Abstract
This paper presents the technical aspects of designing and building a historical database of the Italian Stock Market. The database contains daily market data from 1973 to 2011 and is constructed by merging two main digital sources and several other hand-collected data sources. We analyzed and developed semi-automatic tools to deal with problems related to time-series matchings, quality of data and numerical errors. We also developed a concatenation structure to allow the handling of company name changes, mergers, and spin-offs without artificially altering numerical series. At the same time, we maintained the transparency of the historical information on each individual company listed. Thanks to the overlapping of digital and hand-collected data, the completed database has a very high level of detail and accuracy. The dataset is particularly suited for any empirical research in financial economics and for more practically oriented numerical applications and forecasting simulations.