stockPortfolio (version 1.2)

stockPortfolio-package: Build and manage stock models and portfolios

Description

The package stockPortfolio is a quantitative approach to portfolio allocation among stocks. The package includes functions to download historical data from Yahoo Finance, build models, estimate optimal portfolios, and test portfolios. A large range of graphical features have been included for visual understanding.

Details

Package:

stockPortfolio

Type:

Package

Version:

1.2

Date:

2012-03-14

License:

GPL (>= 2)

LazyLoad:

yes

A common starting point in the package is with the getReturns function, which can be used to obtain stock data using an internet connection. Using an object of class "stockReturns" from the getReturns function, one can build a stock model using the stockModel function. There are four model options in stockModel: no model where a portfolio is selected based on empirical returns, variances, and covariances among the stocks, the single index model, constant correlation model, and the multigroup model. After a stock model has been built, the user can obtain an estimate of the optimal portfolio allocation among those stocks using optimalPort. Additionally, one can test out models and portfolios on data sets that are either supplied by the user or are output from getReturns.

While most objects can be plotted, there are two specialty plotting functions: portPossCurve and portCloud. The function portPossCurve plots the portfolio possibilities curve based on a model, and portCloud plots a cloud of possible portfolios based on a model.

Three data sets and one data "key" have been included as a sample data set: stock94, stock99, stock04, stock94Info.

References

Blume, Marshall E. "Portfolio Theory: A Step Toward Its Practical Application," Journal of Business, 43, No. 2 (April 1970), pp. 152-173.

Markowitz, Harry. "Portfolio Selection Efficient Diversification of Investments." New York: John Wiley and Sons, 1959.

Elton, Edwin, J., Gruber, Martin, J., Padberg, Manfred, W. "Simple Criteria for Optimal Portfolio Selection," Journal of Finance, XI, No. 5 (Dec. 1976), pp. 1341-1357.

Elton, Edwin, J., Gruber, Martin, J., Padberg, Manfred, W. "Simple Rules for Optimal Portfolio Selection: The Multi Group Case," Journal of Financial and Quantitative Analysis, XII, No. 3 (Sept. 1977), pp. 329-345.

Elton, Edwin, J., Gruber, Martin, J., Padberg, Manfred, W. "Simple Criteria for Optimal Portfolio Selection: Tracing Out the Efficient Frontier," Journal of Finance, XIII, No. 1 (March 1978), pp. 296-302.

Elton, E.J., Gruber, M.J., Brown, S.J., and Goetzmann, W.N. "Modern Portfolio Theory and Investment Analysis" (6th Edition). John Wiley and Sons, 2003.

Examples

#===> two examples of downloading data <===#
## Not run: grEx1 <- getReturns(c('C','BAC'), start='2004-01-01', end='2008-12-31')
## Not run: grEx2 <- getReturns(c('KEY', 'WFC', 'JPM', 'AMR', 'BIIB', 'AMGN'))

#===> build four models <===#
data(stock99)
data(stock94Info)
non <- stockModel(stock99, drop=25, model='none', industry=stock94Info$industry)
sim <- stockModel(stock99, model='SIM', industry=stock94Info$industry, index=25)
ccm <- stockModel(stock99, drop=25, model='CCM', industry=stock94Info$industry)
mgm <- stockModel(stock99, drop=25, model='MGM', industry=stock94Info$industry)

#===> build optimal portfolios <===#
opNon <- optimalPort(non)
opSim <- optimalPort(sim)
opCcm <- optimalPort(ccm)
opMgm <- optimalPort(mgm)

#===> test portfolios on 2004-9 <===#
data(stock04)
tpNon <- testPort(stock04, opNon)
tpSim <- testPort(stock04, opSim)
tpCcm <- testPort(stock04, opCcm)
tpMgm <- testPort(stock04, opMgm)

#===> compare performances <===#
plot(tpNon)
lines(tpSim, col=2, lty=2)
lines(tpCcm, col=3, lty=3)
lines(tpMgm, col=4, lty=4)
legend('topleft', col=1:4, lty=1:4, legend=c('none', 'SIM', 'CCM', 'MGM'))