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Department of Banking and Finance

Databases

The Department of Banking and Finance, together with the Department of Business Administration and the Faculty of Business, Economics and Informatics provide access to various financial databases for all types of scientific work at the University of Zurich.

Wharton Interface

The Wharton Research Data Services (WRDS) enable data access via a uniform interface.

The detailed WRDS subscription overview (data products and vendors) can be found here - last update March 2023: WRDS -- UZH subscriptions (PDF, 194 KB)

PhD students, senior assistants and professors (who are either matriculated or employed at the University of Zurich) as well as students writing a thesis or papers with a UZH-professor can obtain a personal account to the Wharton Interface. With such an account Wharton Databases can be accessed through the Internet from anywhere in the world, all you need is an internet connection.

Register for a WRDS Account

If you have any questions, please contact the WRDS Representative of the Department of Banking and Finance by email: wrds@bf.uzh.ch

The WRDS terms of use apply. The user agrees to place the following acknowledgement in all publications or other communications prepared using the WRDS services: “Wharton Research Data Services (WRDS) was used in preparing [identify research piece]. This service and the data available thereon constitute valuable intellectual property and trade secrets of WRDS and/or its third-party suppliers.”

Introduction to WRDS
Training videos of WRDS

Bloomberg

Bloomberg contains the following data:

  • Stock prices
  • Accounting data
  • Bond prices
  • Indices
  • Commodities
  • Option prices
  • Interest rates 
  • Exchange rates
  • Macroeconomic data

This database can be accessed in the Business Library at the University of Zurich. Data can be loaded with a plug-in for Microsoft Excel or viewed via the Bloomberg mask.

Please note that Bloomberg has a monthly limit for downloading data to Excel. This limit is based on unique securities and depends on the type of data being downloaded. Once a terminal reaches the limit, no more data can be downloaded for the rest of the month. Please read the following guide on how to use the Bloomberg terminal efficiently, reducing the likelihood of reaching the download limit.

PDF Bloomberg terminals 2018 (PDF, 575 KB)

Access is available for students of the University of Zurich only.

PDF Bloomberg getting started (PDF, 3 MB).

This guide als describes how you can get help from their helpdesk or tech support team. These can be contacted directly from the terminal.

 

CEO Turnover Data

Florian Peters (University of Amsterdam) and Alexander Wagner (University of Zurich) maintain a database of forced CEO turnovers. The database (XLSX, 66 KB) contains the dates of forced CEO turnovers (and therefore excludes all voluntary turnover or firm-years in which no turnover occurred) of all firms recorded in the Execucomp database between 1993 and 2019. The file comes from the data used in Peters and Wagner (Journal of Finance, vol. 69, no. 4, pp. 1529-1563, 2014) and Jenter and Kanaan (Journal of Finance, Vol. 70, no. 5, pp. 2155-2184, 2015) and it has been extended to 2019 by Peters and Wagner since publication. The construction of the dataset has also benefited from turnover data generously provided to us by Greg Nini, Luke Taylor, Cami Kuhnen, Andrea Eisfeldt, and Ofer Eldar. In particular, discrepancies in classification between these datasets and ours have been resolved. The criteria for classifying a CEO turnover as forced are described in detail in Peters and Wagner (Journal of Finance, vol. 69, no. 4, pp. 1529-1563, 2014).

An important feature of the dataset is that, since 2001, it records forced turnovers also for the cases where a company is dropped from Execucomp from year t to year t+1. This means that all firm-year observations in Execucomp which are not coded as forced in our dataset are cases where either no turnover occurred or where the turnover was voluntary. There are very few exceptions to this rule: Since Execucomp somtimes backfills or modifies some observations of earlier years, our dataset may miss a few turnovers or assign a turnover to a different fiscal year than a current vintage of Execucomp.

The data can be easily merged with the full Execucomp CEO database (i.e. applying condition CEOANN=”CEO”) by joining on the gvkey and year variables. All successfully merged observations within the 1993-2019 period are forced turnovers, all other observations are either voluntary turnovers or cases where no turnover occurred.

We are updating the dataset periodically to include more recent years and to account for observations in earlier years that, over time, are added or modified by Execucomp.

Please cite these data as follows (Peters and Wagner for the 2001-2019 period, Jenter and Kanaan for the 1993-2000 period):

DBF Risk Factors Database

To construct this dataset we received support of the Zurich Cantonal Bank (ZKB), the Swiss National Science Foundation (SNSF) as well as the Commission for Technology and Innovation (CTI).

The provided data are freely available to other researchers and are for non-commercial uses. If you use these data, please cite

Peter S. Schmidt, Urs Von Arx, Andreas Schrimpf, Alexander F. Wagner and Andreas Ziegler: 2019, “Common risk factors in international stock markets,” Financial Markets and Portfolio Management 33(3), 213-241.  

A pre-publication version of this paper is available at:

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1738315

Note that the data actually provided might be different to the data described in the paper as some improvements have been made to the methodology. However, the basic approach is the same. In case of doubt the descriptions provided in the description file online are valid.

Disclaimer: While we have taken considerable care in the preparation of the data and related materials, we can assume no responsibility or liability for any injury, loss or damage incurred as a result of any use or reliance upon the information and material downloaded from these pages.

By downloading and using the data, you agree to these conditions of use.

Download

Risk Factor Database (ZIP, 3 MB)

Datastream

The Datastream database was integrated into the Eikon platform by the provider Refinitiv, formerly the Financial & Risk business unit of Thomson Reuters. The focus is especially on time series and historical price data, which are made easily accessible via Datastream. For example, the stock prices of various companies listed in an index can be downloaded. In contrast to the Wharton interface, historical data is geographically accessible over a wider area, e.g. also for Europe. Unlike Bloomberg, Datastream has no download limits.

Data spans bond indices, bonds, commodities, convertibles, credit default swaps, derivatives, economics, energy, equities, equity indices, ESG, estimates, exchange rates, fixed income, funds, fundamentals, interest rates, and investment trusts.

This database can be accessed via the Eikon terminals in the Business Library at the University of Zurich. Data can be loaded with a plug-in for Microsoft Excel.

Access is available for students of the University of Zurich only. For questions about access, please contact databases@bf.uzh.ch.

Unfortunately, it is not possible for us to offer an introduction in the use of Datastream. However, tutorials can be found here: refinitiv.com/en/support-and-training/datastream-training

Take a look at Datastream’s fact sheet (PDF, 1 MB)

Refinitiv Eikon (former Thomson Reuters)

Eikon covers a similar spectrum as Bloomberg in terms of content. Eikon delivers data in real time and offers comprehensive tools for data analysis. Apart from Bloomberg, Eikon probably has one of the largest coverages of financial market data worldwide. However, the two coverages, Eikon and Bloomberg, are quite different. For example, certain bonds are covered in Eikon, while Bloomberg does not cover these bonds (and vice versa). Also, Eikon does not have download limits. Compared to Datastream, Eikon usually offers shorter time series, but the coverage is much larger.

Eikon contains the following data:

  • Stock prices
  • Accounting data
  • Bond prices
  • Indices
  • Commodities
  • Option prices
  • Interest rates
  • Exchange rates
  • Macroeconomic data
  • Credit Ratings

This database can be accessed in the "Bibliothek für Betriebswirtschaft" at the University of Zurich. Data can be loaded with a plug-in for Microsoft Excel or viewed via the Eikon mask.

Access is available for students of the University of Zurich only. For questions about access, please contact databases@bf.uzh.ch.

Unfortunately, it is not possible for us to offer an introduction in the use of Eikon. However, tutorials can be found here: https://training.refinitiv.com/eikon/.

SDC Platinum

This database is standard for information on new issues, M&A, syndicated loans, private equity, project finance, poison pills, and more. It includes, for example:

  • Worldwide mergers, acquisitions and alliances
  • Global issues
  • Worldwide syndicated loans
  • Poison Pills

This database can be accessed through the Terminal in the Business Library at the University of Zurich. Access is available for students of the University of Zurich only.

For support, please read the Quick Start Guide: PDF SDC Platinum (PDF, 1 MB)

Or take a look at the support web page: refinitiv.com/en/support-and-training/sdc-platinum-training

Fitch Connect

Fitch Connect offers a comprehensive collection of bank financial filings and is a replacement source for Bankscope. It also offers, among other things, historical credit ratings.

There is a limited number of accounts that the University of Zurich is entitled to. If you would like to open an account for the duration of your research project, please email your request to databases@bf.uzh.ch.

Please note that, due to the limited number of accounts, we may be forced to block your account after 6 months, in order to give someone else access. Should you have the need for continued access, please write to databases@bf.uzh.ch.

Accounts are limited to PhD students, senior research associates as well as professors affiliated with the Department of Banking and Finance. The data can be loaded with a plug-in for Microsoft Excel.

Quick start guide
Training video

Orbis

The Department of Banking and Finance has access to Bureau Van Dijk's Orbis database through University of Zurich and the Main Library/Central Library.

With Orbis you get:

  • information on companies in all countries
  • public and private company data – including banks and insurance companies
  • extensive corporate ownership structures
  • data on individuals associated with companies
  • marine vessels data

And optional modules include:

  • beneficial ownership information
  • ESG reputational risk ratings and metrics
  • patents and intellectual property
  • PEPs and sanctions
  • public tenders data
  • financial strength metrics and projected financials
  • scores on companies with limited financials
  • associated news and independent research
  • original as-filed documents and document ordering
    services
  • global M&A deals and rumours
  • royalty agreements
  • PIEs (Public Interest Entities)
  • Probability of Default (PD) credit measures

You can find Orbis here: ub.uzh.ch/en/unterstuetzung-erhalten/fachliche-unterstuetzung/wirtschaftswissenschaften/datenbanken

Please contact databases@bf.uzh.ch to obtain access.

Bureau Van Dijk's Webpage gives useful information on what kind of data Orbis covers and how the database can be used. 

Please also read the Orbis brochure (PDF, 419 KB)

Optionmetrics IvyDB Signed Volume

The IvyDB Signed Volume dataset, available as an add-on product for IvyDB US, contains daily data on detailed option trading volume. Trades in the IvyDB US dataset are assigned as either buyer-initiated or seller-initiated based on the trade price and the bid-ask quote at the time of the trade. The total assigned daily volume is aggregated and updated nightly.

With IvyDB Signed Volume, you can get key insights into option market order flows and participant activity. Use signed volume to better understand buy/sell pressure on options markets and improve your research!

  • Tracks whether a trade occurred at the bid, ask, or midpoint
  • Every option, every day since January 2016
  • Clean and reliable data
  • Symbols and security IDs link to IvyDB US
  • Expanded data points on lower option trade counts

The Optionmetrics dataset is available for all UZH faculty and students: IvyDB Signed Volume via FTP and IvyDB US via WRDS.

Register for a WRDS Account:

If you have any questions, please contact the WRDS Representative of the Department of Banking and Finance by email: wrds@bf.uzh.ch

For access via FTP, please contact databases@bf.uzh.ch.

Urgentem

Urgentem, part of ICE, is a provider of transparent carbon emissions data and climate risk analytics to the finance industry. Its Dataset provides a comprehensive time series of the Greenhouse Gas
Protocol defined scope 1,2 and 3 emissions of the latest 5,500 global companies,
with modelled data available for 30,000+ securities.

The Department of Banking & Finance has access to emissions data of 1,600 listed companies. This access is restricted to students and researchers of the Department of Banking & Finance. In order to obtain data, please contact databases@bf.uzh.ch.

Would you like to know more? Take a look at Urgentem’s Data Fact Sheet (PDF, 106 KB)

More databases at UZH

A number of legal aspects must be considered for the use of the databases (these rules can vary according to the supplier).

Instructions to be followed:

  • The Data which is used within a piece of work must be fully acknowledged. 
  • An acknowledgement example for OptionMetrics: The Authors acknowledge the data from OptionMetrics which were obtained through Wharton Research Data Services (WRDS). The WRDS and the data available thereon constitute valuable intellectual property and trade secrets of WRDS and/or its third-party suppliers."
  • All Databases may be used by entitled users only. The various suppliers apply different rules.
  • Raw data material from the databases may only be published after permission by the supplier.
  • No data may be passed on to third parties.
  • No account details (login and password) may be passed on to any third party which also applies to co-authors!
  • Any commercial use of data is strictly prohibited (including private trading). Only academic use of the data is allowed.
  • The suppliers are not liable for the accuracy of their data.
  • For CRSP data furthermore applies:
  • Any approved publication or dissemination (including by electronic means or in any other form) by Subscriber or its employees or consultants of the data contained within or information derived from the Data Files shall contain attribution to CRSP® and shall bear the words "Source: CRSP®, Center for Research in Security Prices. Graduate School of Business, University of Chicago. Used with permission. All rights reserved. crsp.uchicago.edu"
  • This being the case, if you are going to use raw data in your paper you would need to submit this to CRSP first and obtain their approval. If you are just summarizing results from your research using the CRSP database, you can use the wording stated above. Once this is published you can send a copy to Matthew Frego (Matthew.Frego@crsp.ChicagoGSB.edu) and we will keep this in our files.