The Investors Monthly Manual (IMM), a record of The London Exchange, exists in hard copy for the period from 1871 to 1930, the peak of the colonial era. The London market was the most active market in the world at this time, trading not only domestic securities, but sovereign debt from all over the world as well as the equity and debt of foreign companies. The IMM records prices, dividends and capitalization, as well as other potentially useful information. The articles in the IMM detail issues of current interest to investors over the 70-year period.
The ICF received a grant from a generous donor to transform this data into an electronic database that can be downloaded, manipulated and analyzed by scholars. The scanned Issues of the IMM are now available for download. One can also download a specific series or the entire database of the IMM annual data from our website.
Professors William Goetzmann and K. Geert Rouwenhorst welcome scholars who have already input or used some of this data to share their information through this site as well. We also welcome information about pertinent references pertaining to the database.
This data is supplied solely for academic research purposes. Any commercial use or redistribution without the authorization of the authors and the International Center for Finance at Yale is prohibited. Any use of the data in publication must cite the source appropriately.
The scanned issues of Investors Monthly Manual(IMM) are available for download in PDF and DjVu Format. To download the scanned files click on IMM Issues and choose the issue to download. Please note that the DjVu files are Zipped.
To download the complete database or a specific data series, please click on IMM Data and choose the month and year for downloading. If you have any questions about the IMM data, or need help accessing it, please contact Milad Nozari.
Original IMM Data
Download the comprehensive original IMM data from the following links. Each link is a CSV file including data for different parts of the newspaper such as stocks, railways, banks, or miscellaneous companies.
Download the clean dataset,which includes a subset of the variables, from the following link :