[Returnanalytics-commits] r2138 - pkg/PortfolioAnalytics/sandbox/attribution/man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Mon Jul 9 18:54:42 CEST 2012
Author: braverock
Date: 2012-07-09 18:54:41 +0200 (Mon, 09 Jul 2012)
New Revision: 2138
Modified:
pkg/PortfolioAnalytics/sandbox/attribution/man/Attribution.Rd
pkg/PortfolioAnalytics/sandbox/attribution/man/AttributionFixedIncome.Rd
pkg/PortfolioAnalytics/sandbox/attribution/man/Carino.Rd
pkg/PortfolioAnalytics/sandbox/attribution/man/Conv.option.Rd
pkg/PortfolioAnalytics/sandbox/attribution/man/DaviesLaker.Rd
pkg/PortfolioAnalytics/sandbox/attribution/man/Frongello.Rd
pkg/PortfolioAnalytics/sandbox/attribution/man/Grap.Rd
pkg/PortfolioAnalytics/sandbox/attribution/man/Menchero.Rd
Log:
- update roxygen docs
Modified: pkg/PortfolioAnalytics/sandbox/attribution/man/Attribution.Rd
===================================================================
--- pkg/PortfolioAnalytics/sandbox/attribution/man/Attribution.Rd 2012-07-09 16:54:15 UTC (rev 2137)
+++ pkg/PortfolioAnalytics/sandbox/attribution/man/Attribution.Rd 2012-07-09 16:54:41 UTC (rev 2138)
@@ -1,217 +1,217 @@
-\name{Attribution}
-\alias{Attribution}
-\title{performs arithmetic attribution}
-\usage{
- Attribution(Rp, wp, Rb, wb, wpf = NA, wbf = NA, S = NA,
- F = NA, Rpl = NA, Rbl = NA, Rbh = NA, bf = FALSE,
- method = c("none", "top.down", "bottom.up"),
- linking = c("none", "carino", "menchero", "grap", "frongello", "davies.laker"),
- geometric = FALSE, adjusted = FALSE)
-}
-\arguments{
- \item{Rp}{T x n xts, data frame or matrix of portfolio
- returns}
-
- \item{wp}{vector, xts, data frame or matrix of portfolio
- weights}
-
- \item{Rb}{T x n xts, data frame or matrix of benchmark
- returns}
-
- \item{wb}{vector, xts, data frame or matrix of benchmark
- weights}
-
- \item{method}{Used to select the priority between
- allocation and selection effects in arithmetic
- attribution. May be any of: \itemize{ \item none -
- present allocation, selection and interaction effects
- independently, \item top.down - the priority is given to
- the sector allocation. Interaction term is combined with
- the security selection effect, \item bottom.up - the
- priority is given to the security selection. Interaction
- term is combined with the sector allocation effect}}
-
- \item{wpf}{vector, xts, data frame or matrix with
- portfolio weights of currency forward contracts}
-
- \item{wbf}{vector, xts, data frame or matrix with
- benchmark weights of currency forward contracts}
-
- \item{S}{(T+1) x n xts, data frame or matrix with spot
- rates. The first date should coincide with the first date
- of portfolio returns}
-
- \item{F}{(T+1) x n xts, data frame or matrix with forward
- rates. The first date should coincide with the first date
- of portfolio returns}
-
- \item{Rpl}{xts, data frame or matrix of portfolio returns
- in local currency}
-
- \item{Rbl}{xts, data frame or matrix of benchmark returns
- in local currency}
-
- \item{Rbh}{xts, data frame or matrix of benchmark returns
- hedged into the base currency}
-
- \item{bf}{TRUE for Brinson and Fachler and FALSE for
- Brinson, Hood and Beebower arithmetic attribution}
-
- \item{linking}{Used to select the linking method to
- present the multi-period summary of arithmetic
- attribution effects. May be any of: \itemize{ \item
- carino - logarithmic linking coefficient method, \item
- menchero - Menchero's smoothing algorithm, \item grap -
- linking approach developed by GRAP, \item frongello -
- Frongello's linking method \item davies.laker - Davies
- and Laker's linking method}
-
- \item{geometric}{TRUE/FALSE, whether to use geometric or
- arithmetic excess returns for the attribution analysis}
-
- \item{adjusted}{TRUE/FALSE, whether to show original or
- smoothed attribution effects for each period}
-}
-\value{
- returns a list with the following components: excess
- returns with annualized excess returns over all periods,
- attribution effects (allocation, selection and
- interaction)
-}
-\description{
- Performance attribution analysis. Portfolio performance
- measured relative to a benchmark gives an indication of
- the value-added by the portfolio. Equipped with weights
- and returns of portfolio segments, we can dissect the
- value-added into useful components. This function is
- based on the sector-based approach to the attribution.
- The workhorse is the Brinson model that explains the
- arithmetic difference between portfolio and benchmark
- returns. That is it breaks down the arithmetic excess
- returns at one level. If returns and weights are
- available at the lowest level (e.g. for individual
- instruments), the aggregation up to the chosen level from
- the hierarchy can be done using Return.level function.
- The attribution effects can be computed for several
- periods. The multi-period summary is obtained using one
- of linking methods: Carino, Menchero, GRAP, Frongello. It
- also allows to break down the geometric excess returns,
- which link naturally over time. Finally, it annualizes
- arithmetic and geometric excess returns similarly to the
- portfolio and/or benchmark returns annualization.
-}
-\details{
- The arithmetic excess returns are decomposed into the sum
- of allocation, selection and interaction effects across
- \deqn{n} sectors:
- \deqn{r-b=\overset{n}{\underset{i=1}{\sum}}\left(A_{i}+S_{i}+I_{i}\right)}
- The arithmetic attribution effects for the category
- \deqn{i} are computed as suggested in the Brinson, Hood
- and Beebower (1986): \deqn{A_{i}=(w_{pi}-w_{bi})\times
- R_{bi}} - allocation effect
- \deqn{S_{i}=w_{pi}\times(R_{pi}-R_{bi})} - selection
- effect \deqn{I_{i}=(w_{pi}-w_{bi})\times(r_{i}-b_{i})} -
- interaction effect \deqn{r} - total portfolio returns
- \deqn{b} - total benchmark returns \deqn{w_{pi}} -
- weights of the category \deqn{i} in the portfolio
- \deqn{w_{bi}} - weigths of the category \deqn{i} in the
- benchmark \deqn{R_{pi}} - returns of the portfolio
- category \deqn{i} \deqn{R_{bi}} - returns of the
- benchmark category \deqn{i} If Brinson and Fachler (1985)
- is selected the allocation effect differs:
- \deqn{A_{i}=(w_{pi}-w_{bi})\times (R_{bi} - b)} Depending
- on goals we can give priority to the allocation or to the
- selection effects. If the priority is given to the sector
- allocation the interaction term will be combined with the
- security selection effect (top-down approach). If the
- priority is given to the security selection, the
- interaction term will be combined with the
- asset-allocation effect (bottom-up approach). Usually we
- have more than one period. In that case individual
- arithmetic attribution effects should be adjusted using
- linking methods. Adjusted arithmetic attribution effects
- can be summed up over time to provide the multi-period
- summary:
- \deqn{r-b=\overset{T}{\underset{t=1}{\sum}}\left(A_{t}'+S_{t}'+I_{t}'\right)}
- , where \deqn{T} - number of periods; prime stands for
- the adjustment. The geometric attribution effects do not
- suffer from the linking problem. Moreover we don't have
- the interaction term. For more details about the
- geometric attribution see the documentation to
- \code{link{Attribution.geometric}} Finally, arithmetic
- annualized excess returns are computed as the arithmetic
- difference between annualised portfolio and benchmark
- returns: \deqn{AAER=r_{a}-b_{a}}; the geometric
- annualized excess returns are computed as the geometric
- difference between annualized portfolio and benchmark
- returns: \deqn{GAER=\frac{1+r_{a}}{1+b_{a}}-1} In the
- case of multi-currency portfolio, the currency return,
- currency surprise and forward premium should be
- specified. The multi-currency arithmetic attribution is
- handled following Ankrim and Hensel (1992). Currency
- returns are decomposed into the sum of the currency
- surprise and the forward premium: \deqn{R_{ci} = R_{cei}
- + R_{fpi}}, where \deqn{R_{cei} = \frac{S_{i}^{t+1} -
- F_{i}^{t+1}}{S_{i}^{t}} \deqn{R_{fpi} =
- \frac{F_{i}^{t+1}}{S_{i}^{t}} - 1} \deqn{S_{i}^{t}} -
- stop rate for asset i at time t \deqn{F_{i}^{t}} -
- forward rate for asset i at time t Excess returns are
- decomposed into the sum of allocation, selection and
- interaction effects as in the standard Brinson model:
- \deqn{r-b=\overset{n}{\underset{i=1}{\sum}}\left(A_{i}+S_{i}+I_{i}\right)}
- However the allocation effect is computed taking into
- account currency effects:
- \deqn{A_{i}=(w_{pi}-w_{bi})\times (R_{bi} - R_{ci} -
- R_{l})} - allocation \deqn{R_{l} =
- \overset{n}{\underset{i=1}{\sum}}w_{bi}\times(R_{bi}-R_{ci})}
- - benchmark return adjusted for currecy. The contribution
- from currency is analogous to asset allocation:
- \deqn{C_{i} = (w_{pi} - w_{bi}) \times (R_{cei} - e) +
- (w_{pfi} - w_{bfi}) \times (R_{fi} - e)} where \deqn{e =
- \overset{n}{\underset{i=1}{\sum}}w_{bi}\times R_{cei}}
- The final term, forward premium, is also analogous to the
- asset allocation: \deqn{R_{fi} = (w_{pi} - w_{bi}) \times
- (R_{fpi} - d)} where \deqn{d =
- \overset{n}{\underset{i=1}{\sum}}w_{bi}\times R_{fpi}}
- \deqn{R_{fpi}} - forward premium
-}
-\examples{
-data(attrib)
-Attribution(Rp, wp, Rb, wb, method = "top.down", linking = "carino")
-}
-\author{
- Andrii Babii
-}
-\references{
- Ankrim, E. and Hensel, C. \emph{Multi-currency
- performance attribution}.Russell Research Commentary.
- November 2002
-
- Bacon, C. \emph{Practical Portfolio Performance
- Measurement and Attribution}. Wiley. 2004. Chapter 5, 6,
- 8
-
- Christopherson, Jon A., Carino, David R., Ferson, Wayne
- E. \emph{Portfolio Performance Measurement and
- Benchmarking}. McGraw-Hill. 2009. Chapter 18-19
-
- Brinson, G. and Fachler, N. (1985) \emph{Measuring non-US
- equity portfolio performance}. Journal of Portfolio
- Management. Spring, 73–76.
-
- Gary P. Brinson, L. Randolph Hood, and Gilbert L.
- Beebower, \emph{Determinants of Portfolio Performance},
- Financial Analysts Journal, vol. 42, no. 4, July/August
- 1986, pp. 39–44.
-
- Karnosky, D. and Singer, B. \emph{Global asset management
- and performance attribution. The Research Foundation of
- the Institute of Chartered Financial Analysts}. February
- 1994.
-}
-\seealso{
- \code{\link{Attribution.levels}},
- \code{\link{Attribution.geometric}}
-}
-\keyword{attribution}
-
+\name{Attribution}
+\alias{Attribution}
+\title{performs arithmetic attribution}
+\usage{
+ Attribution(Rp, wp, Rb, wb, wpf = NA, wbf = NA, S = NA,
+ F = NA, Rpl = NA, Rbl = NA, Rbh = NA, bf = FALSE,
+ method = c("none", "top.down", "bottom.up"),
+ linking = c("carino", "menchero", "grap", "frongello", "davies.laker"),
+ geometric = FALSE, adjusted = FALSE)
+}
+\arguments{
+ \item{Rp}{T x n xts, data frame or matrix of portfolio
+ returns}
+
+ \item{wp}{vector, xts, data frame or matrix of portfolio
+ weights}
+
+ \item{Rb}{T x n xts, data frame or matrix of benchmark
+ returns}
+
+ \item{wb}{vector, xts, data frame or matrix of benchmark
+ weights}
+
+ \item{method}{Used to select the priority between
+ allocation and selection effects in arithmetic
+ attribution. May be any of: \itemize{ \item none -
+ present allocation, selection and interaction effects
+ independently, \item top.down - the priority is given to
+ the sector allocation. Interaction term is combined with
+ the security selection effect, \item bottom.up - the
+ priority is given to the security selection. Interaction
+ term is combined with the sector allocation effect}. By
+ default "none" is selected}
+
+ \item{wpf}{vector, xts, data frame or matrix with
+ portfolio weights of currency forward contracts}
+
+ \item{wbf}{vector, xts, data frame or matrix with
+ benchmark weights of currency forward contracts}
+
+ \item{S}{(T+1) x n xts, data frame or matrix with spot
+ rates. The first date should coincide with the first date
+ of portfolio returns}
+
+ \item{F}{(T+1) x n xts, data frame or matrix with forward
+ rates. The first date should coincide with the first date
+ of portfolio returns}
+
+ \item{Rpl}{xts, data frame or matrix of portfolio returns
+ in local currency}
+
+ \item{Rbl}{xts, data frame or matrix of benchmark returns
+ in local currency}
+
+ \item{Rbh}{xts, data frame or matrix of benchmark returns
+ hedged into the base currency}
+
+ \item{bf}{TRUE for Brinson and Fachler and FALSE for
+ Brinson, Hood and Beebower arithmetic attribution}
+
+ \item{linking}{Used to select the linking method to
+ present the multi-period summary of arithmetic
+ attribution effects. May be any of: \itemize{ \item
+ carino - logarithmic linking coefficient method, \item
+ menchero - Menchero's smoothing algorithm, \item grap -
+ linking approach developed by GRAP, \item frongello -
+ Frongello's linking method \item davies.laker - Davies
+ and Laker's linking method By default Carino linking is
+ selected}
+
+ \item{geometric}{TRUE/FALSE, whether to use geometric or
+ arithmetic excess returns for the attribution analysis}
+
+ \item{adjusted}{TRUE/FALSE, whether to show original or
+ smoothed attribution effects for each period}
+}
+\value{
+ returns a list with the following components: excess
+ returns with annualized excess returns over all periods,
+ attribution effects (allocation, selection and
+ interaction)
+}
+\description{
+ Performance attribution analysis. Portfolio performance
+ measured relative to a benchmark gives an indication of
+ the value-added by the portfolio. Equipped with weights
+ and returns of portfolio segments, we can dissect the
+ value-added into useful components. This function is
+ based on the sector-based approach to the attribution.
+ The workhorse is the Brinson model that explains the
+ arithmetic difference between portfolio and benchmark
+ returns. That is it breaks down the arithmetic excess
+ returns at one level. If returns and weights are
+ available at the lowest level (e.g. for individual
+ instruments), the aggregation up to the chosen level from
+ the hierarchy can be done using Return.level function.
+ The attribution effects can be computed for several
+ periods. The multi-period summary is obtained using one
+ of linking methods: Carino, Menchero, GRAP, Frongello. It
+ also allows to break down the geometric excess returns,
+ which link naturally over time. Finally, it annualizes
+ arithmetic and geometric excess returns similarly to the
+ portfolio and/or benchmark returns annualization.
+}
+\details{
+ The arithmetic excess returns are decomposed into the sum
+ of allocation, selection and interaction effects across
+ \deqn{n} sectors:
+ \deqn{r-b=\overset{n}{\underset{i=1}{\sum}}\left(A_{i}+S_{i}+I_{i}\right)}
+ The arithmetic attribution effects for the category
+ \deqn{i} are computed as suggested in the Brinson, Hood
+ and Beebower (1986): \deqn{A_{i}=(w_{pi}-w_{bi})\times
+ R_{bi}} - allocation effect
+ \deqn{S_{i}=w_{pi}\times(R_{pi}-R_{bi})} - selection
+ effect \deqn{I_{i}=(w_{pi}-w_{bi})\times(r_{i}-b_{i})} -
+ interaction effect \deqn{r} - total portfolio returns
+ \deqn{b} - total benchmark returns \deqn{w_{pi}} -
+ weights of the category \deqn{i} in the portfolio
+ \deqn{w_{bi}} - weigths of the category \deqn{i} in the
+ benchmark \deqn{R_{pi}} - returns of the portfolio
+ category \deqn{i} \deqn{R_{bi}} - returns of the
+ benchmark category \deqn{i} If Brinson and Fachler (1985)
+ is selected the allocation effect differs:
+ \deqn{A_{i}=(w_{pi}-w_{bi})\times (R_{bi} - b)} Depending
+ on goals we can give priority to the allocation or to the
+ selection effects. If the priority is given to the sector
+ allocation the interaction term will be combined with the
+ security selection effect (top-down approach). If the
+ priority is given to the security selection, the
+ interaction term will be combined with the
+ asset-allocation effect (bottom-up approach). Usually we
+ have more than one period. In that case individual
+ arithmetic attribution effects should be adjusted using
+ linking methods. Adjusted arithmetic attribution effects
+ can be summed up over time to provide the multi-period
+ summary:
+ \deqn{r-b=\overset{T}{\underset{t=1}{\sum}}\left(A_{t}'+S_{t}'+I_{t}'\right)}
+ , where \deqn{T} - number of periods; prime stands for
+ the adjustment. The geometric attribution effects do not
+ suffer from the linking problem. Moreover we don't have
+ the interaction term. For more details about the
+ geometric attribution see the documentation to
+ \code{link{Attribution.geometric}} Finally, arithmetic
+ annualized excess returns are computed as the arithmetic
+ difference between annualised portfolio and benchmark
+ returns: \deqn{AAER=r_{a}-b_{a}}; the geometric
+ annualized excess returns are computed as the geometric
+ difference between annualized portfolio and benchmark
+ returns: \deqn{GAER=\frac{1+r_{a}}{1+b_{a}}-1} In the
+ case of multi-currency portfolio, the currency return,
+ currency surprise and forward premium should be
+ specified. The multi-currency arithmetic attribution is
+ handled following Ankrim and Hensel (1992). Currency
+ returns are decomposed into the sum of the currency
+ surprise and the forward premium: \deqn{R_{ci} = R_{cei}
+ + R_{fpi}}, where \deqn{R_{cei} = \frac{S_{i}^{t+1} -
+ F_{i}^{t+1}}{S_{i}^{t}} \deqn{R_{fpi} =
+ \frac{F_{i}^{t+1}}{S_{i}^{t}} - 1} \deqn{S_{i}^{t}} -
+ stop rate for asset i at time t \deqn{F_{i}^{t}} -
+ forward rate for asset i at time t Excess returns are
+ decomposed into the sum of allocation, selection and
+ interaction effects as in the standard Brinson model:
+ \deqn{r-b=\overset{n}{\underset{i=1}{\sum}}\left(A_{i}+S_{i}+I_{i}\right)}
+ However the allocation effect is computed taking into
+ account currency effects:
+ \deqn{A_{i}=(w_{pi}-w_{bi})\times (R_{bi} - R_{ci} -
+ R_{l})} - allocation \deqn{R_{l} =
+ \overset{n}{\underset{i=1}{\sum}}w_{bi}\times(R_{bi}-R_{ci})}
+ - benchmark return adjusted for currecy. The contribution
+ from currency is analogous to asset allocation:
+ \deqn{C_{i} = (w_{pi} - w_{bi}) \times (R_{cei} - e) +
+ (w_{pfi} - w_{bfi}) \times (R_{fi} - e)} where \deqn{e =
+ \overset{n}{\underset{i=1}{\sum}}w_{bi}\times R_{cei}}
+ The final term, forward premium, is also analogous to the
+ asset allocation: \deqn{R_{fi} = (w_{pi} - w_{bi}) \times
+ (R_{fpi} - d)} where \deqn{d =
+ \overset{n}{\underset{i=1}{\sum}}w_{bi}\times R_{fpi}}
+ \deqn{R_{fpi}} - forward premium
+}
+\examples{
+data(attrib)
+Attribution(Rp, wp, Rb, wb, method = "top.down", linking = "carino")
+}
+\author{
+ Andrii Babii
+}
+\references{
+ Ankrim, E. and Hensel, C. \emph{Multi-currency
+ performance attribution}.Russell Research Commentary.
+ November 2002
+
+ Bacon, C. \emph{Practical Portfolio Performance
+ Measurement and Attribution}. Wiley. 2004. Chapter 5, 6,
+ 8
+
+ Christopherson, Jon A., Carino, David R., Ferson, Wayne
+ E. \emph{Portfolio Performance Measurement and
+ Benchmarking}. McGraw-Hill. 2009. Chapter 18-19
+
+ Brinson, G. and Fachler, N. (1985) \emph{Measuring non-US
+ equity portfolio
+
+ Gary P. Brinson, L. Randolph Hood, and Gilbert L.
+ Beebower, \emph{Determinants of Portfolio Performance},
+ Financial Analysts Journal,
+
+ Karnosky, D. and Singer, B. \emph{Global asset management
+ and performance attribution. The Research Foundation of
+ the Institute of Chartered Financial Analysts}. February
+ 1994.
+}
+\seealso{
+ \code{\link{Attribution.levels}},
+ \code{\link{Attribution.geometric}}
+}
+\keyword{attribution}
+
Modified: pkg/PortfolioAnalytics/sandbox/attribution/man/AttributionFixedIncome.Rd
===================================================================
--- pkg/PortfolioAnalytics/sandbox/attribution/man/AttributionFixedIncome.Rd 2012-07-09 16:54:15 UTC (rev 2137)
+++ pkg/PortfolioAnalytics/sandbox/attribution/man/AttributionFixedIncome.Rd 2012-07-09 16:54:41 UTC (rev 2138)
@@ -1,109 +1,109 @@
-\name{AttributionFixedIncome}
-\alias{attribution}
-\alias{AttributionFixedIncome}
-\alias{fixed}
-\alias{income}
-\title{fixed income attribution}
-\usage{
- AttributionFixedIncome(Rp, wp, Rb, wb, Rf, Dp, Db, S,
- wbf, geometric = FALSE)
-}
-\arguments{
- \item{Rp}{T x n xts, data frame or matrix of portfolio
- returns}
-
- \item{wp}{vector, xts, data frame or matrix of portfolio
- weights}
-
- \item{Rb}{T x n xts, data frame or matrix of benchmark
- returns}
-
- \item{wb}{vector, xts, data frame or matrix of benchmark
- weights}
-
- \item{Rf}{T x n xts, data frame or matrix with risk free
- rates}
-
- \item{Dp}{T x n xts, data frame or matrix with portfolio
- modified duration}
-
- \item{Db}{T x n xts, data frame or matrix with benchmark
- modified duration}
-
- \item{wbf}{vector, xts, data frame or matrix with
- benchmark weights of currency forward contracts}
-
- \item{S}{(T + 1) x n xts, data frame or matrix with spot
- rates. The first date should coincide with the first date
- of portfolio returns}
-
- \item{geometric}{- TRUE/FALSE for geometric/arithmetic
- attribution}
-
- \item{wbf}{vector, xts, data frame or matrix with
- benchmark weights of currency forward contracts}
-}
-\value{
- list with total excess returns decomposed into
- allocation, selection (and currency effects)
-}
-\description{
- Performs fixed income attribution. The investment
- decision process for bond managers is very different from
- that of equity managers, therefore for most fixed income
- investment strategies the standard Brinson model is not
- suitable. Bonds are simply a series of defined future
- cash flows which are relatively easy to price. Fixed
- income performance is therefore driven by changes in the
- shape of the yield curve. Systematic risk in the form of
- duration is a key part of the investment process. Fixed
- income attribution is, in fact, a specialist form of
- risk-adjusted attribution. The arithmetic attribution is
- handled using weighted duration approach (Van Breukelen,
- 2000). The allocation, selection and currency allocation
- effects for category i are: \deqn{A_{i} = (D_{pi}\times
- w_{i}-D_{\beta}\times D_{bi}\times w_{pi})\times (-\Delta
- y_{bi} + \Delta y_{b})} \deqn{S_{i} = D_{i}\times
- w_{i}\times (-\Delta y_{ri} + \Delta y_{bi})} \deqn{C_{i}
- = (w_{pi} - w_{bi})\times (c_{i} + R_{fi} - c')} where
- \deqn{w_{pi}} - portfolio weights \deqn{w_{bi}} -
- benchmark weights \deqn{D_{i}} - modified duration in
- bond category i \deqn{D_{\beta}=\frac{D_{r}}{D_{b}}} -
- duration beta \deqn{D_{r}} - portfolio duration
- \deqn{D_{b}} - benchmark duration \deqn{D_{bi}} -
- benchmark duration for category i \deqn{D_{pi}} -
- portfolio duration for category i \deqn{\Delta y_{ri}} -
- change in portfolio yield for category i \deqn{\Delta
- y_{bi}} - change in benchmark yield for category i
- \deqn{\Delta y_{b}} - change in benchmark yield
- \deqn{R_{ci} - currency returns for category i
- \deqn{R_{fi}} - risk-free rate in currency of asset i
- \deqn{c'= \underset{i}{\sum}w_{bi}\times(R_{ci}+R_{fi})}
- The geometric attribution is adapted using Van Breukelen
- (2000) approach for the arithmetic attribution. The
- individual allocation and selection effects are computed
- as follows:
- \deqn{A_{i}=D_{i}w_{pi}-D_{\beta}D_{bi}w_{bi}}
- \deqn{S_{i}=\frac{D_{pi}}{D_{bi}}\times (R_{bi} - R_{fi})
- + R_{fi}}
-}
-\examples{
-data(attrib)
-AttributionFixedIncome(Rp, wp, Rb, wb, Rf, Dp, Db, S, wbf, geometric = FALSE)
-}
-\author{
- Andrii Babii
-}
-\references{
- Bacon, C. \emph{Practical Portfolio Performance
- Measurement and Attribution}. Wiley. 2004. Chapter 7
-
- Van Breukelen, G. \emph{Fixed income attribution}.
- Journal of Performance Measurement. Summer, 61–68. 2000
-}
-\seealso{
- \code{\link{Attribution.levels}},
- \code{\link{Attribution.geometric}}
-}
-\keyword{attribution}
-
+\name{AttributionFixedIncome}
+\alias{attribution}
+\alias{AttributionFixedIncome}
+\alias{fixed}
+\alias{income}
+\title{fixed income attribution}
+\usage{
+ AttributionFixedIncome(Rp, wp, Rb, wb, Rf, Dp, Db, S,
+ wbf, geometric = FALSE)
+}
+\arguments{
+ \item{Rp}{T x n xts, data frame or matrix of portfolio
+ returns}
+
+ \item{wp}{vector, xts, data frame or matrix of portfolio
+ weights}
+
+ \item{Rb}{T x n xts, data frame or matrix of benchmark
+ returns}
+
+ \item{wb}{vector, xts, data frame or matrix of benchmark
+ weights}
+
+ \item{Rf}{T x n xts, data frame or matrix with risk free
+ rates}
+
+ \item{Dp}{T x n xts, data frame or matrix with portfolio
+ modified duration}
+
+ \item{Db}{T x n xts, data frame or matrix with benchmark
+ modified duration}
+
+ \item{wbf}{vector, xts, data frame or matrix with
+ benchmark weights of currency forward contracts}
+
+ \item{S}{(T + 1) x n xts, data frame or matrix with spot
+ rates. The first date should coincide with the first date
+ of portfolio returns}
+
+ \item{geometric}{- TRUE/FALSE for geometric/arithmetic
+ attribution}
+
+ \item{wbf}{vector, xts, data frame or matrix with
+ benchmark weights of currency forward contracts}
+}
+\value{
+ list with total excess returns decomposed into
+ allocation, selection (and currency effects)
+}
+\description{
+ Performs fixed income attribution. The investment
+ decision process for bond managers is very different from
+ that of equity managers, therefore for most fixed income
+ investment strategies the standard Brinson model is not
+ suitable. Bonds are simply a series of defined future
+ cash flows which are relatively easy to price. Fixed
+ income performance is therefore driven by changes in the
+ shape of the yield curve. Systematic risk in the form of
+ duration is a key part of the investment process. Fixed
+ income attribution is, in fact, a specialist form of
+ risk-adjusted attribution. The arithmetic attribution is
+ handled using weighted duration approach (Van Breukelen,
+ 2000). The allocation, selection and currency allocation
+ effects for category i are: \deqn{A_{i} = (D_{pi}\times
+ w_{i}-D_{\beta}\times D_{bi}\times w_{pi})\times (-\Delta
+ y_{bi} + \Delta y_{b})} \deqn{S_{i} = D_{i}\times
+ w_{i}\times (-\Delta y_{ri} + \Delta y_{bi})} \deqn{C_{i}
+ = (w_{pi} - w_{bi})\times (c_{i} + R_{fi} - c')} where
+ \deqn{w_{pi}} - portfolio weights \deqn{w_{bi}} -
+ benchmark weights \deqn{D_{i}} - modified duration in
+ bond category i \deqn{D_{\beta}=\frac{D_{r}}{D_{b}}} -
+ duration beta \deqn{D_{r}} - portfolio duration
+ \deqn{D_{b}} - benchmark duration \deqn{D_{bi}} -
+ benchmark duration for category i \deqn{D_{pi}} -
+ portfolio duration for category i \deqn{\Delta y_{ri}} -
+ change in portfolio yield for category i \deqn{\Delta
+ y_{bi}} - change in benchmark yield for category i
+ \deqn{\Delta y_{b}} - change in benchmark yield
+ \deqn{R_{ci} - currency returns for category i
+ \deqn{R_{fi}} - risk-free rate in currency of asset i
+ \deqn{c'= \underset{i}{\sum}w_{bi}\times(R_{ci}+R_{fi})}
+ The geometric attribution is adapted using Van Breukelen
+ (2000) approach for the arithmetic attribution. The
+ individual allocation and selection effects are computed
+ as follows:
+ \deqn{A_{i}=D_{i}w_{pi}-D_{\beta}D_{bi}w_{bi}}
+ \deqn{S_{i}=\frac{D_{pi}}{D_{bi}}\times (R_{bi} - R_{fi})
+ + R_{fi}}
+}
+\examples{
+data(attrib)
+AttributionFixedIncome(Rp, wp, Rb, wb, Rf, Dp, Db, S, wbf, geometric = FALSE)
+}
+\author{
+ Andrii Babii
+}
+\references{
+ Bacon, C. \emph{Practical Portfolio Performance
+ Measurement and Attribution}. Wiley. 2004. Chapter 7
+
+ Van Breukelen, G. \emph{Fixed income attribution}.
+ Journal of Performance
+}
+\seealso{
+ \code{\link{Attribution.levels}},
+ \code{\link{Attribution.geometric}}
+}
+\keyword{attribution}
+
Modified: pkg/PortfolioAnalytics/sandbox/attribution/man/Carino.Rd
===================================================================
--- pkg/PortfolioAnalytics/sandbox/attribution/man/Carino.Rd 2012-07-09 16:54:15 UTC (rev 2137)
+++ pkg/PortfolioAnalytics/sandbox/attribution/man/Carino.Rd 2012-07-09 16:54:41 UTC (rev 2138)
@@ -1,79 +1,78 @@
-\name{Carino}
-\alias{Carino}
-\title{calculates total attribution effects using logarithmic smoothing}
-\usage{
- Carino(rp, rb, attributions, adjusted)
-}
-\arguments{
- \item{rp}{xts of portfolio returns}
-
- \item{rb}{xts of benchmark returns}
-
- \item{attributions}{xts with attribution effects}
-
- \item{adjusted}{TRUE/FALSE, whether to show original or
- smoothed attribution effects for each period}
-}
-\value{
- returns a data frame with original attribution effects
- and total attribution effects over multiple periods
-}
-\description{
- Calculates total attribution effects over multiple
- periods using logarithmic linking method. Used internally
- by the \code{\link{Attribution}} function. Arithmetic
- attribution effects do not naturally link over time. This
- function uses logarithmic smoothing to adjust attribution
- effects so that they can be summed up over multiple
- periods. Attribution effect are multiplied by the
- adjustment factor: \deqn{A_{t}' = A_{t} \times
- \frac{k_{t}}{k}},
-}
-\details{
- where \deqn{k_{t} = \frac{log(1 + r_{t}) - log(1 +
- b_{t})}{r_{t} - b_{t}}}, \deqn{k = \frac{log(1 + r) -
- log(1 + b)}{r - b}}.
-
- In case if portfolio and benchmark returns are equal:
- \deqn{k_{t} = \frac{1}{1 + r_{t}} \deqn{A_{t}}' -
- adjusted attribution effects at period \deqn{t}
- \deqn{A_{t}} - unadjusted attribution effects at period
- \deqn{t} \deqn{r_{t}} - portfolio returns at period
- \deqn{t} \deqn{b_{t}} - benchmark returns at period
- \deqn{t} \deqn{r} - total portfolio returns \deqn{b} -
- total benchmark returns \deqn{n} - number of periods The
- total arithmetic excess returns can be explained in terms
- of the sum of adjusted attribution effects: \deqn{r - b =
- \overset{n}{\underset{t=1}{\sum}}\left(Allocation_{t}+Selection_{t}+Interaction_{t}\right)}
-}
-\examples{
-data(attrib)
-Carino(rp, rb, allocation, adjusted = FALSE)
-}
-\author{
- Andrii Babii
-}
-\references{
- Christopherson, Jon A., Carino, David R., Ferson, Wayne
- E. \emph{Portfolio Performance Measurement and
- Benchmarking}. McGraw-Hill. 2009. Chapter 19
-
- Bacon, C. \emph{Practical Portfolio Performance
- Measurement and Attribution}. Wiley. 2004. p. 191-193
-
- Carino, D. (1999) \emph{Combining attribution effects
- over time}. The Journal of Performance Measurement.
- Summer, 5–14.
-}
-\seealso{
- \code{\link{Attribution}} \cr \code{\link{Menchero}} \cr
- \code{\link{Grap}} \cr \code{\link{Frongello}} \cr
- \code{\link{Attribution.geometric}}
-}
-\keyword{arithmetic}
-\keyword{attribution,}
-\keyword{Carino}
-\keyword{linking}
-\keyword{linking,}
-\keyword{logarithmic}
-
+\name{Carino}
+\alias{Carino}
+\title{calculates total attribution effects using logarithmic smoothing}
+\usage{
+ Carino(rp, rb, attributions, adjusted)
+}
+\arguments{
+ \item{rp}{xts of portfolio returns}
+
+ \item{rb}{xts of benchmark returns}
+
+ \item{attributions}{xts with attribution effects}
+
+ \item{adjusted}{TRUE/FALSE, whether to show original or
+ smoothed attribution effects for each period}
+}
+\value{
+ returns a data frame with original attribution effects
+ and total attribution effects over multiple periods
+}
+\description{
+ Calculates total attribution effects over multiple
+ periods using logarithmic linking method. Used internally
+ by the \code{\link{Attribution}} function. Arithmetic
+ attribution effects do not naturally link over time. This
+ function uses logarithmic smoothing to adjust attribution
+ effects so that they can be summed up over multiple
+ periods. Attribution effect are multiplied by the
+ adjustment factor: \deqn{A_{t}' = A_{t} \times
+ \frac{k_{t}}{k}},
+}
+\details{
+ where \deqn{k_{t} = \frac{log(1 + r_{t}) - log(1 +
+ b_{t})}{r_{t} - b_{t}}}, \deqn{k = \frac{log(1 + r) -
+ log(1 + b)}{r - b}}.
+
+ In case if portfolio and benchmark returns are equal:
+ \deqn{k_{t} = \frac{1}{1 + r_{t}} \deqn{A_{t}}' -
+ adjusted attribution effects at period \deqn{t}
+ \deqn{A_{t}} - unadjusted attribution effects at period
+ \deqn{t} \deqn{r_{t}} - portfolio returns at period
+ \deqn{t} \deqn{b_{t}} - benchmark returns at period
+ \deqn{t} \deqn{r} - total portfolio returns \deqn{b} -
+ total benchmark returns \deqn{n} - number of periods The
+ total arithmetic excess returns can be explained in terms
+ of the sum of adjusted attribution effects: \deqn{r - b =
+ \overset{n}{\underset{t=1}{\sum}}\left(Allocation_{t}+Selection_{t}+Interaction_{t}\right)}
+}
+\examples{
+data(attrib)
+Carino(rp, rb, allocation, adjusted = FALSE)
+}
+\author{
+ Andrii Babii
+}
+\references{
+ Christopherson, Jon A., Carino, David R., Ferson, Wayne
+ E. \emph{Portfolio Performance Measurement and
+ Benchmarking}. McGraw-Hill. 2009. Chapter 19
+
+ Bacon, C. \emph{Practical Portfolio Performance
+ Measurement and Attribution}. Wiley. 2004. p. 191-193
+
+ Carino, D. (1999) \emph{Combining attribution effects
+ over time}.
+}
+\seealso{
+ \code{\link{Attribution}} \cr \code{\link{Menchero}} \cr
+ \code{\link{Grap}} \cr \code{\link{Frongello}} \cr
+ \code{\link{Attribution.geometric}}
+}
+\keyword{arithmetic}
+\keyword{attribution,}
+\keyword{Carino}
+\keyword{linking}
+\keyword{linking,}
+\keyword{logarithmic}
+
Modified: pkg/PortfolioAnalytics/sandbox/attribution/man/Conv.option.Rd
===================================================================
--- pkg/PortfolioAnalytics/sandbox/attribution/man/Conv.option.Rd 2012-07-09 16:54:15 UTC (rev 2137)
+++ pkg/PortfolioAnalytics/sandbox/attribution/man/Conv.option.Rd 2012-07-09 16:54:41 UTC (rev 2138)
@@ -1,54 +1,51 @@
-\name{Conv.option}
-\alias{attribution}
-\alias{Conv.option}
-\alias{options}
-\title{convert information about options, warrants or convertible bonds to the
-equivalent of returns}
-\usage{
- Conv.option(option)
-}
-\arguments{
- \item{\code{n}{x 8} matrix containing option ID (as
- rownames), and columns corresponding to (in particular
- order): strike price, number of options, current option
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/returnanalytics -r 2138
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