Form 13F was adopted pursuant to statutory directive designed to provide the Commission with data from larger managers about their investment activities and holdings.

Introduction In the course of researching the common ownership hypothesis, we found a number of issues with the Thomson Reuters (TR) "S34" dataset used by many researchers and frequently accessed via Wharton Research Data Services (WRDS). WRDS has done extensive work to improve the database, working with other researchers that have uncovered problems, specifically fixing a lack of records of BlackRock holdings. However, even with the updated dataset posted in the summer of 2018, we discovered a number of discrepancies when accessing data for constituent firms of the S&P 500 Index. We therefore set out to separately create a dataset of 13(f) holdings from the source documents, which are all public and available electronically from the Securities and Exchange Commission (SEC) website. Coverage is good starting in 1999, when electronic filing became mandatory. However, the SEC's Inspector General issued a critical report in 2010 about the information contained in 13(f) filings. The process: We gathered all 13(f) filings from 1999-2017 here. The corpus is over 318,000 filings and occupies ~25GB of space if unzipped. (We do not include the raw filings here as they can be downloaded from EDGAR). We wrote code to parse the filings to extract holding information using regular expressions in Perl. Our target list of holdings was all public firms with a market capitalization of at least $10M. From the header of the file, we first extract the filing date, reporting date, and reporting entity (Central Index Key, or CIK, and CIKNAME). Beginning with the September 30 2013 filing date, all filings were in XML format, which made parsing fairly straightforward, as all values are contained in tags. Prior to that date, the filings are remarkable for the heterogeneity in formatting. Several examples are linked to below. Our approach was to look for any lines containing a CUSIP code that we were interested in, and then attempting to determine the "number of shares" field and the "value" field. To help validate the values we extracted, we downloaded stock price data from CRSP for the filing date, as that allows for a logic check of (price * shares) = value. We do not claim that this will exhaustively extract all holding information. We can provide examples of filings that are formatted in such a way that we are not able to extract the relevant information. In both XML and non-XML filings, we attempt to remove any derivative holdings by looking for phrases such as OPT, CALL, PUT, WARR, etc. We then perform some final data cleaning: in the case of amended filings, we keep an amended level of holdings if the amended report a) occurred within 90 days of the reporting date and b) the initial filing fails our logic check described above. The resulting dataset has around 48M reported holdings (CIK-CUSIP) for all 76 quarters and between 4,000 and 7,000 CUSIPs and between 1,000 and 4,000 investors per quarter. We do not claim that our dataset is perfect; there are undoubtedly errors. As documented elsewhere, there are often errors in the actual source documents as well. However, our method seemed to produce more reliable data in several cases than the TR dataset, as shown in Online Appendix B of the related paper linked above. Included Files Perl Parsing Code (find_holdings_snp.pl). For reference, only needed if you wish to re-parse original filings. Investor holdings for 1999-2017: lightly cleaned. Each CIK-CUSIP-rdate is unique. Over 47M records. The fields are CIK: the central index key assigned by the SEC for this investor. Mapping to names is available below. CUSIP: the identity of the holdings. Consult the SEC's 13(f) listings to identify your CUSIPs of interest. shares: the number of shares reportedly held. Merging in CRSP data on shares outstanding at the CUSIP-Month level allows one to construct \beta. We make no distinction for the sole/shared/none voting discretion fields. If a researcher is interested, we did collect that starting in mid-2013, when filings are in XML format. rdate: reporting date (end of quarter). 8 digit, YYYYMMDD. fdate: filing date. 8 digit, YYYYMMDD. ftype: the form name. Notes: we did not consolidate separate BlackRock entities (or any other possibly related entities). If one wants to do so, use the CIK-CIKname mapping file below. We drop any CUSIP-rdate observation where any investor in that CUSIP reports owning greater than 50% of shares outstanding (even though legitimate cases exist - see, for example, Diamond Offshore and Loews Corporation). We also drop any CUSIP-rdate observation where greater than 120% of shares outstanding are reported to be held by 13(f) investors. Cases where the shares held are listed as zero likely mean the investor filing lists a holding for the firm but that our code could not find the number of shares due to the formatting of the file. We leave these in the data so that any researchers that find a zero know to go back to that source filing to manually gather the...

Form 13F was adopted pursuant to statutory directive designed to provide the Commission with data from larger managers about their investment activities and holdings.

By using this dataset, you agree to cite the Related Publication shown below. This dataset captures the quarterly investment holdings of institutional investment managers and maps the ownership structure of public firms. These Schedule 13F reports are submitted to the Securities and Exchange Commission quarterly by all institutional investment managers with at least $100 million in assets under management. Most academic research examining the common ownership of corporations and the portfolio holdings of large investment managers is based on proprietary commercial databases. This hinders the replication of prior work due to unequal access to these subscriptions and because the data manipulation steps in commercial databases are often opaque. This dataset is created from the original regulatory filings without alteration. Daily updates: https://dx.doi.org/10.34740/kaggle/ds/2973565

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This table reports the summary statistics of the key variables in the quasi-natural experiment based on mergers between financial institutional blockholders during 1995–2012. The sample comes from multiple sources. Firm-level financial data come from COMPUSTAT database. Corporate social responsibility data come from MSCI ESG KLD database. Institutional investor holdings data come from Thomson Reuters Institutional (13F) Holdings database. Analyst coverage data come from Institutional Brokers Estimate System (I\B\E\S). We require observations to satisfy the following criteria: (1) Book equity is positive; (2) Each firm should at least have 2-year consecutive observations; (3) Variables are available in all observations; (4) Firms are not in financial (SIC code 6000–6999) or utility (SIC codes 4900–4999) industries. Our sample includes 3,778 firm-years that meet these criteria during 1995–2012 when Thomson Reuters Institutional (13F) Holdings and KLD are available and firms can be matched to blockholder mergers. All continuous variables are winsorized at 1st and 99th percentiles to alleviate the potential disturbance from outliers.

A list of the top 50 Scion Asset Management holdings showing which stocks are owned by Michael Burry's hedge fund.

We empirically assess the implications of the common ownership hypothesis from a historical perspective using the set of S&P 500 firms from 1980–2017. We show that the dramatic rise in common ownership in the time series is driven primarily by the rise of indexing and diversification and, in the cross–section, by investor concentration, which the theory presumes to drive a wedge between cash flow rights and control. We also show that the theory predicts incentives for expropriation of undiversified shareholders via tunneling, even in the Berle and Means (1932) world of the widely held firm.We include additional data on scraped SEC 13f forms for 2000-2017. The rest of the data is provided or downloaded from WRDS and requires a WRDS account.

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For nanoSIMS measurements of R. mucilaginosa cells, we analyzed three sample sets: (i) the original inoculum (Control), (ii) after incubation with 13C-labelled polyethylene without and (iii) with UV-treatment. We measured a total of 1144 regions of interest (ROIs, i.e., corresponding to 1144 individual cells). For IRMS and GCMS measurements we measured 3 replicates for the development of ?13C-CO2 values and CO2 concentration in incubations with R. mucilaginosa (RM) and with 13C-polyethylene (PE), with prior UV-treatment (+UV) and without (-UV) as the sole carbon source as well as in incubations with UV-treated 13C-polyethylene (PE) without R. mucilaginosa.

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Wenige Themen sind in der Wirtschaftsgeschichte derart kontrovers diskutiert worden wie der deutsche Kapitalexport vor dem Ersten Weltkrieg. Die Beurteilungen reichen von der Ausbeutungsthese des Lenin’schen Finanzimperialismus bis hin zur Interpretation als einer frühen Form der Entwicklungshilfe. Die vorliegende Arbeit will diese Diskussion durch die Aufarbeitung einer breiten Faktenbasis auf eine solide Grundlage stellen. Dabei wird deutlich, dass es sich beim Kapitalexport um einen komplexen Vorgang handelt, bei dem neben der Rolle der Banken und der heimischen und auswärtigen Politik die Bedeutung des kapitalanlegenden Publikums und der Kreditnehmer bislang zu wenig betrachtet wurde. Außerdem wird gezeigt, wie die Bildung internationaler Syndikate mit einer starken Konkurrenz der deutschen Banken auf nationaler Ebene einherging, und so die bisher herrschende Auffassung widerlegt, nach der sich am internationalen Kapitalmarkt nationale Bankengruppen in einer Weise gegenübergestanden hätten, die die Konfrontation des Ersten Weltkrieges bereits vorweg genommen hätte. Zum Schluss wird auf breiter Datenbasis die Rentabilität der Auslandsanlagen analysiert. „Kapitalanlage meint im Zusammenhang dieser Arbeit immer eine Investition in verbriefte Forderungsrechte, die den Schuldner verpflichten, dem Gläubiger für die Übereignung von Geld eine Gegenleistung zu gewähren. Die Wirtschaft kennt auch andere Formen der Kapitalanlage (die Investition in Sachkapital und die Direktinvestition im Ausland). In dieser Arbeit soll jedoch nur die erstgenannte Form der Kapitalanlage, die Portfolioinvestition, behandelt werden. Durch die Betrachtung der Auslandsinvestition wird das Blickfeld auf die Interdependenz von Volkswirtschaften gelenkt. Die Betonung des Wertpapieraspekts hat zur Folge, dass sich ständig wiederholende Vorgänge betrachtet und die Veränderung der Umweltbedingungen auf die einzelnen Handlungen beobachtet werden können“ (Schaefer, K. C., a. a. O., S. 13f). Zunächst wir in den ersten drei Kapiteln der Rahmen für den Kapitalexport dargestellt: die Institutionen, das Recht, die volkswirtschaftliche Ausgangssituation. Den Hauptteil der Arbeit bildet eine regional gegliederte Darstellung des deutschen Kapitalexports. Dabei zeigt sich, dass die regionalen Teilmärkte vielfach ganz indi-viduelle Charakteristika aufwiesen, vor allem hinsichtlich des Einflusses der Politik auf die Kapitalanlage und hinsichtlich der Konsortialbildung der Banken. Dem musste der Aufbau der einzelnen Regionalstudien Rechnung tragen, die darum in unterschiedlicher Weise gegliedert sind. Im abschließenden fünften Kapitel der Arbeit steht eine Analyse der Wirkungen des Kapitalexports für die Privatanleger, die Banken und die Kreditnehmer.Die Studie enthält einen umfangreichen Datenanhang mit Tabellen zur deutschen Zahlungsbilanz und zum Nettosozialprodukt, die Emissionsstatistik aus „Der Ökonomist“ (Nominalwerte, Kurswerte) sowie Zeitreihen zu Effektivzinsen, Renditen, Risikomaß und Markthomogenität. Datentabellen in HISTAT:A. Tabellen aus dem AnhangA.01 Deutsche Zahlungsbilanz und Nettosozialprodukt (1880-1913A.02 Emissionsstatistik: Nominalwerte (1883-1914)A.03 Emissionsstatistik: Kurswerte (1883-1914)A.04 Effektivzinsen der Staatsobligationen nach Regionen (1871-1914)A.05 Effektivzinsen der variablen Staatswerte (1871-1914)A.06 Effektivzinsen der fest verzinslichen Eisenbahnwerte (1871-1914)A.07 Effektivzinsen der variabel verzinslichen Eisenbahnwerte (1871-1914)A.08 Effektivzinsen nach Wertpapierarten (1870-1914)A.09 Renditen der festverzinslichen Staatswerte (1870-1914)A.10 Rendite der variabel verzinslichen Staatswerte (1870-1914)A.11 Festverzinsliche Eisenbahnwerte (1870-1914)A.12 Rendite der variabel verzinslichen Eisenbahnwerte (1871-1914)A.13 Renditen nach Wertpapierarten (1871-1914)A.14 Homogenität der Staatsobligationen nach Regionen (1871-1914)A.15 Homogenität der Eisenbahnobligationen (1872-1914)A.16 Homogenität der Eisenbahnaktien (1872-1914)A.17 Homogenität nach Wertpapierarten (1871-1914)A.18 Risiko der Staatsobligationen (1875-1914)A.19 Risiko der Eisenbahnobligationen (1875-1914)A.20 Risiko der Eisenbahnaktien (1875-1914)A.21 Risiko nach Wertpapierarten (1875-1914) T. Tabellen aus dem TextT.01a Aktienkapital deutscher Großbanken (1870-1910)T.01b Deutscher Besitz an ausländischen Wertpapieren (1914-1918)T.02a Effektenkurse in Berlin, Jahresultimowerte nach Salings (1870-1893)T.02b Effektivzinsen der österreichischen und der ungarischen Goldrenten (1875-1914)T.03a An deutschen Börsen zugelassene österreichisch-ungarischen Eisenbahnwerte (1840-1914)T.03b Gesamtkapital der garantierten österreich-ungarischen Eisenbahngesellschaften (1880-1890)T.04a Auslandsbesitz an österreich-ungarischen Wertpapieren: Deutschland (1901-1912)T.04b Auslandsbesitz an österreich-ungarischen Wertpapieren: Frankreich (1901-1912)T.04c Auslandsbesitz an österreich-ungarischen Wertpapieren: England (1901-1912)T.04d Auslandsbesitz an österreich-un...

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