Design and Implementation of a Historical German Firm-level Financial Database
Article No.: 19, Pages 1 - 22
Abstract
Broad, long-term financial, and economic datasets are scarce resources, particularly in the European context. In this article, we present an approach for an extensible data model that is adaptable to future changes in technologies and sources. This model may constitute a basis for digitized and structured long-term historical datasets for different jurisdictions and periods. The data model covers the specific peculiarities of historical financial and economic data and is flexible enough to reach out for data of different types (quantitative as well as qualitative) from different historical sources, hence, achieving extensibility. Furthermore, we outline a relational implementation of this approach based on historical German firm and stock market data from 1920 to 1932.
References
[1]
Daron Acemoglu and James A. Robinson. 2013. Economics versus politics: Pitfalls of policy advice. Journal of Economic Perspectives 27, 2 (2013), 173–92. DOI:
[2]
Heather M. Anderson, Mardi Dungey, Denise R. Osborn, and Farshid Vahid. 2011. Financial integration and the construction of historical financial data for the euro area. Economic Modelling 28, 4 (2011), 1498–1509. DOI:
[3]
Jan Annaert, Frans Buelens, and Marc Deloof. 2015. Long-run stock returns: Evidence from belgium 1838–2010. Cliometrica 9, 1 (2015), 77–95. DOI:
[4]
Jan Annaert, Frans Buelens, and Angelo Riva. 2016. Financial history databases: Old data, old issues, new insights? In Proceedings of the Financial Market History.David Chambers and Elroy Dimson (Eds.), CFA Institute Research Foundation, Charlottesville, VA.
[5]
Jan Barton and Gregory Waymire. 2004. Investor protection under unregulated financial reporting. Journal of Accounting and Economics 38(2004), 65–116. DOI:
[6]
Gennaro Bernile, Vineet Bhagwat, and P. Raghavendra Rau. 2017. What doesn’t kill you will only make you more risk-loving: Early-life disasters and CEO behavior. The Journal of Finance 72, 1(2017), 167–206. DOI:
[7]
Asaf Bernstein, Eric Hughson, and Marc Weidenmier. 2019. Counterparty risk and the establishment of the new york stock exchange clearinghouse. Journal of Political Economy 127, 2(2019), 689–729. DOI:
[8]
Fabio Braggion and Lyndon Moore. 2011. Dividend policies in an unregulated market: The london stock exchange, 1895–1905. The Review of Financial Studies 24, 9(2011), 2935–2973. DOI:
[9]
Paolo Coletti and Maurizio Murgia. 2015. Design and construction of a historical financial database of the italian stock market 1973–2011. Journal of Data and Information Quality 6, 4(2015), 1–23. DOI:
[10]
Marco Costantino and Paolo Coletti. 2008. Information Extraction in Finance. WIT Press, Southampton, UK.
[11]
Jon Danielsson, Marcela Valenzuela, and Ilknur Zer. 2018. Learning from history: Volatility and financial crises. The Review of Financial Studies 31, 7(2018), 2774–2805. DOI:
[12]
Harry DeAngelo and Richard Roll. 2015. How stable are corporate capital structures?The Journal of Finance 70, 1(2015), 373–418. DOI:
[13]
Elroy Dimson, Paul Marsh, and Mike Staunton. 2002. Long-run global capital market returns and risk premia. (2002). Retrieved 28 Dec., 2021 from http://papers.ssrn.com/abstract=217849.
[14]
Elroy Dimson, Paul Marsh, and Mike Staunton. 2009. Triumph of the Optimists. Princeton University Press, Princeton, NJ.
[15]
Jens Dittrich and Alekh Jindal. 2011. Towards a one size fits all database architecture. In Proceedings of the CIDR 2011, 5th Biennial Conference on Innovative Data Systems Research. 195–198. Retrieved from https://bigdata.uni-saarland.de/publications/DJ11.pdf.
[16]
Sebastian Doerr, Stefan Gissler, Jose-Luis Peydro, and Hans-Joachim Voth. 2021. Financial Crises and Political Radicalization: How Failing Banks Paved Hitler’s Path to Power. (2021). Retrieved 28 Dec., 2021 from https://www.bis.org/publ/work978.pdf.
[17]
Jérémie Ducros, Elisa Grandi, Raphaël Hékimian, Emmanuel Prunaux, Angelo Riva, and Stefano Ungaro. 2018. Collecting and storing historical financial data: The DFIH project. In Proceedings of the Computational Social Science in the Age of Big Data.Cathleen Stuetzer, Martin Welker, and Marc Egger (Eds.), Herbert von Halem Verlag, 355–377.
[18]
Barry Eichengreen. 2016. Financial history in the wake of the global financial crisis. In Proceedings of the Financial Market History.David Chambers and Elroy Dimson (Eds.), CFA Institute Research Foundation, Charlottesville, VA.
[19]
Wenzhong Fan. 2004. Construction Methods for the Shanghai Stock Exchange Indexes: 1870–1940. (2004). Retrieved 28 Dec., 2021 from https://som.yale.edu/sites/default/files/2021-12/SSE-CC.pdf.
[20]
Thomas Ferguson and Hans-Joachim Voth. 2008. Betting on hitler—the value of political connections in nazi germany. The Quarterly Journal of Economics 123, 1 (2008), 101–137.
[21]
Thomas Gehrig and Caroline Fohlin. 2006. Trading costs in early securities markets: The case of the berlin stock exchange 1880–1910. Review of Finance 10, 4(2006), 587–612. DOI:
[22]
William N. Goetzmann. 2015. Bubble Investing: Learning from History. Technical Report. National Bureau of Economic Research. Retrieved from http://www.nber.org/papers/w21693.
[23]
William N. Goetzmann and Simon Huang. 2018. Momentum in imperial russia. Journal of Financial Economics 130, 3(2018), 579–591. DOI:
[24]
William N. Goetzmann, Roger G. Ibbotson, and Liang Peng. 2001. A new historical database for the NYSE 1815 to 1925: Performance and predictability. Journal of Financial Markets 4, 1(2001), 1–32. DOI:
[25]
Kilian Huber, Volker Lindenthal, and Fabian Waldinger. 2021. Discrimination, managers, and firm performance: Evidence from “aryanizations” in nazi germany. Journal of Political Economy 129, 9 (2021), 2455–2503. DOI:
[26]
Stratos Idreos, Lukas M. Maas, and Mike S. Kester. 2017. Evolutionary Data Systems. arXiv e-prints (2017); Retrieved from https://arxiv.org/abs/1706.05714.
[27]
Òscar Jordà, Katharina Knoll, Dmitry Kuvshinov, Moritz Schularick, and Alan M. Taylor. 2019. The rate of return on everything, 1870–2015. The Quarterly Journal of Economics 134, 3(2019), 1225–1298.
[28]
Òscar Jordà, Moritz Schularick, and Alan M. Taylor. 2017. Macrofinancial history and the new business cycle facts. NBER Macroeconomics Annual 31 (2017), 213–263.
[29]
Philippe Jorion and William N. Goetzmann. 1999. Global stock markets in the twentieth century. The Journal of Finance 54, 3(1999), 953–980. DOI:
[30]
Pantelis Karapanagiotis. 2020. Technical Document on Preliminary Common Data Model. Technical Report. DOI:
[31]
Ryan Lampe and Petra Moser. 2016. Patent pools, competition, and innovation-evidence from 20 US industries under the new deal. The Journal of Law, Economics, and Organization 32, 1(2016), 1–36. DOI:
[32]
Stuart E. Madnick, Richard Y. Wang, Yang W. Lee, and Hongwei Zhu. 2009. Overview and framework for data and information quality research. Journal of Data and Information Quality 1, 1(2009), 1–22. DOI:
[33]
Maria Eugénia Mata, José Rodrigues da Costa, and David Justino. 2017. The Lisbon Stock Exchange in the Twentieth Century. Imprensa da Universidade de Coimbra/Coimbra University Press. DOI:
[34]
Rajnish Mehra and Edward C. Prescott. 1985. The equity premium: A puzzle. Journal of Monetary Economics 15, 2(1985), 145–161. DOI:
[35]
Leentje Moortgat, Jan Annaert, and Marc Deloof. 2017. Investor protection, taxation and dividend policy: Long-run evidence, 1838–2012. Journal of Banking & Finance 85(2017), 113–131. DOI:
[36]
Petra Moser, Alessandra Voena, and Fabian Waldinger. 2014. German jewish émigrés and US invention. American Economic Review 104, 10(2014), 3222–55. DOI:
[37]
Rimma V. Nehme, Karen Works, Chuan Lei, Elke A. Rundensteiner, and Elisa Bertino. 2013. Multi-route query processing and optimization. Journal of Computer and System Sciences 79, 3(2013), 312–329. DOI:
[38]
Lukas Manuel Ranft, Jefferson Braswell, and Wolfgang König. 2021. EURHISFIRM D5.5: Report on Process for Extendable Data Models. Technical Report. DOI:
[39]
Carmen M. Reinhart and Kenneth S. Rogoff. 2011. From financial crash to debt crisis. American Economic Review 101, 5(2011), 1676–1706. DOI:
[40]
Björn Richter, Moritz Schularick, and Paul Wachtel. 2020. When to lean against the wind. Journal of Money, Credit and Banking 53, 1(2020), 5–39. DOI:
[41]
Kristian Rydqvist and Rong Guo. 2021. Performance and development of a thin stock market: The stockholm stock exchange 1912–2017. Financial History Review 28, 1(2021), 26–44. DOI:
[42]
Christian Schlag and Anja Wodrich. 2000. Has There Always Been Underpricing and Long-Run Underperformance? - IPOs in Germany Before World War I. (2000). Retrieved 28 Dec., 2021 from https://www.ifk-cfs.de/fileadmin/downloads/publications/wp/00_12.pdf.
[43]
John D. Turner, Qing Ye, and Wenwen Zhan. 2013. Why do firms pay dividends? Evidence from an early and unregulated capital market. Review of Finance 17, 5(2013), 1787–1826. DOI:
[44]
Mika Vaihekoski. 2021. Revisiting Index Methodology for Thinly Traded Stock Market. Case: Helsinki Stock Exchange. (2021). Retrieved 28 Dec., 2021 from https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3716682.
[45]
Jan Verelst. 2004. The influence of the level of abstraction on the evolvability of conceptual models of information systems. In Proceedings of the 2004 International Symposium on Empirical Software Engineering. (Redondo Beach, CA). IEEE, 17–26. DOI:
[46]
Fabian Waldinger. 2016. Bombs, brains, and science: The role of human and physical capital for the creation of scientific knowledge. The Review of Economics and Statistics 98, 5(2016), 811–831. DOI:
[47]
Zhipu Xie, Weifeng Lv, Linfang Qin, Bowen Du, and Runhe Huang. 2018. An evolvable and transparent data as a service framework for multisource data integration and fusion. Peer-To-Peer Networking and Applications 11, 4(2018), 697–710. DOI:
[48]
Kostas Zoumpatianos, Stratos Idreos, and Themis Palpanas. 2016. ADS: The adaptive data series index. The VLDB Journal 25, 6(2016), 843–866. DOI:
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Publication History
Published: 29 June 2022
Online AM: 30 April 2022
Accepted: 01 February 2022
Received: 01 March 2021
Published in JDIQ Volume 14, Issue 3
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