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Excel Add-In Spreadsheets

This page contains example spreadsheets on how to use the functionality. The spreadsheets only work if you have the add-in installed on your computer! If you have not purchased the add-in yet, please have a look at selected screenshots  taken from the spreadsheets below.

If you do have a regular licence and encounter errors anyway, then you will most likely have an outdated version. Please update your add-in or contact us by email.

The spreasheets flagged "new" are either new or have been updated for the current release.

  • Matrix / Linear Algebra: various functions related to matrices and vectors: SVD, PCA, QR, LU factorizations, Hankel & Toeplitz matrices, lagged data matrices and much more.

  • Singular Spectral Analysis - Spectrum, signals, components, forecasting, multivariate SSA, w-correlations, redrawing.
  • Gerber Statistic: Gerber statistic & modified Gerber statistic, Gerber matrix & tables. An interesting dependency concept in the tradition of Kendall's Tau, fully compatioble to traditional mean-variance optimizers.

  • OLS - Flexible functions implementing OLS linear regression analytics, univariate & multivariate, processing many Y variables at the same time.

  • Linear Combinations in Correlation Matrices, Mean-Squared Difference - forming weighted linear combinations of selected constituents in a correlation matrix, assessing similarity/dissimiliarty of two correlation matrices by calculaing their MSD.
  • PCA Yield Curve Risk Factors: calculating the level, slope and curvature factors for a given yield curve using principal component analysis.

  • Resampled Confidence Bands: non-parametric confidence bands for means and volatilities, correlation, skewness and excess kurtosis.

  • Partial Correlations: a simple approach to measuring downside and upside correlations based on either the arithmetic mean or quantiles.

  • Stochastic Mean Variance Frontier: resampling the efficient frontier portfolios is a reminder that the classical mean-variance frontier is not deterministic.

  • Turbulence Analysis: an approach to measure the degree of disturbance in an asset universe with the possitbility to isolate contributions from volatilities and correlations.

  • Cauchy Distribution: unimodal distribution with undefined first and second moments.

  • Decorrelation: removing correlations while preserving certain other characteristics of a time series matrix.

  • Simulating from Randomized NIG Distributions: illustration of the Central Limit Theorem when distributions averaged are not identical anymore.

  • Critical Line Algorithm: Applying the original Markowitz procedure to generate the exact mean-variance efficient frontier with randmized asset correlations.

  • Combinatorial Portfolio Construction: using cominatorics to build portfolios.

  • Fraud Flags: Fraud indicators like Benford's Law, Bias Ratio and Condiditional Serial Correlation.

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