economics

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European Funds dataset from Morningstar

Creators: (Leone, Stefano)
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. A key feature of this dataset is the inclusion of detailed Morningstar ratings, which are widely used in the financial industry to assess fund quality based on past performance, risk-adjusted returns, and analyst evaluations. Additionally, it offers categorization of funds, allowing for segmentation by investment type, sector, region, and fund style (e.g., growth vs. value investing). The dataset has a total size of approximately 103.88 MB.

Overall, the dataset is structured into the following variables:

  • ticker: Fund ticker code.
  • isin: Fund ISIN code.
  • fund_name: Extended name of the fund.
  • inception_date: Date of the fund’s inception.
  • category: Fund category.
  • rating: Morningstar rating.
  • analyst_rating: Morningstar analyst rating.
  • risk_rating: Morningstar risk rating.
  • performance_rating: Morningstar performance rating.

US Funds dataset from Yahoo Finance

Creators: (Leone, Stefano)
Publication Date: 2018
Creators: (Leone, Stefano)

The US Funds dataset from Yahoo Finance collects data on 24,821 mutual funds and 1,680 exchange-traded funds (ETFs). This contains detailed information on various aspects of each fund, including general characteristics, portfolio indicators, returns, and financial ratios. A notable feature of this dataset is its extensive coverage, offering insights into both mutual funds and ETFs, which can be instrumental for comparative analyses and investment research. The dataset was published in 2018 and contains data up to November 2020, providing a temporal coverage that spans several years leading up to that point. In total, it covers 1.7 GB.

The dataset includes various variables for each fund, such as:

  • fund_symbol: Symbol of the ETF.
  • price_date: Date of the price (in YYYY-MM-DD format).
  • open: Open daily price.
  • high: Highest daily price.
  • low: Lowest daily price.
  • close: Close daily price.
  • adj_close: Adjusted close daily price, which considers elements that have impacted the price such as share splits, dividends, etc.
  • volume: Daily traded volume.
  • nav_per_share: Daily Net Asset Value (NAV) per share.
  • region: Name of the region in which the fund has the domicile.
  • initial_investment: Minimum amount for initial investment.
  • subsequent_investment: Minimum amount for subsequent investments.
  • exchange_code: Code of the exchange where the fund is traded.
  • exchange_name: Name of the exchange where the fund is traded

 

Relative Wealth Index Data

Creators: Chi, Guanghua; Fang, Han; Chatterjee, Sourav; Blumenstock, Joshua E.
Publication Date: 2021
Creators: Chi, Guanghua; Fang, Han; Chatterjee, Sourav; Blumenstock, Joshua E.
The Relative Wealth Index predicts the relative standard of living within countries using de-identified connectivity data, satellite imagery and other nontraditional data sources.
It has been built by researchers at the University of Carlifornia – Berkeley and Facebook. The estimates are built by applying machine learning algorithms to vast and heterogeneous data from satellites, mobile phone networks, topographic maps, as well as aggregated and de-identified connectivity data from Facebook. They train and calibrate the estimates using nationally-representative household survey 20 data from 56 LMICs, then validate their accuracy using four independent sources of household survey data from 18 countries. They also provide confidence intervals for each micro-estimate to facilitate responsible downstream use.
The data is provided for 93 low and middle-income countries at 2.4km resolution. It covers the time between April 01, 2021 and December 22, 2023. An interactive map of the Relative Wealth Index is available here: http://beta.povertymaps.net/
The combined size of the dataset is approximately 0,08 GB, available in CSV format.
Please cite / attribute any use of this dataset using the following:
Microestimates of wealth for all low- and middle-income countries Guanghua Chi, Han Fang, Sourav Chatterjee, Joshua E. Blumenstock Proceedings of the National Academy of Sciences Jan 2022, 119 (3) e2113658119; DOI: 10.1073/pnas.2113658119 

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