Showing 1-8 of 11 results

IRS E-File Bucket

Publication Date: 2016
Creators: Internal Revenue Service

This bucket contains a mirror of the IRS e-file release as of December 31, 2016.

Political risks and Covid-19 measures

Publication Date: 2019
Creators: Firm-level-risk

This website aggregates firm-level measures of exposure, risk, and sentiment constructed using textual analysis of quarterly earnings conference calls held by more than 11,000 listed firms in 81 countries. The data draws on work in three papers:
In our paper “Firm-Level Political Risk: Measurement and Effects,” as published in the Quarterly Journal of Economics , we construct measures of political sentiment and risk ranging from 2002 to 2021q2.

Reference & details
In “The Global Impact of Brexit Uncertainty,” we extend this methodology to construct measures of the costs, benefits, and risks associated with specific shocks, such as the UK’s decision to leave the EU. Our measures of Brexit exposure, risk, and sentiment are currently updated through the first quarter of 2019.

Reference & details
In a third paper, “Firm-level Exposure to Epidemic Disease: Covid-19, SARS, and H1N1,” we apply the same methodology to construct measures of costs, benefits, and risks individual firms associate with the spread of Covid-19, SARS, H1N1, Ebola, Zika, and MERS, ranging 2002 to 2021q2.

Speeches Dataset

Publication Date: 2019
Creators: European Central Bank

To assist researchers in the field of central bank communication, we offer a precompiled dataset containing the content of all speeches together with limited metadata.

COVID-19 Economic Stimulus Packages Database

Publication Date: 2021
Creators: Elgin, C; Yalaman, A

we conduct a comprehensive review of different economic policy measures adopted by 166 countries as a response to the COVID-19 pandemic and create a large database including fiscal, monetary, and exchange rate measures. Furthermore, using principle component analysis (PCA), we construct a COVID-19 Economic Stimulus Index (CESI) that combines all adopted policy measures. This index standardises economic responses taken by governments and allows us to study cross-country differences in policies. Finally, using simple cross-country OLS regressions we report that the median age of the population, the number of hospital beds per-capita, GDP per-capita, and the number of total cases are all significantly associated with the extent of countries’ economic policy responses.

Video Game Sales

Publication Date: 2016
Creators: Smith, Gregory

This dataset contains a list of video games with sales greater than 100,000 copies. It was generated by a scrape of vgchartz.com.
Fields include
Rank – Ranking of overall sales
Name – The games name
Platform – Platform of the games release (i.e. PC,PS4, etc.)
Year – Year of the game’s release
Genre – Genre of the game
Publisher – Publisher of the game
NA_Sales – Sales in North America (in millions)
EU_Sales – Sales in Europe (in millions)
JP_Sales – Sales in Japan (in millions)
Other_Sales – Sales in the rest of the world (in millions)
Global_Sales – Total worldwide sales.

European Funds dataset from Morningstar

Publication Date: 2019
Creators: (Leone, Stefano)

The file contains 57,603 Mutual Funds and 9,495 ETFs with general aspects (as Total Net Assets, management company and size), portfolio indicators (as cash, stocks, bonds, and sectors), returns (as yeartodate, 2020-11) and financial ratios (as price/earning, Treynor and Sharpe ratios, alpha, and beta).
Additional data in terms of sustainability is also available.

Credit Card Fraud Detection

Publication Date: 2016
Creators: Worldline and the Machine Learning Group of ULB ((Universite Libre de Bruxelles)

The dataset contains transactions made by credit cards in September 2013 by European cardholders. This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions. The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions.

US Funds dataset from Yahoo Finance

Publication Date: 2018
Creators: (Leone, Stefano)

The file contains 24,821 Mutual Funds and 1,680 ETFs with general aspects (as Total Net Assets, management company and size), portfolio indicators (as cash, stocks, bonds, and sectors), returns (as yeartodate, 2020-11) and financial ratios (as price/earning, Treynor and Sharpe ratios, alpha, and beta).

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