Gerber

Package for using the Gerber Statistic for various statistical techniques.

Applications of Gerber Statistic

1. Gerber Portfolio Optimization
2. Rolling Gerber Correlations
3. AutoGerberlation
4. Gerber Betas
5. GerberPCA

Repo layout

    Gerber
      └───src
          │   Gerber.py
          │   setup.py
      └───testNotebooks
          │   setup.py
          │   TestEfficientFrontier.ipynb
          │   TestRollingGerber.ipynb
          |   TestPCA.ipynb
          |   TestGeberOLS.ipynb
          |   TestRollingOLSGerber.ipynb
          |   TestAutoGerberlation.ipynb
      └───testScripts
          │   setup.py
          │   testMatrices.py
          │   testGerberNp.py
          │   testAutoGerberalation.py
          |   testAutoCorrGerber.py
          |   testCumsumComovement.py
      └───Examples
          │   StockBondCorrelation.ipynb
          |   CumsumComovementExample.ipynb

src files:

• Gerber.py: OOP file for all of the Gerber Functions

testNotebooks Files:

• setup.py: Downloads sample retursn data from yahoo finance
• TestEfficientFrontier.ipynb: Examines the differences between Efficient Frontiers using Gerber Covariance and Standard Covariance
• TestRollingGerber.ipynb: Look at the rolling Gerber correlation and standard rolling Gerber Correlation
• TestPCA.ipynb: Applying PCA decomposition to Gerber matrix rather than Pearson Correlation & Covariance
• TestGeberOLS.ipynb: Using Gaussian Log-likelihood Estimators with Gerber Correlation & Covariance
• TestRollingOLSGerber.ipynb: Rolling OLS with Gerber Correlation & Covariance
• TestAutoGerberlation.ipynb: Calculating Autocorrelation and Autocovaraince with Gerber Statistic

testScripts Files:

• setup.py: Downloads sample retursn data from yahoo finance
• testMatrices.py: Creates Sample covariance and correlation matrix using Gerber Statistic
• testGerberNp.py: Compares Gerber-based covariance and correlation matrix to standard
• testAutoGerberlation.py: Creates Gerber based autocorrelation and autocovariance matrix and the difference between Gerber and Pearson
• testAutoCorrGerber.py: Finds autcorrelation with Gerber statistics
• testCumsumComovement: Generating cumulative co-movement sum

Example Files:

• StockBondCorrelation.ipynb: Analyzing rolling stock bond correlation using some examples from other research. Specifically looking at historical relationship using Shiller Data.
• CumsumComovement.ipynb: Using the Cumulative Sum Comovement to generate time series that follow the comovement.