Package index • PerformanceAnalytics

All functions
`ActiveReturn()`	Active Premium or Active Return
`AdjustedSharpeRatio()`	Adjusted Sharpe ratio of the return distribution
`AppraisalRatio()`	Appraisal ratio of the return distribution
`AverageDrawdown()`	Calculates the average depth of the observed drawdowns.
`AverageLength()`	Calculates the average length (in periods) of the observed drawdowns.
`AverageRecovery()`	Calculates the average length (in periods) of the observed recovery period.
`BernardoLedoitRatio()`	Bernardo and Ledoit ratio of the return distribution
`BetaCoVariance()` `BetaCoSkewness()` `BetaCoKurtosis()`	Functions to calculate systematic or beta co-moments of return series
`BurkeRatio()`	Burke ratio of the return distribution
`CAPM.CML.slope()` `CAPM.CML()` `CAPM.RiskPremium()` `CAPM.SML.slope()`	utility functions for single factor (CAPM) CML, SML, and RiskPremium
`CAPM.dynamic()`	Time-varying conditional single factor model beta
`CAPM.epsilon()`	Regression epsilon of the return distribution
`CAPM.jensenAlpha()`	Jensen's alpha of the return distribution
`CDD()`	Calculate Uryasev's proposed Conditional Drawdown at Risk (CDD or CDaR) measure
`CDaR.alpha()`	Conditional Drawdown alpha
`CDaR.beta()`	Conditional Drawdown beta
`CalmarRatio()` `SterlingRatio()`	calculate a Calmar or Sterling reward/risk ratio Calmar and Sterling Ratios are yet another method of creating a risk-adjusted measure for ranking investments similar to the `SharpeRatio`.
`CoSkewnessMatrix()` `CoKurtosisMatrix()` `CoVariance()` `CoSkewness()` `CoKurtosis()` `M3.MM()` `M4.MM()`	Functions for calculating comoments of financial time series
`DRatio()`	d ratio of the return distribution
`DownsideDeviation()` `DownsidePotential()` `SemiDeviation()` `SemiSD()` `SemiVariance()`	downside risk (deviation, variance) of the return distribution
`DownsideFrequency()`	downside frequency of the return distribution
`DownsideSharpeRatio()`	Downside Sharpe Ratio
`DrawdownDeviation()`	Calculates a standard deviation-type statistic using individual drawdowns.
`DrawdownPeak()`	Drawdawn peak of the return distribution
`ETL()`	calculates Expected Shortfall(ES) (or Conditional Value-at-Risk(CVaR) for univariate and component, using a variety of analytical methods.
`M2.ewma()` `M3.ewma()` `M4.ewma()`	Functions for calculating EWMA comoments of financial time series
`FamaBeta()`	Fama beta of the return distribution
`Frequency()`	Frequency of the return distribution
`HurstIndex()`	calculate the Hurst Index The Hurst index can be used to measure whether returns are mean reverting, totally random, or persistent.
`InformationRatio()`	InformationRatio = ActivePremium/TrackingError
`Kappa()`	Kappa of the return distribution
`KellyRatio()`	calculate Kelly criterion ratio (leverage or bet size) for a strategy
`Level.calculate()`	Calculate appropriate cumulative return series or asset level using xts attribute information
`M2Sortino()`	M squared for Sortino of the return distribution
`M3.MCA()` `M4.MCA()`	Functions for doing Moment Component Analysis (MCA) of financial time series
`MSquared()`	M squared of the return distribution
`MSquaredExcess()`	M squared excess of the return distribution
`MarketTiming()`	Market timing models
`MartinRatio()`	Martin ratio of the return distribution
`MeanAbsoluteDeviation()`	Mean absolute deviation of the return distribution
`MinTrackRecord()`	Minimum Track Record Length
`Modigliani()`	Modigliani-Modigliani measure
`MM.NCE()`	Functions for calculating the nearest comoment estimator for financial time series
`NetSelectivity()`	Net selectivity of the return distribution
`Omega()`	calculate Omega for a return series
`OmegaExcessReturn()`	Omega excess return of the return distribution
`OmegaSharpeRatio()`	Omega-Sharpe ratio of the return distribution
`PainIndex()`	Pain index of the return distribution
`PainRatio()`	Pain ratio of the return distribution
`PerformanceAnalytics-package` `PerformanceAnalytics`	Econometric tools for performance and risk analysis.
`ProbSharpeRatio()`	Probabilistic Sharpe Ratio
`ProspectRatio()`	Prospect ratio of the return distribution
`RPESE.control()`	Controls Function for the Computation of Standard Errors for Risk and Performance estimators
`RachevRatio()`	Rachev Ratio
`Return.Geltner()`	calculate Geltner liquidity-adjusted return series
`Return.annualized()`	calculate an annualized return for comparing instruments with different length history
`Return.annualized.excess()`	calculates an annualized excess return for comparing instruments with different length history
`Return.calculate()` `CalculateReturns()`	calculate simple or compound returns from prices
`Return.clean()`	clean returns in a time series to to provide more robust risk estimates
`Return.convert()`	Convert coredata content from one type of return to another
`Return.cumulative()`	calculate a compounded (geometric) cumulative return
`Return.excess()`	Calculates the returns of an asset in excess of the given risk free rate
`Return.locScaleRob()`	Robust Filter for Time Series Returns
`Return.portfolio()`	Calculate weighted returns for a portfolio of assets
`Return.read()`	Read returns data with different date formats
`Return.relative()`	calculate the relative return of one asset to another
`SFM.alpha()`	Calculate single factor model (CAPM) alpha
`SFM.beta()` `SFM.beta.bull()` `SFM.beta.bear()` `TimingRatio()`	Calculate single factor model (CAPM) beta
`SFM.coefficients()`	Calculate single factor model alpha and beta coefficients
`SFM.fit.models()`	Compare SFM estimated using robust estimators with that estimated by OLS
`Selectivity()`	Selectivity of the return distribution
`SharpeRatio()` `SharpeRatio.modified()`	calculate a traditional or modified Sharpe Ratio of Return over StdDev or VaR or ES
`SharpeRatio.annualized()`	calculate annualized Sharpe Ratio
`M2.shrink()` `M3.shrink()` `M4.shrink()`	Functions for calculating shrinkage-based comoments of financial time series
`SkewnessKurtosisRatio()`	Skewness-Kurtosis ratio of the return distribution
`SmoothingIndex()`	calculate Normalized Getmansky Smoothing Index
`SortinoRatio()`	calculate Sortino Ratio of performance over downside risk
`SpecificRisk()`	Specific risk of the return distribution
`StdDev()`	calculates Standard Deviation for univariate and multivariate series, also calculates component contribution to standard deviation of a portfolio
`StdDev.annualized()`	calculate a multiperiod or annualized Standard Deviation
`M2.struct()` `M3.struct()` `M4.struct()`	Functions for calculating structured comoments of financial time series
`SystematicRisk()`	Systematic risk of the return distribution
`TotalRisk()`	Total risk of the return distribution
`TrackingError()`	Calculate Tracking Error of returns against a benchmark
`TreynorRatio()`	calculate Treynor Ratio or modified Treynor Ratio of excess return over CAPM beta
`UlcerIndex()`	calculate the Ulcer Index
`UpDownRatios()`	calculate metrics on up and down markets for the benchmark asset
`UpsideFrequency()`	upside frequency of the return distribution
`UpsidePotentialRatio()`	calculate Upside Potential Ratio of upside performance over downside risk
`UpsideRisk()`	upside risk, variance and potential of the return distribution
`VaR()`	calculate various Value at Risk (VaR) measures
`VolatilitySkewness()`	Volatility and variability of the return distribution
`apply.fromstart()`	calculate a function over an expanding window always starting from the beginning of the series
`apply.rolling()`	calculate a function over a rolling window
`Return.centered()` `centeredmoment()` `centeredcomoment()`	calculate centered moment/co-moment return matrices
`chart.ACF()` `chart.ACFplus()`	Create ACF chart or ACF with PACF two-panel chart
`chart.Bar()` `charts.Bar()`	wrapper for barchart of returns
`chart.BarVaR()` `charts.BarVaR()`	Periodic returns in a bar chart with risk metric overlay
`chart.Boxplot()`	box whiskers plot wrapper
`chart.CaptureRatios()`	Chart of Capture Ratios against a benchmark
`chart.Correlation()`	correlation matrix chart
`chart.CumReturns()`	Cumulates and graphs a set of periodic returns
`chart.Drawdown()`	Time series chart of drawdowns through time
`chart.ECDF()`	Create an ECDF overlaid with a Normal CDF
`chart.Events()`	Plots a time series with event dates aligned
`chart.Histogram()`	histogram of returns
`chart.QQPlot()`	Plot a QQ chart
`chart.Regression()`	Takes a set of returns and relates them to a market benchmark in a scatterplot
`chart.RelativePerformance()`	relative performance chart between multiple return series
`chart.RiskReturnScatter()`	scatter chart of returns vs risk for comparing multiple instruments
`chart.RollingCorrelation()`	chart rolling correlation fo multiple assets
`chart.RollingMean()`	chart the rolling mean return
`chart.RollingPerformance()`	wrapper to create a chart of rolling performance metrics in a line chart
`chart.RollingQuantileRegression()` `chart.RollingRegression()` `charts.RollingRegression()`	A wrapper to create charts of relative regression performance through time
`chart.SFM()`	Compare SFM estimated using robust estimators with that estimated by OLS
`chart.Scatter()`	wrapper to draw scatter plot with sensible defaults
`chart.SnailTrail()`	chart risk versus return over rolling time periods
`chart.StackedBar()`	create a stacked bar plot
`chart.TimeSeries()` `chart.TimeSeries.base()` `chart.TimeSeries.builtin()` `chart.TimeSeries.dygraph()` `chart.TimeSeries.ggplot2()` `chart.TimeSeries.googlevis()` `chart.TimeSeries.plotly()` `charts.TimeSeries()`	Creates a time series chart with some extensions.
`chart.VaRSensitivity()`	show the sensitivity of Value-at-Risk or Expected Shortfall estimates
`charts.PerformanceSummary()`	Create combined wealth index, period performance, and drawdown chart
`charts.RollingPerformance()`	rolling performance chart
`checkData()`	check input data type and format and coerce to the desired output type
`checkSeedValue()`	Check 'seedValue' to ensure it is compatible with coredata_content attribute of 'R' (an xts object)
`clean.boudt()`	clean extreme observations in a time series to to provide more robust risk estimates
`.coefficients()`	Wrapper for SFM's regression models.
`edhec`	EDHEC-Risk Hedge Fund Style Indices
`Drawdowns()` `findDrawdowns()`	Find the drawdowns and drawdown levels in a timeseries.
`kurtosis()`	Kurtosis
`lpm()`	calculate a lower partial moment for a time series
`managers`	Hypothetical Alternative Asset Manager and Benchmark Data
`maxDrawdown()`	caclulate the maximum drawdown from peak equity
`mean(<geometric>)` `mean(<arithmetic>)` `mean(<stderr>)` `mean(<LCL>)` `mean(<UCL>)`	calculate attributes relative to the mean of the observation series given, including geometric, stderr, LCL and UCL
`portm2()` `derportm2()` `portm3()` `derportm3()` `portm4()` `derportm4()`	Portfolio moments
`portfolio_bacon`	Bacon(2008) Data
`prices`	Selected Price Series Example Data
`skewness()`	Skewness
`sortDrawdowns()`	order list of drawdowns from worst to best
`table.AnnualizedReturns()`	Annualized Returns Summary: Statistics and Stylized Facts
`table.Arbitrary()`	wrapper function for combining arbitrary function list into a table
`table.Autocorrelation()`	table for calculating the first six autocorrelation coefficients and significance
`table.SFM()`	Single Factor Asset-Pricing Model Summary: Statistics and Stylized Facts
`table.CalendarReturns()`	Monthly and Calendar year Return table
`table.CaptureRatios()` `table.UpDownRatios()`	Calculate and display a table of capture ratio and related statistics
`table.Correlation()`	calculate correlalations of multicolumn data
`table.Distributions()`	Distributions Summary: Statistics and Stylized Facts
`table.DownsideRisk()`	Downside Risk Summary: Statistics and Stylized Facts
`table.DownsideRiskRatio()`	Downside Summary: Statistics and ratios
`table.Drawdowns()`	Worst Drawdowns Summary: Statistics and Stylized Facts
`table.DrawdownsRatio()`	Drawdowns Summary: Statistics and ratios
`table.HigherMoments()`	Higher Moments Summary: Statistics and Stylized Facts
`table.InformationRatio()`	Information ratio Summary: Statistics and Stylized Facts
`table.Stats()`	Returns Summary: Statistics and Stylized Facts
`table.ProbOutPerformance()`	Outperformance Report of Asset vs Benchmark
`table.RollingPeriods()` `table.TrailingPeriodsRel()`	Rolling Periods Summary: Statistics and Stylized Facts
`table.SpecificRisk()`	Specific risk Summary: Statistics and Stylized Facts
`table.Variability()`	Variability Summary: Statistics and Stylized Facts
`test_returns`	Sample sector returns for use by unit tests
`test_weights`	Sample sector weights for use by unit tests
`replaceTabs.inner()` `replaceTabs()` `textplot()`	Display text information in a graphics plot.
`to.period.contributions()`	Aggregate contributions through time
`M3.vec2mat()` `M3.mat2vec()` `M4.vec2mat()` `M4.mat2vec()`	Helper function for comoment matrices
`managers`	Selected Portfolio Weights Data
`zerofill()`	zerofill

Reference

All functions