PerformanceAnalytics 1.0.2 Release Notes
(released to CRAN 2010-04-08)

This release is an incremental improvement on v.1.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.


