Analysis of ‘Investment funds statistics broken down by type of fund - Stocks’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/ecb-investment-funds-type-of-fund-stocks on 07 January 2022.

--- Dataset description provided by original source is as follows ---

Investment funds can be distinguished by type of fund (open-end or closed-end). This dataset covers outstanding amounts at the end of the period.

--- Original source retains full ownership of the source dataset ---

Xverum’s Alternative Data delivers a unique lens into the evolving landscape of global businesses - offering non-traditional insights built from social media signals and public web profiles. With over 750M enriched professional profiles and 50M verified companies, this dataset empowers investors, hedge funds, and analysts to identify hidden trends, benchmark headcount dynamics, and make smarter portfolio decisions.

Our data bridges the gap between surface-level company metrics and internal workforce dynamics - ideal for those seeking high-signal, low-noise intelligence.

🔍 Key Features: ✅ Social Media–Derived Insights: Profiles collected and enriched from open social platforms and web sources. ✅ Workforce Trend Monitoring: Track hiring surges, downsizing, department shifts, and growth by role or region. ✅ Educational Intelligence: Understand degree types, universities, and certifications across a company’s talent base. ✅ 50M Company Profiles: Enriched with org size, industry, location, and growth signals. ✅ Dynamic Dataset: Monthly refresh with 350M+ updates per month to ensure timeliness. ✅ Fully GDPR/CCPA-Compliant: Ethically sourced and privacy-secure.

Primary Use Cases: 💠 VC & Hedge Fund Due Diligence Spot early-stage momentum and pre-IPO growth by tracking hiring trends, talent density, and team structure shifts.

💠 Investment Signal Generation Discover investment opportunities based on headcount expansion, leadership changes, and team expertise indicators.

💠 Corporate Intelligence & Benchmarking Compare peer companies by workforce size, education level, technical background, and hiring speed.

💠 Talent Strategy & Workforce Analytics Analyze top roles, degrees, and backgrounds across competitive organizations.

Why Xverum’s Alternative Data? ✅ 750M Verified Professional Profiles ✅ 50M Company Datasets with rich firmographics ✅ Unique social-driven signals for workforce tracking ✅ Investor-grade alternative intelligence ✅ Bulk delivery in .json or .csv formats ✅ S3 Bucket, Email, Cloud Services - fully flexible delivery

Request a free sample today and discover how our social media–powered alternative data can enhance your investment strategies, VC scouting, and workforce due diligence.

PURPOSE (possible uses)

Non-professional investors often try to find an interesting stock among those in an index (such as the Standard and Poor's 500, Nasdaq, etc.). They need only one company, the best, and they don't want to fail (perform poorly). So, the metric to optimize is accuracy, described as:

Accuracy = True Positives / (True Positives + False Positives)

And the predictive model can be a binary classifier.

The data covers the price and volume of shares of 31 NASDAQ companies in the year 2022.

Context

Every data set I found to predict a stock price (investing) aims to find the price for the next day, and only for that stock. But in practical terms, people like to find the best stocks to buy from an index and wait a few days hoping to get an increase in the price of this investment.

Content

Rows are grouped by companies and their age (newest to oldest) on a common date. The first column is the company. The following are the age, market, date (separated by year, month, day, hour, minute), share volume, various traditional prices of that share (close, open, high...), some price and volume statistics and target. The target is mainly defined as 1 when the closing price increases by at least 5% in 5 days (open market days). The target is 0 in any other case.

Complex features and target were made by executing: https://www.kaggle.com/code/luisandresgarcia/202307

Thanks

Many thanks to everyone who participates in scientific papers and Kaggle notebooks related to financial investment.

Analysis of ‘Investment funds statistics broken down by type of fund - Growth rates’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/ecb-investment-funds-type-of-fund-growth-rates on 12 November 2021.

--- Dataset description provided by original source is as follows ---

Investment funds can be distinguished by type of fund (open-end or closed-end). This dataset covers annual percentage changes.

--- Original source retains full ownership of the source dataset ---

As part of our commitment to continuous improvement and being open and transparent, we publish the Fund’s holdings. We update the data every quarter. For operational reasons, we publish this at least 3 months after the end of the quarter. Before you access the data, please read the introduction below and specifically the conditions to the use of the data. We delegate day-to-day management of the Fund’s assets to a number of Fund Managers. They have full discretion to manage their portfolios subject to their investment management agreements with us and in compliance with the Fund’s policies. We do not seek to direct the managers on individual investment decisions. The Funding Strategy takes account of, and informs the development of, our investment strategy and our statement of investment principles (SIP). In all matters, our fiduciary obligations to Fund members are paramount, and neither the Fund’s committees nor the Fund’s officers would take any action which would be in conflict with these obligations. Attribution statement: © Environment Agency copyright and/or database right 2022. All rights reserved.

Explore the Investment Funds Open/Close dataset, providing information on annually closed-ended assets in million SR, total quarterly open-ended funds, and more in Saudi Arabia.

Annually, Close-ended, Assets in Million SR, Total, Quarterly, Number, Open-ended, Bank, Money, Assets, Fund, SAMA Quarterly

Saudi ArabiaFollow data.kapsarc.org for timely data to advance energy economics research..Important notes:Note: As of 2006, the source of data is the Capital Market Authority (CMA).

Information of minors registered in the institution and the amounts of profits for them distributed according to the branches and offices of the institution

This table contains 37 series, with data for years 1970 - 1987 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Investments (37 items: Total portfolio at market value;Investments in Canada;Term deposits;Chartered banks; ...).

Details about the registrants in the community small business investment funds program. The data contains: * registrant name * address * contact information * registration date * registration number * status About the community small business investment fund program

When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

Our experienced analyst team use quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as XML, XLSX or API via SFTP or Snowflake.

Sample dataset for Desktop Service has been provided with some proprietary fields concealed. Upon request, we can provide a detailed Quant sample.

Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, United Kingdom, Europe

ABSTRACT This article assesses the impact of alternative assets on the performance of Brazilian private pension funds. Few studies touch on this topic in Brazil and most only investigate the addition of alternative assets and their impact on the performance. The market of open private pension funds in Brazil has been growing rapidly in recent years and gaining much relevance, especially after the announcement of the reformulation of the Brazilian pension system. In 2018, the Free Benefit Generating Plan (PGBL) and the Free Benefit Generating Life (VGBL) represented more than 94% of total assets in their sector. The Brazilian specially constituted investment funds (FIEs) of PGBL and VGBL private pension plans are characterized by their dependence on fixed income assets. Brazil currently faces an unprecedent low interest rate scenario - which, following a worldwide panorama, seems to be set for a long time - and pension fund managers must search for alternative investments that aggregate both risk premia and diversification. The results of this study may support managers in this little-discussed matter. We compare the performance of FIEs without additional alternative assets versus the portfolio with alternative assets, adding a hedge fund index, an equity mutual funds index, a commodity index, an electric power index, a public utilities index, a gold index, and a real estate index. Several performance measures were used, considering Brazilian regulations and a rebalancing strategy. Our results showed that almost all alternative assets used in this study improved the performance of the Brazilian FIEs of PGBL and VGBL private pension plans, especially the public utilities index and the hedge fund index. Some even improved the portfolio tail risk.

Concept: 90 days past due loans by source of funds and type of credit - individual microentrepreneur (MEI) - earmarked credit - Rural financing - investment. Financing granted to rural producers for agricultural and livestock investments. Source: Central Bank of Brazil - Department of Financial Education 26800-90-days-past-due-loans-by-source-of-funds-and-type-of-credit---individual-microentrepreneur-m 26800-90-days-past-due-loans-by-source-of-funds-and-type-of-credit---individual-microentrepreneur-m

Switzerland Investment Fund: Number of Active Fund: Open: Securities data was reported at 136.000 Unit in Mar 2018. This records a decrease from the previous number of 137.000 Unit for Dec 2017. Switzerland Investment Fund: Number of Active Fund: Open: Securities data is updated quarterly, averaging 152.000 Unit from Sep 2005 (Median) to Mar 2018, with 51 observations. The data reached an all-time high of 212.000 Unit in Sep 2005 and a record low of 129.000 Unit in Jun 2017. Switzerland Investment Fund: Number of Active Fund: Open: Securities data remains active status in CEIC and is reported by Swiss National Bank. The data is categorized under Global Database’s Switzerland – Table CH.O006: Investment Funds: by Type.

This table contains 32 series, with data for years 1970 - 1988 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Investments (32 items: Total portfolio at market value;Investments in Canada;Term deposits;Chartered banks; ...).

Concept: 90 days past due loans by source of funds and type of credit - small-sized enterprise - nonearmarked credit - Rural financing - investment. Financing granted to rural producers for agricultural and livestock investments. Source: Credit Information System 26416-90-days-past-due-loans-by-source-of-funds-and-type-of-credit---small-sized-enterprise---nonea 26416-90-days-past-due-loans-by-source-of-funds-and-type-of-credit---small-sized-enterprise---nonea

This table contains 8 series, with data for years 1970 - 1990 (not all combinations necessarily have data for all years), and is no longer being released. This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Mortgage and investment reserves and reserve fund (8 items: Balance at end of quarter;Opening balance;Add, provisions charged to current expenses;Add, transfers from retained earnings; ...).

Content

The results data presented below is based on the portfolio of SREP projects and has been compiled on behalf of the following multilateral development banks: ADB, AFDB, IDB, IFC and IBRD. It follows the principles outlined under the Revised SREP Results Framework and includes the indicators that help determine whether and to what extent the SREP interventions achieve the proposed project outcome objectives involving: (a) Annual electricity output; (b) Improved energy access to people, businesses and community services; (c) GHG emissions reduced/avoided (tons of CO2 equivalent); (d) increased public and private investments in targeted subsectors (co-financing) You can learn more and get further analysis at the 2017 SREP Operational and Results Report: https://www.climateinvestmentfunds.org/sites/default/files/meeting-documents/srep_18_3_orr_1.pdf

Context

This is a dataset hosted by the World Bank. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore World Bank's Financial Data using Kaggle and all of the data sources available through the World Bank organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using Socrata's API and Kaggle's API. Socrata has assisted countless organizations with hosting their open data and has been an integral part of the process of bringing more data to the public.

This dataset is distributed under Creative Commons Attribution 3.0 IGO

When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

Our experienced analyst team uses quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as XML, XLSX or API via SFTP or Snowflake.

Sample dataset for Desktop Service has been provided with some proprietary fields concealed. Upon request, we can provide a detailed Quant sample.

Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading Data, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, Africa

This dataset includes processed climate change datasets related to climatology, hydrology, and water operations. The climatological data provided are change factors for precipitation and reference evapotranspiration gridded over the entire State. The hydrological data provided are projected stream inflows for major streams in the Central Valley, and streamflow change factors for areas outside of the Central Valley and smaller ungaged watersheds within the Central Valley. The water operations data provided are Central Valley reservoir outflows, diversions, and State Water Project (SWP) and Central Valley Project (CVP) water deliveries and select streamflow data. Most of the Central Valley inflows and all of the water operations data were simulated using the CalSim II model and produced for all projections.

These data were originally developed for the California Water Commission’s Water Storage Investment Program (WSIP). The WSIP data used as the basis for these climate change resources along with the technical reference document are located here: https://data.cnra.ca.gov/dataset/climate-change-projections-wsip-2030-2070. Additional processing steps were performed to improve user experience, ease of use for GSP development, and for Sustainable Groundwater Management Act (SGMA) implementation. Furthermore, the data, tools, and guidance may be useful for purposes other than sustainable groundwater management under SGMA.

Data are provided for projected climate conditions centered around 2030 and 2070. The climate projections are provided for these two future climate periods, and include one scenario for 2030 and three scenarios for 2070: a 2030 central tendency, a 2070 central tendency, and two 2070 extreme scenarios (i.e., one drier with extreme warming and one wetter with moderate warming). The climate scenario development process represents a climate period analysis where historical interannual variability from January 1915 through December 2011 is preserved while the magnitude of events may be increased or decreased based on projected changes in precipitation and air temperature from general circulation models.

2070 Extreme Scenarios Update, September 2020

DWR has collaborated with Lawrence Berkeley National Laboratory to improve the quality of the 2070 extreme scenarios. The 2070 extreme scenario update utilizes an improved climate period analysis method known as "quantile delta mapping" to better capture the GCM-projected change in temperature and precipitation. A technical note on the background and results of this process is provided here: https://data.cnra.ca.gov/dataset/extreme-climate-change-scenarios-for-water-supply-planning/resource/f2e1c61a-4946-4863-825f-e6d516b433ed.

Note: the original version of the 2070 extreme scenarios can be accessed in the archive posted here: https://data.cnra.ca.gov/dataset/sgma-climate-change-resources/resource/51b6ee27-4f78-4226-8429-86c3a85046f4

Total-Cashflows-From-Financing-Activities Time Series for Appfolio Inc. AppFolio, Inc., together with its subsidiaries, provides cloud-based platform for the real estate industry in the United States. The company provides a cloud-based platform that assist with leasing, maintenance, accounting, and other business critical tasks; includes generative AI to answer questions, perform tasks, and automate common workflows; and other technology and services offered by third parties. It offers AppFolio Property Manager Core, a platform that provides the basic functionalities required to operate a property management business, as well as serves as a system of record; AppFolio Property Manager Plus, which offers housing management, student housing management, complex accounting, advanced data analysis, user-defined field customization, and enhanced customer support services; AppFolio Property Manager Max that provides customer relationship management tools, user-defined field customization, full database access through a read/write application programming interface, and customer support resource services; and AppFolio Investment Manager, a software that offers investment management, asset management, and relationship management solutions. The company also provides value-added services, which are designed to enhance, automate, and streamline business-critical processes and workflows for property management businesses, such as electronic payment, tenant screening, and risk mitigation services. AppFolio, Inc. was incorporated in 2006 and is headquartered in Santa Barbara, California.