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NEWS
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PerformanceAnalytics 1.0.4.3 Release Notes
(sent to CRAN 2012-03-29)
This release is aimed almost exclusively at support for
multiple changes made to deal with R core changes, especially in
the areas of multi-column support for sd() and mean().
User functionality should be unchanged.
... and the usual minor things that get changed and updated in the general
course of maintenance.
PerformanceAnalytics roxygen note (2011-10-02):
We're converting the documentation to use roxygen2. If you find any errors or
omissions from previous documentation, please notify us.
We will shift to roxygen documentation with package v1.1
PerformanceAnalytics 1.0.3.1 Release Notes
A change to the behavior of as.xts removed functionality relied on by
PerformanceAnalytics in checkData. Thanks to debugging help from
Jeff Ryan and a one-line patch, everything should work as expected
back through current and older xts versions.
... and the usual minor things that get changed and updated in the general
course of maintenance.
PerformanceAnalytics 1.0.3 Release Notes
(sent to CRAN 2010-08-04)
This is an incremental bugfix and improvement release on the v1.0.x cycle.
We would like to acknowledge feedback and suggestions from
Giuseppe Milicia and Murali Menon which have resulted in changes or
improvements to several functions in this release, mostly to eliminate
problems with edge cases or specific failure modes.
Style functions have been removed in this release and moved to
the new project FactorAnalytics with Eric Zivot on R-Forge.
... and the usual minor things that get changed and updated in the general
course of maintenance.
PerformanceAnalytics 1.0.2 Release Notes
(released to CRAN 2010-04-08)
This release is an incremental improvement on v1.0.x
We've continued to make functions more friendly for use in parallel
execution and optimization environments.
Several bugfixes have been applied to edge case problems, details
are in the full ChangeLog provided with the package.
We've added several new ways of calling functions that can take
moments rather than returns to allow for more robust or other
improved methods of calculating moments.
Added patches to graphics provided by Dominik Locher.
... and the usual minor things that get changed and updated in the general
course of maintenance.
PerformanceAnalytics 1.0.1 Release Notes
(tagged 2010-01-07, not released to CRAN)
This release is predominantly a minor bugfix release.
We've reduced the number of warning() calls throughout the code to better
allow for execution in a highly parallel environment.
We've fixed bugs related to assuming compounding/geometric returns in all
functions that could be affected by such assumptions.
Bugs related to handling matrices pointed out by Dr. Stefan Albrecht
have been removed.
... and the usual minor things that get changed and updated in the general
course of maintenance.
PerformanceAnalytics 1.0.0 Release Notes
(released to CRAN 2009-10-27)
This release marks a major milestone for PerformanceAnalytics. After several
years and acquiring users worldwide, we feel things are stable enough to mark
this release 1.0.0. Hopefully this will decrease the number of changes made to
the interfaces and functionality of the package in the future, and let us work
on other things.
Probably the most new functionality in this release has gone into VaR, ES and
modified VaR and ES. Thanks to some excellent code and research contributions
from Kris Boudt of K.U. Leuven, we've added substantially to the capabilities in
this release. The new 'VaR' and 'ES' functions allow a wide variety of methods
for calculation, and even methods for calculating risk contribution given
portfolio weights. This is great stuff, and we're deeply greatful for Kris'
contribution.
During the past year, we've modified almost every function in the package.
There were two things we wanted to accomplish: move to xts for time series
functions internally, and improve the speed and convenience of the functions.
The move to xts has improved the package immensely. Not only have the time axes
of the graphics improved, but calculations and charts now handle different data
periodicities automatically. Calculations are noticably faster, too.
Users of fPortfolio and other Rmetrics packages can use timeSeries objects with
PA functions seamlessly. Thanks to xts' reclass function, if you input a
timeSeries object into a PA function that calculates a time series result (such
as Drawdowns), that result is delivered as a timeSeries classed object.
All of the functions in PA now support multi-column returns objects. Drop a
data set in, and the calculations are done for each column.
For example:
> > data(managers)
> > SharpeRatio.annualized(managers[,1:8])
HAM1 HAM2 HAM3 HAM4 HAM5 HAM6
1.6033616 1.3240442 1.1488361 0.6169326 0.1933374 1.8380958
EDHEC.LS.EQ SP500.TR
1.6414220 0.6448502
In any re-write like this, there's good news and bad news. The bad news is that
there have been changes to parameter names along the way. The most substantial
of these is anywhere we used 'rf' for the risk free rate, we now use Rf. We've
made the changes to be more consistent and make the code easier to maintain, and
we appreciate your patience.
PerformanceAnalytics v0.9.7 Release Notes
(released to CRAN 2008-10-12)
New Functionality:
This release adds 39 new public functions, an example dataset,
and utilizes R's namespace capability. We have also decreased the number
of "Requires" packages to just "zoo", moving the rest to "Suggests" and
loading them only when needed, with a warning or error (as appropriate) if
they are not available. This should lower both loading time and the memory
footprint of using PerformanceAnalytics.
Risk functionality
We have extended the risk metrics provided by
Performanceanalytics to include multivariate portfolio measures
of Gaussian and Cornish fisher VaR and Expected Shortfall.
Functions:
* GES.MM
* GVaR.MM
* mES.MM
* mVaR.MM
Modified Sharpe Ratios
Earlier versions of PerformanceAnalytics contained the modified
Sharpe Ration based on the Cornish fisher expansion. we have
added additional modified Sharpe ratios to calculate portfolio
ratios for both Gaussian and modified Cornish Fisher Var and
Expected Shortfall of the multivariate portfolio distribution.
Functions:
* SR.GES.MM
* SR.GVaR.MM
* SR.mES.MM
* SR.mVaR.MM
* SR.StdDev.MM
TODO: need to wrap the SharpeRatio function to take a "method"
argument and return one or all.
Style Analysis
We are happy to announce that style analysis, long a goal of this
package, has made significant progress in this release, with the
addition of four new functions.
These functions calculate style weights using an asset class
style model as described in detail in Sharpe (1992). The use of
quadratic programming to determine a fund's exposures to the
changes in returns of major asset classes is usually referred to
as "style analysis".
Functions:
* chart.RollingStyle
calculates and displays those weights in
rolling windows through time.
* chart.Style
calculates and displays style weights calculated
over a single period.
* style.fit
manages the calculation of the factor weights by method
* style.QPfit
calculates the specific constraint case that requires
quadratic programming
Charts
We've added three new graph functions in this release:
chart.VaRSensitivity
Creates a chart of Value-at-Risk estimates by confidence interval
for multiple methods. Possibly useful for comparing a calculated
VaR method to the historical VaR.
chart.SnailTrail
A scatter chart that shows how rolling calculations of annualized
return and annualized standard deviation have proceeded through
time. The color of lines and dots on the chart diminishes with
respect to time. May be helpful for showing the trend of the
return/risk characteristics of the fund over time.
chart.StackedBar
This creates a stacked column chart with time on the horizontal
axis and values in categories. This kind of chart is commonly
used for showing portfolio 'weights' through time, although the
function will plot any values by category. This is a primitive
function and is expected to improve.
Moments of a distribution
We have added several functions to calculate standardized moments
and multivariate moments of an asset or multivariate portfolio
distribution. When working with multivariate series, the joint
distribution of the returns is to be preferred over the simple
univariate distribution of the resulting return vector of a
portfolio. Once the multivariate moments are available, it is
possible to compute the comoments, comoment matrices, and beta or
systematic comoments.
skewness
kurtosis
skewness.MM
kurtosis.MM
We've ported and reimplemented skewness and kurtosis from
Rmetrics to allow for additional data classes as well as
multivariate series.
StdDev.MM
multivariate_mean
Return.centered
M3.MM
M4.MM
We've additionally implemented the multivariate moment
calculations for the first two portfolio moments (mean and
standard deviation) as well as the third and forth mathematical
moments.
CoVariance
CoKurtosis
CoSkewness
Calculates the covariance, coskewness. or cokurtosis of one asset
with relation to another (scalar measure) utilizing the
standardized central mathematical moments of the distribution.
CoKurtosisMatrix
CoSkewnessMatrix
Calculates the N x N2 co-moment matrix of assets to one another,
can be utilized in a portfolio context. This is a complete
reimplementation of the prior functions in PerformanceAnalytics
to calculate moments, and has been validated by our research work
as superior to the prior implementation.
centeredmoment
centeredcomoment
Used internally by PerformanceAnalytics to calculate centered
moments for a multivariate distribution as well as the
standardized moments of a portfolio distribution. They are
exposed here for users who wish to use them directly
BetaCoVariance
BetaCoSkewness
BetaCoKurtosis
Calculates the systematic or beta comoment of two assets or an
asset versus a portfolio. used to assess diversification
potential in a portfolio, or in multivariate multimoment
portfolio optimization.
Significant Changes to existing functions:
chart.BarVaR
* Incorporates 'Return.clean' methods for using cleaning methods
when charting forecasted VaR values.
* Handles multiple columns OR multiple VaR calculation methods
* Can show cleaned returns overlaid on original data
* Added horizontal line to show exceedences to most recent risk
estimate
Co-moments and Beta/Systematic Co-moments have been completely
reimplemented, and are discussed above.