[Returnanalytics-commits] r2173 - pkg/PortfolioAnalytics/sandbox/attribution/R
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Wed Jul 18 12:49:36 CEST 2012
Author: ababii
Date: 2012-07-18 12:49:36 +0200 (Wed, 18 Jul 2012)
New Revision: 2173
Added:
pkg/PortfolioAnalytics/sandbox/attribution/R/MarketTiming.R
Removed:
pkg/PortfolioAnalytics/sandbox/attribution/R/MertonHenriksson.R
pkg/PortfolioAnalytics/sandbox/attribution/R/TreynorMazuy.R
Log:
- Replace MartonHenriksson and TreynorMazuy by MarketTiming
- currently returns only gamma, but works with multiple assets and multiple benchmarks
Added: pkg/PortfolioAnalytics/sandbox/attribution/R/MarketTiming.R
===================================================================
--- pkg/PortfolioAnalytics/sandbox/attribution/R/MarketTiming.R (rev 0)
+++ pkg/PortfolioAnalytics/sandbox/attribution/R/MarketTiming.R 2012-07-18 10:49:36 UTC (rev 2173)
@@ -0,0 +1,92 @@
+#' Market timing models
+#'
+#' Allows to estimate Treynor-Mazuy or Merton-Henriksson market timing model.
+#' The Treynor-Mazuy model is essentially a quadratic extension of the basic
+#' CAPM. It is estimated using a multiple regression. The second term in the
+#' regression is the value of excess return squared. If the gamma coefficient
+#' in the regression is positive, then the estimated equation describes a
+#' convex upward-sloping regression "line". The quadratic regression is:
+#' \deqn{R_{p}-R_{f}=\alpha+\beta (R_{b} - R_{f})+\gamma (R_{b}-R_{f})^2+
+#' \varepsilon_{p}}{Rp - Rf = alpha + beta(Rb -Rf) + gamma(Rb - Rf)^2 +
+#' epsilonp}
+#' \eqn{\gamma}{gamma} is a measure of the curvature of the regression line.
+#' If \eqn{\gamma}{gamma} is positive, this would indicate that the manager's
+#' investment strategy demonstrates market timing ability.
+#'
+#' The basic idea of the Merton-Henriksson test is to perform a multiple
+#' regression in which the dependent variable (portfolio excess return and a
+#' second variable that mimics the payoff to an option). This second variable
+#' is zero when the market excess return is at or below zero and is 1 when it
+#' is above zero:
+#' \deqn{R_{p}-R_{f}=\alpha+\beta (R_{b}-R_{f})+\gamma D+\varepsilon_{p}}{Rp -
+#' Rf = alpha + beta * (Rb - Rf) + gamma * D + epsilonp}
+#' where all variables are familiar from the CAPM model, except for the
+#' up-market return \eqn{D=max(0,R_{b}-R_{f})}{D = max(0, Rb - Rf)} and market
+#' timing abilities \eqn{\gamma}{gamma}
+#' @param Ra an xts, vector, matrix, data frame, timeSeries or zoo object of
+#' the asset returns
+#' @param Rb an xts, vector, matrix, data frame, timeSeries or zoo object of
+#' the benchmark asset return
+#' @param Rf risk free rate, in same period as your returns
+#' @param method used to select between Treynor-Mazuy and Henriksson-Merton
+#' models. May be any of: \itemize{ \item TM - Treynor-Mazuy model,
+#' \item HM - Henriksson-Merton model}}
+#' @param \dots any other passthrough parameters
+#' @author Andrii Babii
+#' @seealso \code{\link{CAPM.beta}}, \code{\link{MertonHendriksson}}
+#' @references J. Christopherson, D. Carino, W. Ferson. \emph{Portfolio
+#' Performance Measurement and Benchmarking}. 2009. McGraw-Hill, p. 127-133.
+#' \cr J. L. Treynor and K. Mazuy, "Can Mutual Funds Outguess the Market?"
+#' \emph{Harvard Business Review}, vol44, 1966, pp. 131-136
+#' \cr Roy D. Henriksson and Robert C. Merton, "On Market Timing and Investment
+#' Performance. II. Statistical Procedures for Evaluating Forecast Skills,"
+#' \emph{Journal of Business}, vol.54, October 1981, pp.513-533 \cr
+#' @examples
+#'
+#' data(managers)
+#' MarketTiming(managers[,1,drop=FALSE], managers[,8,drop=FALSE], Rf=.035/12, method = "HM")
+#' MarketTiming(managers[80:120,1:6], managers[80:120,7,drop=FALSE], managers[80:120,10,drop=FALSE])
+#' MarketTiming(managers[80:120,1:6], managers[80:120,8:7], managers[80:120,10,drop=FALSE], method = "TM")
+#'
+#' @export
+MarketTiming <- function (Ra, Rb, Rf = 0, method = c("TM", "HM"))
+{ # @author Andrii Babii
+
+ # FUNCTION
+
+ Ra = checkData(Ra)
+ Rb = checkData(Rb)
+ if (!is.null(dim(Rf)))
+ Rf = checkData(Rf)
+ Ra.ncols = NCOL(Ra)
+ Rb.ncols = NCOL(Rb)
+ pairs = expand.grid(1:Ra.ncols, 1:Rb.ncols)
+ method = method[1]
+ xRa = Return.excess(Ra, Rf)
+ xRb = Return.excess(Rb, Rf)
+
+
+ mt <- function (xRa, xRb)
+ {
+ switch(method,
+ "HM" = { S = xRb > 0 },
+ "TM" = { S = xRb }
+ )
+ R = merge(xRa, xRb, xRb*S)
+ R.df = as.data.frame(R)
+ model = lm(R.df[, 1] ~ 1 + ., data = R.df[, -1])
+ return(coef(model)[3])
+ }
+
+ result = apply(pairs, 1, FUN = function(n, xRa, xRb)
+ mt(xRa[, n[1]], xRb[, n[2]]), xRa = xRa, xRb = xRb)
+
+ if(length(result) == 1)
+ return(result)
+ else {
+ result = matrix(result, ncol = Ra.ncols, nrow = Rb.ncols, byrow = TRUE)
+ rownames(result) = paste("Gamma:", colnames(Rb))
+ colnames(result) = colnames(Ra)
+ return(result)
+ }
+}
\ No newline at end of file
Deleted: pkg/PortfolioAnalytics/sandbox/attribution/R/MertonHenriksson.R
===================================================================
--- pkg/PortfolioAnalytics/sandbox/attribution/R/MertonHenriksson.R 2012-07-17 08:46:48 UTC (rev 2172)
+++ pkg/PortfolioAnalytics/sandbox/attribution/R/MertonHenriksson.R 2012-07-18 10:49:36 UTC (rev 2173)
@@ -1,72 +0,0 @@
-#' Merton-Henriksson market timing model
-#'
-#' Test of market-timing skill (the ability to profitably move from one asset
-#' class to another) developed by Henriksson and Merton. The basic idea of the
-#' test is to perform a multiple regression in which the dependent variable
-#' (portfolio excess return and a second variable that mimics the payoff to an
-#' option). This second variable is zero when the market excess return is at or
-#' below zero and is 1 when it is above zero:
-#' \deqn{R_{p}-R_{f}=\alpha+\beta (R_{b}-R_{f})+\gamma D+\varepsilon_{p}}{Rp -
-#' Rf = alpha + beta * (Rb - Rf) + gamma * D + epsilonp}
-#' where all variables are familiar from the CAPM model, except for the
-#' up-market return \eqn{D=max(0,R_{b}-R_{f})}{D = max(0, Rb - Rf)} and market
-#' timing abilities \eqn{\gamma}{gamma}
-#'
-#' @param Ra an xts, vector, matrix, data frame, timeSeries or zoo object of
-#' the asset returns
-#' @param Rb an xts, vector, matrix, data frame, timeSeries or zoo object of
-#' the benchmark asset return
-#' @param Rf risk free rate, in same period as your returns
-#' @param \dots any other passthrough parameters
-#' @author Andrii Babii
-#' @seealso \code{\link{CAPM.beta}}, \code{\link{TreynorMazuy}}
-#' @references J. Christopherson, D. Carino, W. Ferson. \emph{Portfolio
-#' Performance Measurement and Benchmarking}. 2009. McGraw-Hill, p. 127-129.
-#' \cr Roy D. Henriksson and Robert C. Merton, "On Market Timing and Investment
-#' Performance. II. Statistical Procedures for Evaluating Forecast Skills,"
-#' \emph{Journal of Business}, vol.54, October 1981, pp.513-533 \cr
-#' @examples
-#'
-#' data(managers)
-#' MertonHenriksson(managers[,1,drop=FALSE], managers[,8,drop=FALSE], Rf=.035/12)
-#' MertonHenriksson(managers[80:120,1:6], managers[80:120,7,drop=FALSE], managers[80:120,10,drop=FALSE])
-#' MertonHenriksson(managers[80:120,1:6], managers[80:120,8:7], managers[80:120,10,drop=FALSE])
-#'
-#' @export
-MertonHenriksson <- function (Ra, Rb, Rf = 0, ...)
-{ # @author Andrii Babii
-
- # FUNCTION
-
- Ra = checkData(Ra)
- Rb = checkData(Rb)
- if (!is.null(dim(Rf)))
- Rf = checkData(Rf)
- Ra.ncols = NCOL(Ra)
- Rb.ncols = NCOL(Rb)
- pairs = expand.grid(1:Ra.ncols, 1:Rb.ncols)
-
- xRa = Return.excess(Ra, Rf)
- xRb = Return.excess(Rb, Rf)
-
- mh <- function (xRa, xRb)
- {
- D = pmax(0, xRb)
- y = xRa
- X = cbind(rep(1, length(xRa)), xRb, D)
- bhat = solve(t(X) %*% X) %*% t(X) %*% y
- return(bhat[3])
- }
-
- result = apply(pairs, 1, FUN = function(n, xRa, xRb)
- mh(xRa[, n[1]], xRb[, n[2]]), xRa = xRa, xRb = xRb)
-
- if(length(result) == 1)
- return(result)
- else {
- result = matrix(result, ncol = Ra.ncols, nrow = Rb.ncols, byrow = TRUE)
- rownames(result) = paste("Gamma:", colnames(Rb))
- colnames(result) = colnames(Ra)
- return(result)
- }
-}
\ No newline at end of file
Deleted: pkg/PortfolioAnalytics/sandbox/attribution/R/TreynorMazuy.R
===================================================================
--- pkg/PortfolioAnalytics/sandbox/attribution/R/TreynorMazuy.R 2012-07-17 08:46:48 UTC (rev 2172)
+++ pkg/PortfolioAnalytics/sandbox/attribution/R/TreynorMazuy.R 2012-07-18 10:49:36 UTC (rev 2173)
@@ -1,67 +0,0 @@
-#' Treynor-Mazuy market timing model
-#'
-#' The Treynor-Mazuy model is essentially a quadratic extension of the basic
-#' CAPM. It is estimated using a multiple regression. The second term in the
-#' regression is the value of excess return squared. If the gamma coefficient
-#' in the regression is positive, then the estimated equation describes a
-#' convex upward-sloping regression "line". The quadratic regression is:
-#' \deqn{R_{p}-R_{f}=\alpha+\beta (R_{b} - R_{f})+\gamma (R_{b}-R_{f})^2+
-#' \varepsilon_{p}}{Rp - Rf = alpha + beta(Rb -Rf) + gamma(Rb - Rf)^2 +
-#' epsilonp}
-#' \eqn{\gamma}{gamma} is a measure of the curvature of the regression line.
-#' If \eqn{\gamma}{gamma} is positive, this would indicate that the manager's
-#' investment strategy demonstrates market timing ability.
-#'
-#' @param Ra an xts, vector, matrix, data frame, timeSeries or zoo object of
-#' the asset returns
-#' @param Rb an xts, vector, matrix, data frame, timeSeries or zoo object of
-#' the benchmark asset return
-#' @param Rf risk free rate, in same period as your returns
-#' @param \dots any other passthrough parameters
-#' @author Andrii Babii
-#' @seealso \code{\link{CAPM.beta}}, \code{\link{MertonHendriksson}}
-#' @references J. Christopherson, D. Carino, W. Ferson. \emph{Portfolio
-#' Performance Measurement and Benchmarking}. 2009. McGraw-Hill, p. 129-133.
-#' \cr J. L. Treynor and K. Mazuy, "Can Mutual Funds Outguess the Market?"
-#' \emph{Harvard Business Review}, vol44, 1966, pp. 131-136 \cr
-#' @examples
-#'
-#' data(managers)
-#' TreynorMazuy(managers[,1,drop=FALSE], managers[,8,drop=FALSE], Rf=.035/12)
-#' TreynorMazuy(managers[80:120,1:6], managers[80:120,7,drop=FALSE], managers[80:120,10,drop=FALSE])
-#' TreynorMazuy(managers[80:120,1:6], managers[80:120,8:7], managers[80:120,10,drop=FALSE])
-#'
-#' @export
-TreynorMazuy <- function (Ra, Rb, Rf = 0, ...)
-{ # @author Andrii Babii
-
- # FUNCTION
-
- Ra = checkData(Ra)
- Rb = checkData(Rb)
- if (!is.null(dim(Rf)))
- Rf = checkData(Rf)
- Ra.ncols = NCOL(Ra)
- Rb.ncols = NCOL(Rb)
- pairs = expand.grid(1:Ra.ncols, 1:Rb.ncols)
-
- tm <- function (Ra, Rb, Rf)
- {
- y = Ra - Rf
- X = cbind(rep(1, length(Ra)), Rb - Rf, (Rb - Rf)^2)
- bhat = solve(t(X) %*% X) %*% t(X) %*% y
- return(bhat[3])
- }
-
- result = apply(pairs, 1, FUN = function(n, Ra, Rb, Rf)
- tm(Ra[, n[1]], Rb[, n[2]], Rf), Ra = Ra, Rb = Rb, Rf = Rf)
-
- if(length(result) == 1)
- return(result)
- else {
- result = matrix(result, ncol = Ra.ncols, nrow = Rb.ncols, byrow = TRUE)
- rownames(result) = paste("Gamma:", colnames(Rb))
- colnames(result) = colnames(Ra)
- return(result)
- }
-}
\ No newline at end of file
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