KernelESNormalKernel

Calculates ES using normal kernel approach

LogNormalVaRPlot3D

Plots log normal VaR against confidence level and holding period

LogNormalVaRPlot2DCL

Plots log normal VaR against confidence level

KernelVaRNormalKernel

Calculates VaR using normal kernel approach

LogNormalVaRETLPlot2DCL

Plots log normal VaR and ETL against confidence level

FrechetESPlot2DCl

Plots Frechet Expected Shortfall against confidence level

Figure of t - VaR and ES and pdf against L/P

Estimates VaR plot using principal components analysis

GaussianCopulaVaR

Bivariate Gaussian Copule VaR

First (binomial) Lopez forecast evaluation backtest score measure

NormalESPlot2DHP

Plots normal ES against holding period

LogtVaRPlot2DCL

Plots log-t VaR against confidence level

KernelVaRTriangleKernel

Calculates VaR using triangle kernel approach

Percentiles of ES distribution function for t-distributed P/L

Bootstrapped VaR for specified confidence level

CdfOfSumUsingProductCopula

Derives prob ( X + Y < quantile) using Product copula

GumbelCopulaVaR

Bivariate Gumbel Copule VaR

LogNormalESPlot2DCL

Plots log normal ES against confidence level

VaR for normally distributed P/L

HSVaRESPlot2DCl

Plots historical simulation VaR and ES against confidence level

VaR of Insurance Portfolio

AmericanPutESSim

Estimates ES of American vanilla put using binomial option valuation tree and Monte Carlo Simulation

BlackScholesCallPrice

Price of European Call Option

BlackScholesPutPrice

Price of European Put Option

Figure of Historical SImulation VaR and ES and histogram of L/P

NormalVaRPlot2DHP

Plots normal VaR against holding period

ProductCopulaVaR

Bivariate Product Copule VaR

Estimates ES with Box-Cox transformation

BinomialBacktest

Carries out the binomial backtest for a VaR risk measurement model.

NormalSpectralRiskMeasure

Estimates the spectral risk measure of a portfolio

AdjustedVarianceCovarianceES

Cornish-Fisher adjusted Variance-Covariance ES

Percentiles of ES distribution function for normally distributed P/L data

KernelESTriangleKernel

Calculates ES using triangle kernel approach

ChristoffersenBacktestForIndependence

Christoffersen Backtest for Independence

Figure of t- VaR and pdf against L/P

LogNormalVaRFigure

Figure of lognormal VaR and pdf against L/P

VarianceCovarianceES

Variance-covariance ES for normally distributed returns

NormalESHotspots

Hotspots for normal ES

tQuantileStandardError

Standard error of t quantile estimate

LogNormalESPlot3D

Plots log normal ES against confidence level and holding period

VaR for t distributed geometric returns

Plots t VaR against holding period

Figure of Historical SImulation VaR and histogram of L/P

Plots t VaR against confidence level

LogNormalESFigure

Figure of lognormal VaR and ES and pdf against L/P

LogNormalVaRPlot2DHP

Plots log normal VaR against holding period

LongBlackScholesCallVaR

Derives VaR of a long Black Scholes call option

VaR for t distributed P/L

Plots log-t ES against holding period

VaR and ES of Insurance Portfolio

LogNormalESPlot2DHP

Plots log normal ES against holding period

Plots t- ES against confidence level

NormalQuantileStandardError

Standard error of normal quantile estimate

Figure of normal VaR and ES and pdf against L/P

Estimates VaR by principal components analysis

Plots log-t VaR against confidence level and holding period

NormalVaRFigure

Figure of normal VaR and pdf against L/P

Plots normal ES against confidence level and holding period

LongBlackScholesPutVaR

Derives VaR of a long Black Scholes put option

NormalVaRDFPerc

Percentiles of VaR distribution function for normally distributed P/L

Pickand Estimator - Tail Sample Size Plot

Plots t ES against confidence level and holding period

Plots t ES against holding period

Plots t VaR against confidence level and holding period

Estimates ES by principal components analysis

Plots t VaR and ES against confidence level

NormalVaRHotspots

Hotspots for normal VaR

ShortBlackScholesPutVaR

Derives VaR of a short Black Scholes put option

ES for t distributed P/L

LogNormalVaRDFPerc

Percentiles of VaR distribution function for normally distributed geometric returns

NormalESConfidenceInterval

Generates Monte Carlo 95% Confidence Intervals for normal ES

LogtVaRPlot2DHP

Plots log-t VaR against holding period

StopLossLogNormalVaR

Log Normal VaR with stop loss limit

Normal Quantile Quantile Plot

Percentiles of VaR distribution function

KernelESEpanechinikovKernel

Calculates ES using Epanechinikov kernel approach

VaR for normally distributed geometric returns

Mean Excess Function Plot

NormalVaRPlot2DCL

Plots normal VaR against confidence level

VarianceCovarianceVaR

Variance-covariance VaR for normally distributed returns