Last updated on 20201023
by Dirk Eddelbuettel
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 ,
Multivariate, Optimization, Robust,
SocialSciences and TimeSeries Task Views.
The ctv
package supports these Task Views. Its functions
install.views
and update.views
allow,
respectively, installation or update of packages from a given Task View;
the option coreOnly
can restrict operations to packages labeled as
core below.
Contributions are always welcome, and encouraged. Since the start of
this CRAN task view in April 2005, most contributions have arrived as
email suggestions. The source file for this particular task view file
now also reside in a GitHub repository (see below) so that pull
requests are also possible.
Standard regression models
 A detailed overview of the available regression methodologies is
provided by the Econometrics task view. This is
complemented by the Robust task view, which focuses on more
robust and resistant methods.
 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 standard optim()
function. Many other suitable methods
are listed in the Optimization view. Nonlinear 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, and sandwich packages.
The Rcmdr package provide user
interfaces that may be of interest as well.
Time series
 A detailed overview of tools for time series analysis can be found in
the TimeSeries task view. Below a brief overview of the
most important methods in finance is given.
 Classical time series functionality is provided
by the
arima()
and KalmanLike()
commands in the
basic R distribution.
 The dse and timsac packages provide a variety of more
advanced estimation methods; fracdiff can
estimate fractionally integrated series; longmemo covers
related material.
 For volatility modeling, the standard GARCH(1,1) model can
be estimated with the
garch()
function in the
tseries package. Rmetrics (see below) contains
the fGarch package which has additional models.
The rugarch package can be used to model a
variety of univariate GARCH models with extensions such as
ARFIMA, inmean, external regressors and various other
specifications; with methods for fit, forecast, simulation,
inference and plotting are provided too. The rmgarch
builds on it to provide the ability to estimate several multivariate
GARCH models. The
betategarch package can estimate and simulate the
BetatEGARCH model by Harvey. The bayesGARCH
package can perform Bayesian estimation of a GARCH(1,1)
model with Student's t innovations. For multivariate
models, the gogarch package provides functions for
generalized orthogonal GARCH models. The
gets package (which was preceded by a related package
AutoSEARCH) provides automated generaltospecific model selection of the mean and
logvolatility of a logARCHX model. The lgarch package
can estimate and fit logGARCH models. The garchx
package estimate GARCH models with leverage and external
covariates. The bmgarch package fits several
multivariate GARCH models in a Bayesian setting.
 Unit root and cointegration tests are provided by tseries,
and urca.
The Rmetrics packages timeSeries and
fMultivar contain a number of estimation functions for
ARMA, GARCH, long memory models, unit roots and more.
The CADFtest package implements the Hansen unit root test.

dlm package provides
Bayesian and likelihood analysis of dynamic linear models (i.e.
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 packages 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.
tsDyn adds time series analysis based on dynamical systems theory.

The forecast package adds functions for
forecasting problems.

The tsfa package provides functions for time series factor analysis.

The stochvol package implements Bayesian
estimation of stochastic volatility using Markov Chain Monte
Carlo, and factorstochvol extends this to the
multivariate case.

The MSGARCH package adds methods to fit (by Maximum Likelihood
or Bayesian), simulate, and forecast various MarkovSwitching GARCH processes.

The DriftBurstHypothesis package estimates a ttest statistics for the
explosive drift burst hypothesis (Christensen, Oomen and Reno, 2018).
Finance
 The Rmetrics suite of packages comprises
fAssets,
fBasics, fBonds, timeDate (formerly: fCalendar),
fCopulae, fExoticOptions,
fExtremes, fGarch, fImport,
fNonlinear, fOptions, fPortfolio,
fRegression, timeSeries (formerly: fSeries),
fTrading,
and contains a very large number of relevant functions for different aspect of empirical
and computational finance.
 The RQuantLib package provides several optionpricing
functions as well as some fixedincome functionality from the
QuantLib project to R. The RcppQuantuccia provides a
smaller subset of QuantLib functionality as a headeronly library;
at current only some calendaring functionality is exposed.
 The quantmod package offers a number of functions for
quantitative modelling in finance as well as data acquisition, plotting
and other utilities.
 The backtest offers tools to
explore portfoliobased hypotheses about financial instruments.
The pa package offers performance attribution
functionality for equity portfolios.
 The PerformanceAnalytics package contains a large number
of functions for portfolio performance calculations and risk management.
 The TTR contains functions to construct technical
trading rules in R.
 The sde package provides simulation and inference functionality
for stochastic differential equations.
 The YieldCurve package contains methods for the estimation
of zerocoupon yield curves and spread curves based the parametric
Nelson and Siegel (1987) method with the Svensson (1994)
extension. The former package adds the McCulloch (1975) cubic
splines approach, the latter package adds the Diebold and Li approach.
The SmithWilsonYieldCurve construct the yield curve using
the SmithWilson approach based on LIBOR and SWAP rates.
 The vrtest package contains a number of variance ratio
tests for the weakform of the efficient markets hypothesis.
 The gmm package provides generalized method of moments
(GMM) estimations function that are often used when estimating the
parameters of the moment conditions implied by an asset pricing
model.
 The BurStFin and BurStMisc package has a collection of
function for Finance including the estimation of covariance
matrices.
 The AmericanCallOpt package contains a pricer for
different American call options.
 The VarSwapPrice package can price a variance swap
via a portfolio of European options contracts.
 The FinAsym package implements the Lee and Ready (1991)
and Easley and O'Hara (1987) tests for, respectively, trade direction,
and probability of informed trading.

The parma package provides support for portfolio
allocation and risk management applications.

The GUIDE package provides a GUI for
DErivatives and contains numerous pricer examples as
well as interactive 2d and 3d plots to study these pricing
functions.

The SharpeR package contains a collection of tools
for analyzing significance of trading strategies, based on the
Sharpe ratio and overfit of the same.

The RND package implements various functions to extract riskneutral densities
from option prices.

The LSMonteCarlo package can price American Options via the Least Squares Monte Carlo
method.

The BenfordTests package provides
seven statistical tests and support functions for determining if numerical data
could conform to Benford's law.

The OptHedging package values call and put option portfolio and implements an
optimal hedging strategy.

The markovchain package provides functionality to
easily handle and analyse discrete Markov chains.

The ycinterextra package models yield curve interpolation and extrapolation using
via the NelsonSiegel, Svensson, or SmithWilson models, as well as Hermite cubic splines.

The tvm package models provides functions for time
value of money such as cashflows and yield curves.

The MarkowitzR package provides functions to test
the statistical significance of Markowitz portfolios.

The pbo package models the probability of backtest
overfitting, performance degradation, probability of loss, and the
stochastic dominance when analysing trading strategies.

The OptionPricing package implements
efficient Monte Carlo algorithms for the price and the sensitivities
of Asian and European Options under Geometric Brownian Motion.

The matchingMarkets package implements a structural
estimator to correct for the bias arising from endogenous matching
(e.g. group formation in microfinance or matching of firms and
venture capitalists).

The restimizeapi package interfaces the API at
www.estimize.com which provides crowdsourced earnings estimates.
 The credule package is another pricer for credit
default swaps.
 The obAnalytics package analyses and visualizes
information from events in limit order book data.
 The derivmkts package adds a set of pricing and
expository functions useful in teaching derivatives markets.
 The PortfolioEffectHFT package provides portfolio
analysis suitable for intraday and highfrequency data, and also interfaces the
PortfolioEffect service.
 The ragtop package prices equity derivatives under an extension
to Black and Scholes supporting default under a powerlaw link price
and hazard rate.
 The sharpeRratio package adds momentfree estimation of Sharpe ratios.
 The QuantTools package offers enhanced quantitative trading
and modeling tools.
 The pinbasic package adds tools for fast and stable estimates the Probability of
Informed Trading (PIN) by Easley et al, and offers factorizations of
the model likelihood. The InfoTrad packages also estimates
PIN and extends it different factorization and estimation algorithms.
 The FinancialMath package contains financial math and derivatives pricing functions
as required by the actuarial exams by the Society of Actuaries and Casualty Actuarial Society
'Financial Mathematics' exam.
 The tidyquant package rearranges functionality from
several other key packages for use in the socalled tidyverse.
 The BCC1997 prices European options under the Bakshi,
Cao anc Chen (1997) model for stochastic volatility, stochastic rates
and random jumps.

The Sim.DiffProc package provides functions to simulate
and analyse multidimensional Itô and Stratonovitch stochastic calculus for
continuoustime models.

The BLModel package computes the posterior distribution
in a BlackLitterman model from a prior distribution given by asset
returns and continuous distribution of views given by an external function.
 The rpatrec package aims to recognise charting patterns
in (financial) time series data.
 The PortfolioOptim can solve both small and large
sample portfolio optimization.
 The estudy2 package implements most commonly used
parametric and nonparametric eventstudy methodology tests.
 The DtD package computes the distance to
default per Merton's model.
 The PeerPerformance package analyzes performance of
investments funds relative to its peers in a pairwise manner that
is robust to false discoveries.
 The crseEventStudy package provides another eventstudy
tool to analyse abnormal return in longhorizon events.
 The simfinapi package provides R access to
SimFin fundamental financial statement data (given an API key).
Risk management

The packages qrmtools and qrmdata provide tools and data for
standard tasks in Quantitative Risk Management (QRM) and accompany the book
of McNeil, Frey, Embrechts (2005, 2015, "Quantitative Risk Management: Concepts, Techniques, Tools").

The Task View ExtremeValue regroups a number of relevant packages.

The packages CreditMetrics provides function for modelling credit risks.

The mvtnorm package provides code for multivariate Normal and tdistributions.

The package nvmix provides functionality for multivariate normal variance mixtures
(including normal and t for noninteger degrees of freedom).

The Rmetrics packages fPortfolio and
fExtremes also contain a number of relevant functions.

The packages copula and copulaData cover a wide range
of modeling tasks for copulas.

The fgac package implements generalized Archimedean copulas.

The actuar package provides an actuarial
perspective to risk management.

The ghyp package provides generalized hyberbolic distribution
functions as well as procedures for VaR, CVaR or targetreturn
portfolio optimizations.

The ChainLadder package provides functions for modeling
insurance claim reserves; and the lifecontingencies package
provides functions for financial and actuarial evaluations of life contingencies.

The frmqa package aims to collect functions for Financial Risk Management and Quantitative Analysis.

The ESG package can be used to model for asset projection, a scenariobased simulation approach.

The riskSimul package provides efficient simulation
procedures to estimate tail loss probabilities and conditional
excess for a stock portfolios where logreturns are assumed to
follow a tcopula model with generalized hyperbolic or t marginals.

The GCPM package analyzes the default risk of credit
portfolio using both analytical and simulation approaches.

The FatTailsR package provides a family of four
distributions tailored to distribution with symmetric and asymmetric
fat tails.

The Dowd package contains functions ported from the 'MMR2'
toolbox offered in Kevin Dowd's book "Measuring Market Risk".

The PortRisk package computes portfolio risk attribution.

The NetworkRiskMeasures package implements some risk measures for financial networks such as DebtRank, Impact
Susceptibility, Impact Diffusion and Impact Fluidity.

The Risk package computes 26 financial risk measures for any continuous distribution.

The RiskPortfolios package constructs riskbased
portfolios as per the corresponding papers by Ardia et al.

The reinsureR package models reinsurances a class Claims
whose objective is to store claims and premiums, on which different
treaties can be applied.

The RM2006 package estimates conditional covariance matrix
using the RiskMetrics 2006 methodology described in Zumbach (2007).
 The cvar package computes expected shortfall and value at risk for continuous distributions.
 riskParityPortfolio offers fast implementations for constructing riskparity portfolios.
Books
 The NMOF package provides functions, examples and data
from Numerical Methods and Optimization in Finance by Manfred Gilli, Dietmar Maringer and
Enrico Schumann (2011), including the different optimization heuristics such as
Differential Evolution, Genetic Algorithms, Particle Swarms, and Threshold Accepting.
 The FRAPO package provides data sets and code for the
book Financial Risk Modelling and Portfolio Optimization with
R by Bernhard Pfaff (2013).
Data and date management
 The zoo and
timeDate (part of Rmetrics) packages provide support for
irregularlyspaced time series. The xts package extends
zoo specifically for financial time series. See the
TimeSeries task view for more details.
 timeDate also addresses
calendar issues such as recurring holidays for a large number of
financial centers, and provides code for highfrequency data sets.

The fame package can access Fame time series databases (but
also requires a Fame backend). The tis package provides
time indices and timeindexed series compatible with Fame
frequencies.

The TSdbi package provides a unifying interface for
several time series data base backends, and its SQL implementations
provide a database table design.

The IBrokers package provides access to the Interactive Brokers
API for data access (but requires an account to access the service).

The data.table package provides very efficient and fast
access to inmemory data sets such as asset prices.

The TFX package provides an interface to the TrueFX (TM)
service for free streaming realtime and historical
tickbytick market data for interbank foreign exchange
rates at the millisecond resolution.

The package highfrequency contains functionality
to manage, clean and match highfrequency trades and quotes
data and enables users to calculate various liquidity
measures, estimate and forecast volatility, and investigate
microstructure noise and intraday periodicity.

The Rbitcoin package offers access to Bitcoin
exchange APIs (mtgox, bitstamp, btce, kraken) via public and
private API calls and integration of data structures for all
markets.

The bizdays package compute business days if
provided a list of holidays.

The TAQMNGR package manages tickbytick (equity)
transaction data performing 'cleaning', 'aggregation' and
'import' where cleaning and aggregation are performed
according to Brownlees and Gallo (2006).

The Rblpapi package offers efficient access to the Bloomberg API
and allows
bdp
, bdh
, and bds
queries as well as data retrieval both in (regular time)bars and
ticks (albeit without subsecond resolution).

The finreportr package can download reports from the SEC
Edgar database, and relies on, inter alia, the XBRL
package for parsing these reports.

The GetTDData package imports Brazilian government
bonds data (such as LTN, NTNB and LFT ) from the Tesouro Direto website.

The fmdates package implements common date calculations
according to the ISDA schedules, and can check for business in
different locales.