Historical German Stock Market Database (GOETHE-Project)

Project Start:07/2015
Status:Completed
Researchers:Stephanie Collet, Christian Hirsch, Wolfgang König, Uwe Risch, Moritz Christian Weber
Category: Data Center
Funded by:LOEWE

Having complete long-term time series is a key success factor for empirical research. To allow researchers to carry out excellent research based on historical data, this project plans to collect historical, currently non-digitalized financial data for Germany. Making this data digitally available is important, because it can be the basis for a wide array of research initiatives that contribute to our understanding of economic and financial history from an academic and a policy perspective. The understanding of history could contribute to significant changes in our perception on finance today.

While digitalized data is available for the last decades, time series are sparse and erroneous for periods before the digital revolution. Especially during historic events (like world wars, financial crises or the introduction of social insurance) time series are often incomplete and scattered. In the GOETHE project, we aim to collect stock prices for approximately 800 German companies listed on the Berlin Stock Exchange from a collection of old, but complete newspapers.

It is a joint endeavor of the House of Finance (Wolfgang König), the University Library (Uwe Risch) and the SAFE Data Center (Christian Hirsch). The source will be the Berliner Börsenkurier for the period 1872 till 1930, which is already available as scanned pdfs. The Berlin stock exchange was the most important market in Germany before WWII and is thus a relevant source of information for the given time period. The data is to be seen as preparatory work for a larger endeavor to collect historical data over a period of 100 years. The SAFE Data Center plans to cooperate with different partner institutions on a large-scale endeavor with the ultimate goal of building a European infrastructure with wide collection of compatible historical databases.

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