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Advanced Portfolio Analytics Library .NET

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Current Release Version: 2.10

Version 2.10.0 (April 26, 2023)

Implementation of additional functionality (total of 28 new functions)...

Conditional Correlation Analysis (16 new functions): apaCorrels.Conditional.Mean.Joint, apaCorrels.Conditional.Sigma.Joint, apaCorrels.Conditional.Mean, apaCorrels.Conditional.Sigma, apaCorrels.Conditional.Mean.Joint.Lower, apaCorrels.Conditional.Sigma.Joint.Lower, apaCorrels.Conditional.Mean.Lower, apaCorrels.Conditional.Sigma.Lower, apaCorrels.Conditional.Box, apaCorrels.Conditional.Box.Joint, apaCorrels.Conditional.Box.In, apaCorrels.Conditional.Box.In.Joint, apaCorrels.Conditional.Box.Out, apaCorrels.Conditional.Box.Out.Joint, apaCorrels.Conditional.Quantile, apaCorrels.Conditional.Quantile.Lower, apaCorrels.Conditional.Quantile.Joint, apaCorrels.Conditional.Quantile.Joint.Lower
Gerber Statistic (2 new functions): apaCorrel.Gerber, apaCorrel.Gerber.Modified, apaCorrels.Gerber.Modified, apaCorrels.Gerber.Table, apaCorrels.Gerber, apaCorrels.Gerber.Altered, apaCorrel.Gerber.Altered
Concentration Measurement (2 new functions): apaHerfindahlIndex, apaHerfindahlIndex.Normalized
Mathematical Functions (4 new functions): apaLogisticFunction, apaLogisticFunction.Inverse, apaLogisticFunction.FirstDerivative, apaLogisticFunction.FirstAntiderivative
Risk Visualisation (2 new functions): apaCone.Polynomial, apaCone.Linear
Linear Algebra (2 new functions): apaMatrix.Scalar.Mult.OffMajDiag, apaMatrix.Scalar.Mult.MajDiag
Machine Learning, Artificial Intelligence, Data Sciences Methods (1 new function): apaHPFilter.Boosted

Changes and enhancements...

Renamed apaCorrels.Partial.Quantile and apaCorrels.ArithmeticMean to apaCorrels.Conditional.Quantile and apaCorrels.Conditional.Mean.
Renamed Gerber functions such that they can be integreated with the functions groups apaCorrel.<xyz> and apaCorrels.<xyz>. Affected functions are apaGerberStatistic, apaGerberStatistic.Modified, apaGerberStatistic.Matrix and apaGerberStatistic.
Conditional correlation functions have slightly modified methodology: now based on percentage ranks, not estimated empirical cdf anymore. Minor impact on calculation results.
Start of implementation of help texts in the Excel function editor: short description of function and variables will be made available for more functions with this and every future release.
Start of implementation of a new online-based help system, which is supposed to replace the PDF manual at one point.
Various minor enhancements and fixes.

Version 2.9 (December 21, 2022)

Implementation of additional functionality (total of 70 new functions)...

Correlation Analysis (5 new functions): apaCorrels.Group.Select, apaCorrels.NonGroup.Select, apaCorrels.Add.LinComb, apaCorrels.MSD, apaCorrels.Kendall
Gerber Statistic (4 new functions): apaGerber.Statistic, apaGerber.Statistic.Modified, apaGerber.Table, apaGerber.Matrix
Regression Analysis: (7 new functions): apaCorrels.MultipleCorrels, apaOLS.Residuals, apaOLS.Fitted, apaOLS.Parameter.tValue, apaOLS.Parameter.StandardError, apaOLS.Parameter.pValue, apaOLS.Parameter.CriticalValue
Singular Spectral Analysis (5 new functions): apaSSA.Components.Forecast, apaSSA.Signal.Forecast, apaSSA.Spectrum.Percent.Cum, apaSSA.Spectrum.Percent,apaSSA.wCorrels
Linear Algebra functionality (49 new functions):
- apaMatrix.Center.Double, apaMatrix.Center.Rows, apaMatrix.Center.Cols, apaMatrix.Standard.Rows, apaMatrix.Standard.Cols, apaMatrix.Normal.Rows, apaMatrix.Normal.Cols
- apaMatrix.Diagonal.Minor.Put, apaMatrix.Diagonal.Minor.Get, apaMatrix.Diagonal.Major.Nth.Get, apaMatrix.Diagonal.Minor.Nth.Get, apaMatrix.Flip.Cols, apaMatrix.Flip.Rows, apaMatrix.Concatenate.Cols, apaMatrix.Concatenate.Rows, apaMatrix.Diagonal.Major.Get, apaMatrix.Diagonal.Major.Put, apaMatrix.Shift.Pad, apaMatrix.Shift.Circular, apaMatrix.Repeat.Cols, apaMatrix.Repeat.Rows
- apaMatrix.Averages.Diagonal.Major, apaMatrix.Averages.Diagonal.Minor, apaMatrix.Averages.Cols, apaMatrix.Averages.Rows
- apaMatrix.Sort.Rows.ByVector.Des, apaMatrix.Sort.Rows.ByVector.Asc, apaMatrix.Sort.Rows.ByFirstColumn.Asc, apaMatrix.Sort.Rows.ByFirstColumn.Des
- apaMatrix.Toeplitz, apaMatrix.Hankel, apaMatrix.Lagged, apaMatrix.Lagged.Pad
- apaMatrix.SVD.V, apaMatrix.SVD.U, apaMatrix.SVD.S, apaMatrix.LU.P, apaMatrix.LU.U, apaMatrix.LU.L, apaMatrix.QR.R, apaMatrix.QR.Q
- apaMatrix.Vec, apaMatrix.Vech, apaMatrix.Vecl
- apaMatrix.Kron
- apaMatrix.Trace, apaMatrix.Minors, apaMatrix.Cofactors, apaMatrix.Adjugate

Changes and enhancements...

Singular Spectral Analysis: all relevant functions now able to perform multivariate SSA (previously only univariate)
apaOLS.Parameter.Evaluation: Standard Error, t-Value, Critical Value, P-Value
apaSSA.Spectrum: shows Eigenvalues now (previously Singular values)
Renaming of apaMatrix.PseudoInverse to apaMatrix.Inverse.Pseudo
Retired apaMatrix.Standardize (now available as apaMatrix.Standard.Cols/Rows)
All apaOLS functions can now handle more than one Y variable
Several minor bugfixes and performance enhancements

Version 2.8 (February 14, 2022)

Implementation of additional functionality (31 new functions)

apaCorrels.SortedBy.LoadingsPC.Order, apaCorrels.SortedBy.LoadingsPC
apaCorrels.Blocks, apaCorrels.LeadLag apaCorrels.Drop, apaCorrels.Swap, apaCorrels.Randomise
apaCorrels.Mins, apaCorrels.Maxs, apaCorrels.Dispersions, apaCorrels.Averages, apaCorrels.SortedBy.Dispersions, apaCorrels.SortedBy.Averages
apaShortfallProb.ConfidenceIntervals
apaEigenvalues.Sorted.Percent, apaEigenvalues.Sorted.Percent.Cumulative
apaDistances.Correl, apaDistances.Euclidian, apaDistances.Chebyshev, apaDistances.Manhattan
apaClustering.Hierarchical.CompleteLinkage, apaClustering.Hierarchical.SingleLinkage, apaClustering.Hierarchical.AverageLinkage
apaClustering.Hierarchical.WaterfallAllocation
apaClustering.Hierarchical.Dendrogram, apaClustering.Hierarchical.Dendrogram.UnitHeight
apaClustering.Hierarchical.CophenticMatrix, apaClustering.Hierarchical.ClusterResultAsMatrix, apaClustering.Hierarchical.ClusterCompositions.Matrix, apaClustering.Hierarchical.ClusterCompositions, apaClustering.Hierarchical.Cophenetic... ...CorrelationCoefficient, apaClustering.Hierarchical.SortCorrsOrDists

Changes...

renamed function apaKMeans to apaClustering.kMeans
renamed function to apaShortfall.Historical to apaShortfallProb.Historical
renamed function to apaLongfall.Historical to apaLongfallProb.Historical

Version 2.7 (June 14, 2021)

New and updated functionality...

new functions apaRating.EndingAllocation, apaRating.TransitionMatrix.Compound
new functions apaEigenvalues.Sorted, apaEigenvectors.Sorted
new functions apaDistanceVolatilities, apaDistanceVariances, apaDistanceCorrels, apaDistanceCovars, apaDistanceCorrelation, apaDistanceVariance, apaDistanceCovariance, apaDistanceMatrix
new functions apaCopula.Empirical.Resample, apaCopula.Empirical.Pdf.Multivariate

Enhancements and changes...

apaCopula.Empirical.Pdf and apaQuantileTable (changed output layout, performance enhancements)
Various minor optimizations

Version 2.6 (December 17, 2019)

New and updated functionality...

new function apaCVaR.Modified(Returns, ConfidenceLevel): Modified CVar based on a return time series.
apaMarketData.Yahoo(): retired due to changes on the side of the data provider.

Enhancements and changes...

Compatible with .NET framework versions up to 4.6
Updates relating to the integration of the function library with Excel
Various minor optimizations

Version 2.5 (December 8, 2014)

Implementation of additional functionality (23 new functions)...

apaTradeProfile.ConditionalDrawdown(), apaTradeProfile.Drawdown(), apaTradeProfile.CVaR(), apaTradeProfile.VaR(): trade profiles for various loss-based risk measures.
apaCorrels.Partial.Quantile(), apaCorrels.Partial.ArithmeticMean(): calculating conditional correlation matrices.
apaMean.ConfidenceInternvals(), apaVolatility.ConfidenceIntervals(), apaSkewness.ConfidenceIntervals(), apaKurtosis.ConfidenceIntervals(), apaCorrelation.ConfidenceIntervals(): non-parametric confidence intervals for various risk characteristics based on a resampling/bootstrapping approach.
apaCLA.Resample(): resampling efficient frontier portfolios illustrates the stochasic nature of the efficient frontier.
apaCauchyInv(), apaCauchyPdf(), apaCauchyCdf(), apaCauchyRnd(), apaCauchySim(): our implementation of the location/scale Cauchy distribution, a distribution with infinite first and second moments.
apaUlcerIndex(), apaUlcerPerformanceIndex(): yet another risk measure and risk-asjusted performance measure.
apaAbsorptionRatio(): a PCA-based methodology to measure degree of diversification in an asset universe.
apaTurbulence(), apaCorrelationSurprise(), apaMagnitudeSurprise(): a turbulence indicator for an asset universe, including a decomposition of contributions from innovations in volatilities and correlations.

Enhancements and changes...

apaWealthSimulation(): various enhancements to the wealth simulator, noteably the possibility to model time-varying strategy returns and volatilities.
apaCVaR.Historical(), apaCDaR.Historical(): introduction of a smoothing parameter. Also affects trade profile and other functions.
Bugfix affecting apaTrnd() and apaTsim().
Adjusted percentile calculations in order to handle degenerative inputs. Various functions are affected.

Version 2.4 (December 11, 2013)

Implementation of additional functionality (5 new functions)...

apaNIGarg.randomized(), apaNIGsim.randomized(): generate randomized NIG arguments, simulate fom a randomized NIG distribution
apaBL.PosteriorReturns.Confidence(), apaBL.ImpliedWeights: Black/Litterman posterior returns with explicit view-specific confidence levels. Black/Litterman "implied weights" analogeous to "implied returns".
apaSystem.Deactivate.ComputerName(): deactivate a computer from another computer
apaSystem.ComputerName(): name of current computer
apaSystem.ComputerName.All(): name of all computers of current license
apaMatrix.Inverse(), apaMatrix.PseudoInverse(): inverse and pseudo-inverse of a matrix
apaMatrix.Ones(), apaMatrix.Zeros(): generate matrix of ones and zeros.

Enhancements and changes...

Introduction of computer names in order to simplify activation of new computers replacing existing ones. IMPORTANT: users will be prompted for a computer name when starting this version of the add-in on already activated computers the first time.
All code-related files are now digitally signed. Being a "Trusted Publisher" will contribute to a better installation experience.
Calculation of pseudo-inverse in all internal functions, addressing issues related to singular and near-singular matrices.
Bugfix apaCorrels.Shrink: "average" target did not work properly.
apaBL.<...>: name changes affecting various Black/Litterman functions, various BL functions now accept tau values as arguments.
Bugfix apaCorrel.Average: now accepts a correlation matrix as an input, not a return matrix anymore.
Bugfix apaWeights.Combinatorial.TwoAssets: missing results on last row under certain cirumstances.
Bugfix affecting apaNelsonSiegel.PV and apaNelsonSiegelSvensson.PV
Various low-level adjustments affecting calculation speed and robustness of calculations.

Version 2.3 (September 13, 2013)

Implementation of additional functionality (31 new functions)...

apaNelsonSiegel.ConstantTau.Estimate(): estimation of the Diebold/Li version of the Nelson/Siegel yield curve model
apaNelsonSiegel.ForwardRate(), apaNelsonSiegel.PV(), apaNelsonSiegel.Yield(), apaNelsonSiegel.Estimate(): construction, estimation and valuation functions related to the Nelson/Siegel yield curve model.
apaNelsonSiegelSvensson.ForwardRate(), apaNelsonSiegelSvensson.PV(), apaNelsonSiegelSvensson.Yield(), apaNelsonSiegelSvensson.Estimate(): construction, estimation and valuation functions related to the Nelson/Siegel/Svensson yield curve model.
apaWeights.MVE.Unrestricted.ReturnTarget(), apaWeights.MVE.Restricted.VolaTarget(): portfolio composition of points on the restricted and unrestricted efficient mean-variance frontiers
apaMVE.Unrestricted.Risk.FromReturn(), apaMVE.Unrestricted.Return.FromRisk(): calculation of points on the unrestricted mean-variance efficient frontier
apaWeights.MVE.Restricted.MSR(), apaWeights.MVE.Restricted.MSR(): weights of the restricted and unrestricted maxiimum Sharpe Ratio portfolio
apaMVE.Unrestricted.Coefficients(), apaMVE.Unrestricted.Hyperbola.Center(), apaMVE.Unrestricted.Hyperbola.AsymptoteSlope(): shape parameters of the unrestricted efficient mean-variance frontier
apaNinv(): inverse normal distribution
apaUsim.correlated(): Simulate correlated uniform distributions
apaNIGsim.correlated(): Simulate correlated NIG distributions
apaCFsim.correlated(): Simulate correlated Cornish-Fisher distributions
apaCorrels.SpearmanToPearson(), apaCorrels.PearsonToSpearman(): conversions for multivariate normal distributions
apaMatrix.Cholesky(): Cholesky decomposition
apaSharpeRatio.Contributions.FromCovarsExpRets(): Calculate contributions to portfolio Sharpe Ratio from expected returns and covariances
apaNormalMixture.sim.correlation(): simulate correlated two-component Normal Mixture distributions
apaNormalMixture.match: Determine two-component Normal Mixture parameters such that the resulting distributions exhibits desired first four moments
apaIsValidNIG(): test whether skewness/kurtosis inputs are within feasible range
apaCFmom(): moments of the Cornish-Fisher expansion
apaCFcal(): calibrate parameters of Cornish-Fisher expension to replicate desired moments
apaCVaR.Modified.Moments(): Calculate Modified CVaR from the first four moments
apaWLS(): helper function to perform weighted least squares regressions
apaManual.Update(): Download of latest PDF manual

Enhancements and changes...

apaHistogram(): histogram methodology slightly altered, such that histogram is centered on bin centers
apaStatFactorModel...(): Optional flag to force unit component variances
apaUPM, apaLPM: enhanced calculation methodology
apaReplicateRiskReturn(), apaNIGrnd(): minor bug fixes
apaShrinkageEstimator.Returns.JamesStein(): accepts a manual shrinkage factor
apaFixedIncome... functions: have been renamed to apaNelsonSiegel... or apaNelsonSiegelSvensson
apaMVE.Restricted.MRP.RT(): renamed function for consistency reasons
Further alignment of accuracy/performance characteristics between functions, additional functions affected by apaSpeed.Set()
PDF manual is now part of the installation package; the latest version is downloaded automatically when updating the add-in automatically.

Version 2.2 (March 25, 2013)

Implementation of additional functionality (8 new functions)...

apaCLA(): Critical Line Algorithm (original Markowitz procedure to determine the exact efficient frontier)
apaMRP.RT(): risk tolerance of the restricted maximum return portfolio
apaWeights.MSR(): Weights of the maximum Sharpe Ratio portfolio
apaCorrels.Random(), apaCorrels.Const(): generate correlation matrices with random and constant values
apaMatrix.Standardize(): Standardize a time series matrix
apaSystem.Deactivate(): Transfer your license from an old computer to a new one
apaLicense.UserID(): for users not remembering their user id (because they have too many already)

Enhancements and changes...

Various enhancements related to license management, update and similar operational functionality
Enhanced algorithms for calculating correlation matrices from inputs/data, rank correlations
Further alignment of accuracy/performance characteristics between functions, additional functions affected by apaSpeed.Set()

Version 2.1 (January 30, 2013)

Implementation of additional functionality (19 new functions)...

apaMVE(): direct calculation of mean, volatility and composition of portfolios on th mean-variance frontier
apaWeights.Combinatorial.TwoAssets(), apaWeights.Combinatorial.EqualWeighted(): helper functions for combinatorical portfolio construction
apaTimePoints.FromDates(), apaTimePoints.Rounded(): helper functions to handle conversion of actual dates to time points / time periods for analytical purposes
apaReturn.IRR.All(): calculation of all real and imaginary solutions for the internal rate of return problem
apaMarketData.Yahoo(): retrieve price/return data from Yahoo Finance
apaGainLossSpread(), apaGiniMeanDifference(): alternative risk measures
apaCovar.Semi(), apaCovars.Semi(), apaCoLPMs.Asymmetrical.Symmetrized(), apaCoUPMs.Asymmetrical.Symmetrized(): additional partial moment functions
apaConditionalSerialCorrelation(), apaBenfordLaw(), apaBiasRatio(): fraud indicators
apaActiveShare(): an exposure-based tracking measure
apaNormalMixture.StateProbabilities(), apaNormalMixture.States(): additional normal mixture distribution functionality

Enhancements and changes...

Fixed a bug affecting the existing asymmetrical LPM/UPM
In return calculation formulas, the argument "CFWeights" has been renamed "CFTime"
Additional functions are now covered by the speed mode settings, further fine tuning of the speed modes
Selected low-level performance enhancements

Version 2.0 (October 11, 2012)

Implementation of additional functionality (9 new functions)...

apaCaptureRation.Downside.Continuous(), apaCaptureRation.Downside.Discrete(), apaCaptureRation.Upside.Discrete(), apaCaptureRation.Upside.Continuous() - various capture ratios
apaLicense.ExpiryDate(), apaLicense.Puchased(), apaLicense.InUse() - software license helper functions
apaMatrix.Rank(), apaMatrix.ConditionNumber() - matrix / linear algebra functionality

Enhancements and changes...

Fixed a bug in the installation process which affected automatic updating in certain system environments. IMPORTANT: the fix works on new installations only; existing installations should be 1) uninstalled and 2) all files and folders deleted manually; release 2.0 can then be downloaded and installed.
Redesign of the installation wizard such that the same setup file can be used for Excel 32-bit and 64-bit.
Introduction of a subscription-based licensing system: New users now purchase the add-in on a one year subscription basis. IMPORTANT: existing users can continue using the add-in and are eligible for all future updates at no additional costs.

Version 1.7 (September 30, 2012)

Implementation of additional functionality (9 new functions)...

apaBL.PosteriorReturns(), apaBL.PosteriorReturns.FullConf(), apaBL.ImpliedConfidence(), apaBL.ImpliedReturns(), apaBL.ImpliedWeights() - Blacl/Litterman portfolio construction
apaVolatility.ExPost.Contributions(), apaTrackingError.ExPost.Contributions(), apaBeta.ExPost.Contributions() - ex post contributions to various portfolio risk measures
apaEntropy.Shannon() - an alternative dispersion measure

Enhancements and changes...

Fixed some compatibility issues of version 1.6 with older Excel versions.

Version 1.6 (September 17, 2012)

Implementation of additional functionality (23 new functions)...

apaSSA.Signal(), apaSSA.Signal.Redrawn(), apaSSA.Components(), apaSSA.Spectrum() - several methods to conduct singular spectral analysis
apaPriceSim.GBM(), apaPriceSim.GARCH11(), apaPriceSim.MN(), apaPriceSim.ARMA22(), apaPriceSim.JDLN - simulation of univaruate price processes; geometric Brownian motion, GARCH(1,1), Mmxed normal, ARMA(2,2) and Jump-Diffusion with lognormally distributed jumps
apaPcdf(), apaPpdf(), apaPinv(), apaPrnd(), apaPsim() - implementation of the Poisson distribution
apaUsim() - simulation of the uniform distribution, much faster and better than Excel's internal RAND()
apaLognormalToNormal.Correlation(), apaLognormalToNormal.Covariance(), apaLognormalToNormal.Volatility(), apaLognormalToNormal.Mean() and apaNormalToLognormal.Correlation(), apaNormalToLognormal.Covariance(), apaNormalToLognormal.Volatility(), apaNormalToLognormal.Mean() - conversion of the first two moments and dependence between the normal and corresponding lognormal distributions

Enhancements and changes...

Various minor enhancements affecting all functions or selected function groups

Version 1.5 (May 29, 2012)

Implementation of additional functionality (13 new functions)...

apaWeights.RB, apaWeights.RB.FromCovars: Determine composition of the risk budgeting portfolio (i.e. portfolio with risk contributions that correspond to a given risk budget)
apaSpeed.Set and apaSpeed.Get: Management of calculation speed and calculation accuracy
apaReturn.Contributions: contributions to portrfolio return from portfolio constitutents
apaSharpeRatio.Contributions: contributions to Sharpe Ratio from portfolio constitutents
apaSharpeRatio.FromConst: calculate portfolio Sharpe Ratio directly from constituent exces returns and constituent weights
apaIsValidCF: validates skeweness and kurtosis values for Cornish-Fisher expansion
apaKMeans: k-means clustering algorithm
apaCorrels.Analyze: analysis of the validity of a correlation matrix
apaCorrels.Fixed: Makes a correlation matrix semi-positive definite (Eigenvalue method)
apaWeights.MD.FromCovars: Maximum Diversification portfolio from covariances
apaWeights.EVC.FromCovars: Equal Risk Contributiuon (Risk Parity) portfolio from covariances

Enhancements and changes...

Simplified startup procedure resulting in faster startup times
Increased secruity, the add-in only connects to our domain www.andreasssteiner.net
More robust determination of maximum diversification and risk partiy portfolios
Implemented a workaround for a multi-threading issue in Excel

Version 1.4

Implementation of additional functionality (13 new functions)...

apaWeights.MD: determines the Most Diversified portfolio.
apaCorrels.Implied: correlation matrix based on implied correlation coefficient,
apaCorrel.Implied: Implied correlation coefficient.
apaCorrels.IsValid: checks whether a matrix is a valid correlation matrix
apaWeights.EVC.Robust: determines the robust risk parity portfolio.
apaHPFilter: Hodrick-Prescott filter.
apaMACD: Moving Average Convergence Divergence indicator (technical analysis).
apaTradeProfile: impact analysis of trades on selected return, risk and risk-adjusted performance measures.
apaSharpe.Incremental: incremental asset contributions to portfolio Sharpe Ratio.
apaVolatility.Incremental: incremental asset contributions to portfolio volatility.
apaTSGetRow: extract a row from a matrix.
apaTurnover: calculates tunrover based on changes in precentage allocations
apaVolatility.ExAnte.Contributions.FromCovars: ex ante volatility contributions from asset exposures and a covariance matrix.

Enhancements and changes....

New argument IsCorrelOtherwiseCovar: All functions related to statistical factor modeling (apaStatFactors...) can now either target the correlation or the covariance matrix.
Changed versioning: new format is Major.Minor(.Build)
Set user agent to operate the function library / Excel add-in in high security environments.

Version 1.3.4

Implementation of additional functionality (1 new function)...

apaWeights.MVE.Liabilities.Restricted.RiskTolerance: constituent weights of a portfolio on the mean-variance-liability efficient frontier,

Enhancements and changes....

Web-based activation/licensing system
Various minor performance enhancements affecting many functions indirectly

Version 1.3.3

Implementation of additional functionality (7 new functions)...

apaWeights.EVC: Weights of the fully invested long-only equal-volatility-contribution portfolio.
apaActivePassiveRatio: a portfolio's active-passive ratio
apaGARCH11.Volatility.Conditional.Forward: GARCH(1,1) forward volatility
apaGARCH11.Volatility.Conditional.ExpectedForward: GARCH(1,1) expected forward volatility
apaCorrel.Average: Average correlation coefficient from returns
apaCorrel.Dispersion: Dispersion of orrelation coefficient from returns
apaCorrels.Dispersion: Dispersion of orrelation coefficient from correlations

Enhancements and changes....

Name changes in all GARCh(1,1) functions
Changes in GARCH(1,1) methodology: unconditional volatility is now set to the sample volatility of the return time series (volatility targeting)
Various minor performance enhancements affecting many functions indirectly
Generalized licensing algorithm

Version 1.3.2

Implementation of additional functionality (7 new functions)...

apaWealthSimulation: Stochastic wealth simulation that can be used for financial planning purposes or asset/liability management
apaSkewness.Contributions: Contributions to portfolio skewness
apaKurtosis.Contributions: Contributions to portfolio kurtosis
apaCorrels.Contributions: Contributions to correlation
apaCFinv, apaCFrnd, apaCFsim: a partial implementation of the distribution based on the Cornish-Fisher Expansion for simulation purposes

Enhancements and changes....

Introduction of a setup file, making the activcation process more user friendly
apaTSGet() returns a zero value if no numerical values are found in a range

Version 1.3.1

Implementation of additional functionality (3 new functions)...

apaStrategy.CPPI: CPPI strategy simulation
apaVersion.Current: Latest available version number
apaUrnd: Fast generation of a high-quality uniform random number

Enhancements and changes....

Automatic version check and download whenever a new release is available
Fast and high-quality random number generation with the Multiply-With-Carry method
Various numerically intense functions were given an optional DoSwitchOff parameter (e.g. apaVaR.GP)
Various numerically intense functions are not calcualted anymore in the Excel function wizard
Renamed apaVersion to apaVersion.Installed
Various minor performance enhancements affecting several functions

Version 1.3.0

Implementation of additional functionality (28 new function in total)...

Automatically resize array formulas such that all results are shown
Several functions related to empirical loss analysis (e.g. mean excess loss)
Exceedance correlations
Empirical tail dependence
Generalized Pareto distribution: cdf, pdf, inv, simulation, estimation
EVT VaR estimate based on the Generalized Pareto distribution
Symetrized Joe-Clayton copula: cdf, pdf, simualtion, estimation
Empirical copulas: pdf, cdf
Simulation of the independence copula
Ichimoku chart
Diversification ratio
Random allocations with restrictions and bias

Enhancements and changes....

Requires the .NET 4.0 framework
Returns low-level error messages, not just #VALUE anymore
Various performance enhancement
Faster and more accurate numerical optimization algorithm (Nelder-Mead)
Renamed apaSystemPerformance() to apaSystem.Performance()

Version 1.2.6

Implementation of additional functionality (38 new functions in total)...

Expected maximum drawdown of a Geometric Brownian Motion
Z-Score, Modified Z-Score
Outlier identification with Z-Score and Modified Z-Score
Mean Absolute Deviation from Mean, Mean Absolute Deviation from Median
Normal Mixture Distributions (two components): Cdf, pdf, maximum likelihood estimation, inv cdf, simulation, theoretical first four moments from distribution arguments
Shrinking a valid correlation matrix towards a target (perfect correlation, zero correlation, minimium correlation)
Parametric Value-At-Risk from conditional and unconditional GARCH(1,1) volatilities
Non-linear serial dependency: autocorrelations calculated with Spearman's rank correlation coefficient
Linear Multiple Regression (OLS): parameters, R-squared, adjusted R-squared, t-test and p-values
Upper and Lower returns relative to a threshold
Chow test for structural breaks
Conversion of price series into return time series
Resampling from time series with the option to preserve serial dependencies
Linear or Non-Linear Dual Alpha / Dual Beta Single-Index Model
Logistic distribution: cdf, pdf, inv cdf, moments, arguments from moments
Tail risk attribution of Modified Value-At-Risk

Enhancements...

Various minor changes enhancing stability (Excel crashes due to memory overflows)
Different, more mainstream, formula for Clayton copula
Renamed BiNormal and BiClayton simulation functions
Rolling style analysis: the first n weights are not zero anymore, but N/A