CRAN Task View: Empirical Finance

This CRAN Task View contains a list of packages useful for empirical work in Finance, grouped by topic.

Besides these packages, a very wide variety of functions suitable for empirical work in Finance is provided by both the basic R system (and its set of recommended core packages), and a number of other packages on the Comprehensive R Archive Network (CRAN). Consequently, several of the other CRAN Task Views may contain suitable packages, in particular the Econometrics Task View.

Please send suggestions for additions and extensions for this task view to the task view maintainer .

Standard regression models

• Linear models such as ordinary least squares (OLS) can be estimated by lm() (from by the stats package contained in the basic R distribution). Maximum Likelihood (ML) estimation can be undertaken with the optim() function. Non-linear least squares can be estimated with the nls() function, as well as with nlme() from the nlme package.
• For the linear model, a variety of regression diagnostic tests are provided by the car, lmtest, strucchange, urca, uroot, and sandwich packages. The Rcmdr and Zelig packages provide user interfaces that may be of interest as well.

Time series

• Classical time series functionality is provided by the arima() and KalmanLike() commands in the basic R distribution.
• The dse packages provides a variety of more advanced estimation methods; fracdiff can estimate fractionally integrated series; longmemo covers related material; FracSim simulates fractional Levy series.
• For volatily modeling, the standard GARCH(1,1) model can be estimated with the garch() function in the tseries package. Rmetrisc (see below) contains the fGarch package which has additional models.
• The realized package contains functions to model and visualize 'realized' variance (from high-frequency sampling, as opposed to historical volatility and variance from lower-frequency returns, or implied volatility from option prices).
• Unit root and cointegration tests are provided by tseries, urca and uroot. The Rmetrics packages fSeries and fMultivar contain a number of estimation functions for ARMA, GARCH, long memory models, unit roots and more.
• The ArDec implements autoregressive time series decomposition in a Bayesian framework; MSBVAR provides Bayesian estimation of vector autoregressive models. The dlm package provides Bayesian and likelihood analysis of dynamic linear models (ie linear Gaussian state space models).
• The vars package offer estimation, diagnostics, forecasting and error decomposition of VAR and SVAR model in a classical framework.
• The dyn and dynlm are suitable for dynamic (linear) regression models.
• Several packages provide wavelet analysis functionality: rwt, wavelets, waveslim, wavethresh. Some methods from chaos theory are provided by the package tseriesChaos, and tsDyn adds time-series analysis based on dynamical systems therory.
• The forecasting bundle adds functions and dataset for forecasting problems.

Finance

• The Rmetrics bundle comprised of the fArma, fAsianOptions, fAssets, fBasics, fBonds, fCalendar, fCopulae, fEcofin, fExoticOptions, fExtremes, fGarch, fImport, fMultivar, fNonlinear, fOptions, fPortfolio, fRegression, fSeries, fTrading, fUnitRoots and fUtilities packages contains a very large number of relevant functions for different aspect of empirical and computational finance.
• The RQuantLib package provides several option-pricing functions as well as some fixed-income functionality from the QuantLib project to R.
• The quantmod package offers a number of functions for quantitative modelling in finance as well as data acqusition, plotting and other utilities.
• The portfolio package contains classes for equity portfolio management; the portfolioSim builds a related simulation framework and tradeCosts estimates the potential impact of trades on the prevalent market prices. The backtest offers tools to explore portfollio-based hypotheses about financial instruments.
• The TTR contains functions to construct technical trading rules in R.
• The financial package can compute present values, cash flows and other simple finance calculations.
• The sde package provides simulation and inference functionality for stochastic differential equations.
• The termstrc package contains methods for the estimation of zero-coupon yield curves and spread curves based the parametric Nelson and Siegel (1987) method with the Svensson (1994) extension, and the McCulloch (1975) cubic splines approach.
• The vrtest package contains a number of variance ratio tests for the weak-form of the efficient markets hypothesis.

Risk management

• The VaR package estimates Value-at-Risk, and several packages provide functionality for Extreme Value Theory models: evd, evdbayes, evir, extRremes, ismec, POT.
• The CreditMetrics package provides functions for Credit Risk modeling.
• The QRMlib covers quantitative risk modelling.
• The mvtnorm package provides code for multivariate Normal and t-distributions.
• The Rmetrics packages fPortfolio and fExtremes also contain a number of relevant functions.
• The copula and fgac packages cover multivariate dependency structures using copula methods.
• The actuar package provides an actuarial perspective to risk management.
• The ghyp provides generalized hyberbolic distribution functions as well as procedures for VaR, CVaR or target-return portfolio optimizations.

Books

• The FinTS package provides an R companion to Tsay (2005), Analysis of Financial Time Series , 2nd ed. Wiley, and includes data sets, functions and script files to work some of the examples.

Data and date management

• The its, zoo and fCalendar (part of Rmetrics) packages provide support for irregularly-spaced time series. The xts package extends zoo specifically for financial time series.
• fCalendar also addresses calendar issues such as recurring holidays for a large number of financial centers, and provides code for high-frequency data sets.
• The RBloomberg package can access Bloomberg data (but requires a Bloomberg installations on a Windows PC).

CRAN packages:

• actuar
• ArDec
• backtest
• car
• copula
• CreditMetrics
• dlm
• dse
• dyn
• dynlm
• evd
• evdbayes
• evir
• extRemes
• fArma (core)
• fAsianOptions (core)
• fAssets (core)
• fBasics (core)
• fBonds (core)
• fCalendar (core)
• fCopulae (core)
• fEcofin (core)
• fExoticOptions (core)
• fExtremes (core)
• fgac
• fGarch (core)
• fImport (core)
• financial
• fMultivar (core)
• fNonlinear (core)
• fOptions (core)
• forecasting
• fPortfolio (core)
• fracdiff
• FracSim
• fRegression (core)
• fSeries (core)
• fTrading (core)
• fUnitRoots (core)
• fUtilities (core)
• ghyp
• ismev
• its (core)
• lmtest
• longmemo
• MSBVAR
• mvtnorm
• PerformanceAnalytics (core)
• portfolio
• portfolioSim
• POT
• QRMlib
• quantmod
• RBloomberg
• Rcmdr
• realized
• Rmetrics (core)
• RQuantLib
• rwt
• sandwich
• sde
• strucchange
• termstrc
• tradeCosts
• tsDyn
• tseries (core)
• tseriesChaos
• TTR
• urca (core)
• uroot
• VaR
• vars
• vrtest
• wavelets
• waveslim
• wavethresh
• xts
• Zelig
• zoo (core)

Related links:

• CRAN Task View: Econometrics
• CRAN Task View: Multivariate
• CRAN Task View: SocialSciences
• Rmetrics contains a wealth of R code for Finance
• Quantlib is a C++ library for quantitative finance
• Mailing list: R Special Interest Group Finance
• Russell indexes data
• MSCI indexes data
• French/Fama data
• Wilshire indexes data
• Barra indexes data
• Rene Carmona
• Eric Zivot
• R Code for Ruppert's 'Statistics and Finance'
• FinancePack and FractalPack