ICM25

Analysis of the long-term evolution of international equity markets (average returns, volatilities, long-term correlations) and economic risks of European stock markets.

Case 1: Analyzing 25 years of stock market returns

Analysis of the longterm evolution of international equity markets, i.e.

• Average returns
• Volatilities
• Long-term correlations between markets
• Correlation regimes

Data set (Case1.csv) includes 16 stock market indices in local currencies covering developed markets in North America, Europe and Asia-Pacific

• Monthly stock market data starting on December 31, 1992, and ending on February 28, 2018
• Indexed to ”100” at the beginning of the period

Case 2: Rational asset pricing and multifactor models

Data set (Case2Factors.csv and Case2MSCI.csv) include monthly total return index data over the 1st decade of the 21st century, from January 2000 to December 2009, denominated in EUR for 10 European stock markets and 4 global risk factors.

Case2.py analyzes the relationships between the returns of the stock markets and the changes of the global factors using the following regressions for each market:

• Market return on the MSCI World index return (single factor model)
• Market return on the 4 global factors (4-factor model)

================================ Switzerland =================================
                            OLS Regression Results                            
==============================================================================
Dep. Variable:            Switzerland   R-squared:                       0.674
Model:                            OLS   Adj. R-squared:                  0.662
Method:                 Least Squares   F-statistic:                     59.37
Date:                Sat, 10 Aug 2024   Prob (F-statistic):           4.25e-27
Time:                        23:18:03   Log-Likelihood:                 280.69
No. Observations:                 120   AIC:                            -551.4
Df Residuals:                     115   BIC:                            -537.4
Df Model:                           4                                         
Covariance Type:            nonrobust                                         
================================================================================
                   coef    std err          t      P>|t|      [0.025      0.975]
--------------------------------------------------------------------------------
const            0.0035      0.002      1.565      0.120      -0.001       0.008
FX USD/EUR       0.2081      0.075      2.759      0.007       0.059       0.358
EUR 10Y Rate     0.0626      0.052      1.206      0.230      -0.040       0.165
CRB Index       -0.1146      0.048     -2.383      0.019      -0.210      -0.019
MSCI World       0.7431      0.053     14.017      0.000       0.638       0.848
==============================================================================
Omnibus:                        4.731   Durbin-Watson:                   1.689
Prob(Omnibus):                  0.094   Jarque-Bera (JB):                4.503
...
==============================================================================

Note

This project has been inspired by the International Capital Markets and Investment Practice lecture held during S2024 by Prof. Dr. Peter Oertmann.

Usage

1. Activate the virtual environment

source env/bin/activate

2. Run the notebook

jupyter notebook

Build

Run the following command to build the notebook. The build files can be found in the build folder:

make

This will execute the Jupyter notebook and convert it to an HTML file, which will be moved to the build directory as index.html.

To clean up the build directory, run:

make clean

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© Carlo Bortolan

Carlo Bortolan  ·  GitHub carlobortolan  ·  contact via [email protected]