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22 results for “investors”
Figure data and model used in Stranded fossil-fuel assets translate to major losses for investors in advanced economies
<p>The package contains i) the figure code and underlying data to create all figures in the main paper and supplementary information of the journal article and ii) the network and imputation model used to calculate the shock calculation.</p>
Initial Investors of the BB1 token
<p>In 2019 the Berlin based crypto company <a href="https://www.bitbondsto.com/">bitbond</a> issued the security token BB1 (ITIN: 8WR5-AKBG-X) in Germany’s first, completely regulated STO (security token offering). The BB1 token is structured like a bond of the issuer Bitbond Finance GmbH, with a fixed coupon of 4.00% p.a. (frequency: quarterly), and a floating coupon of 60% of the pre-tax profit of the issuer (frequency: annually).</p> <p>All BB1 related transactions can be observed at the <a href="https://stellar.expert/explorer/public/asset/BB1-GD5J6HLF5666X4AZLTFTXLY46J5SW7EXRKBLEYPJP33S33MXZGV6CWFN">Stellar</a> blockchain. We used this transpareny to extract a list of all investors who initially bought the token. We found 1021 initial investments in total, with a total investment volume of around 2,5 mio BB1 token. The list contains all investments, which have been claimed between July 2019 and June 2020.</p> <p>For each investment we extracted the following data:</p> <ul> <li><strong>Date. </strong>This is the date, at which the investor claimed the purchased tokens.</li> <li><strong>Recipient.</strong> Is the ID of the investros account in the Stellar network. All details about this account can be retrieved by: https://stellar.expert/explorer/public/account/[ID]</li> <li><strong>Symbol. </strong>The symbol of the BB1 token.</li> <li><strong>Volume.</strong> The number of BB1 tokens the investor has intially purchased.</li> </ul> <p>If you have any questions regarding this dataset please contact Lutz Maicher (lutz.maicher@uni-jena.de).</p> <p>There is already a piece at Medium where this data is used: <a href="https://medium.com/@Lutz.Maicher/how-versatile-is-the-crowd-of-sto-investors-the-case-of-the-bb1-token-53a3095925c8">"How versatile is the crowd of STO investors — the case of the BB1 token"</a></p>
Dataset: U.S. Global Investors, Inc. (GROW) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: Investors Title Company (ITIC) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Data set for "Measuring synchronization and anticipation between individual investors from their daily performance"
<p>The data stored here is used as a support of the paper "Measuring<br> synchronization and anticipation between individual investors from their<br> daily performance" where a measure based on Mutual Information and<br> Transfer of Entropy is used in order to map investors' behaviour and which<br> ones are following same behavioural patterns.</p> <p>The study linked to this data is published on pre-print Arxiv.org<br> with the following citation:</p> <p><br> Mario Gutiérrez-Roig, Javier Borge-Holthoeffer, Alex Arenas and<br> Josep Perelló. Measuring synchronization and anticipation between<br> individual investors from their daily performance (2018)</p>
Does Investor Risk Perception Drive Asset Prices in Markets? Experimental Evidence.
<p>Extract the .zip-file into one folder (sub-folders for the raw data will be created). Then run the GIMS_DataAnalysis.R for the main results, GIMS_DataAnalysis_Return.R for the RETURN results, GIMS_DataAnalysis_2Assets.R for the EXPERIENCE results, and GIMS_DataAnalysis_2Markets.R for the 2MARKETS results.</p>
Investor Sentiment and Information Efficiency: Evidence from the Bitcoin Market.
<p>This dataset contains information about the volume of Google searches for the term "bitcoin," the values of the Twitter happiness index and the Fear Index, the number of page views for the term "Bitcoin" on Wikipedia, and the online participation of the Bitcointalk.org online forum. Additionally, bitcoin prices and historical returns for the period July 2015 to June 2021 are included.</p>
Women Investors in India - A Systematic Literature Review
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ESG INDEX IS GOOD FOR SOCIALLY RESPONSIBLE INVESTOR IN INDIA
<p>At present time sustainable development is a most concerning phenomenon in <br>almost all parts of the world, mostly in developing countries like India and China. Since <br>almost every country is facing the sustainability challenges distressed with environmental, <br>social, governance and financial crisis, sustainable development has become a universal goal. <br>This paper examines whether ESG(Environment Socially Governance)stocks portfolio<br>(represented by S&P ESG) outperforms the blue chip stocks portfolios and the market <br>portfolio in the Indian stock market, by using absolute rate of return and the risk adjusted <br>measures viz Sharpe ratio and Treynor ratio, Jensen ratio and the CAPM. During the period <br>30th jan2008 to 30th September 2013, we find that ESG stocks portfolios has outperformed <br>the blue chip and market portfolios .ESG stocks portfolios is found to be highly correlated <br>with blue chip and market portfolios in India stock market. By Using absolute rate of return <br>we find that the ESG stocks portfolio generated higher return than the blue chip and the <br>market portfolio. Monthly mean return on ESG stocks portfolios is found to be higher than <br>the other two stocks portfolios though not significant. Using risk adjusted measures – Sharpe <br>ratio and Treynor and Jensen ratio, we find that ESG stocks portfolio outperform the market. <br>Moreover, ESG stocks portfolio is most aggressive portfolio as it is found to have high <br>systematic risk and the total risk than the other two portfolios. Further regression results <br>shows that high ESG stocks portfolio is providing higher abnormal returns as compared to<br>blue chip stocks portfolio and market portfolio. Daily results are also found to be consistent <br>with the monthly returns. The findings have important implications for the investors who are<br>socially responsible as they can start investing in such stocks to reap higher return as <br>compared to that of the market.</p>
Does Investor Sentiment Predict Bitcoin Return and Volatility? - A Quantile Regression Approach
<p>This dataset was used in generating findings for the paper titled "<strong>Does Investor Sentiment Predict Bitcoin Return and Volatility? - A Quantile Regression Approach".</strong></p>
Replication package for "Investor Sentiment, Sovereign Debt Mispricing, and Economic Outcomes"
<p>Replication package for "Investor Sentiment, Sovereign Debt Mispricing, and Economic Outcomes" by Ramzy Al-Amine and Tim Willems</p>
Relative Investor Sentiment (01-01-1996 - 31.12.2022, monthly and daily)
<p>The data set contains the daily and the monthly Relative Investor Sentiment for the time 1996 to 2022 which is described and used in:</p> <p>Gao, Xiang and Koedijk, Kees and Walther, Thomas and Wang, Zhan, Relative Investor Sentiment (May 24, 2022). Available at SSRN: <a href="https://ssrn.com/abstract=4122594" target="_blank" rel="noopener">https://ssrn.com/abstract=4122594</a> or <a href="https://dx.doi.org/10.2139/ssrn.4122594" target="_blank" rel="noopener">http://dx.doi.org/10.2139/ssrn.4122594</a></p>
Data Package: Investors Reward Countries for Participating in Climate Agreements
<p>This package contains the processed dataset containing publicly available data, log files, and codes for the manuscript 'Investors Reward Countries for Participating in Climate Agreements'. The log files and codes correspond to the key regression output from the manuscript. All analysis was conducted using Stata version 18.5.</p>
Replication package for: Which Investors Matter for Equity Valuations and Expected Returns?
<p>Koijen, Ralph SJ, Robert J. Richmond, and Motohiro Yogo. <em>Which investors matter for equity valuations and expected returns?</em>. Review of Economic Studies. </p> <p>This repository contains replication material for "<em>Which investors matter for equity valuations and expected returns?</em>"</p>
Investment Behavior of Retail Investors
<p>This dataset is part of the author’s doctoral dissertation.</p>
FERDI Database on impact investors in Africa
<p><strong>Important:</strong> Lors de l’utilisation de cette base de données, merci de citer : Léon, F. et Rabary, S. « Impact investing in Africa : a 2024 analytical map », Rapport FERDI, 76 p. OU Léon, F. et Rabary, S. « L’investissement d’impact en Afrique : enseignements d’une cartographie du secteur », Rapport Ferdi, 84 p.</p> <p><strong>Avertissement</strong><br>Nous avons fait de notre mieux pour fournir des informations précises dans cette base de données. Cependant, ni nous ni les institutions auxquelles nous sommes ou avons été affiliés ne pouvons être tenus responsables des éventuelles erreurs restantes.</p> <p><strong>Questions</strong><br>Les questions peuvent être adressées à Florian Léon (<a rel="noopener">florian.leon1@ferdi.fr</a>) et/ou Sitraka Rabary (<a rel="noopener">sitraka.rabary@ferdi.fr</a>). Cependant, avant de poser des questions, merci de lire attentivement cette fiche ainsi que le rapport décrivant la base de données.</p> <p><strong>Base de données</strong><br>Ce fichier contient une liste des investisseurs d’impact opérant en Afrique en 2023. Il inclut (lorsque disponible) pour chaque investisseur des informations de base comme son année de création ou l’emplacement de son siège social.</p> <p><strong>Sources</strong><br>Sources : Les données ont été collectées manuellement en utilisant de nombreuses sources disponibles publiquement : sites web et rapports annuels des investisseurs d’impact, cartographies précédentes, etc. Un défi majeur a été d’harmoniser les données dans un format commun, car les définitions et les années considérées peuvent différer. En particulier, les données sur les actifs sous gestion ne sont pas toujours comparables.</p>
Data from: Dynamics of investor spanning trees around dot-com bubble
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Financial Products Overview for Investors
<div> <div> <div> <p>The dataset provides a detailed overview of a variety of exchange-traded funds (ETFs) or conventional funds, with crucial information for investors. It includes various attributes such as the fund name, total assets under management, investment style, twelve-month annualized performance, portfolio turnover, distribution fee level, price/earnings ratio, and dividend yield percentage.</p> <div> <div> <div> <p>This dataset has been specifically modified to not present real information about the investment funds, and the number of rows has been reduced.</p> </div> </div> </div> <p> </p> </div> </div> </div>
Data set The Determinants of Perceived Risk: A Moderating Role of investor Sophistication
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Dataset DETERMINANT FACTORS OF INVESTMENT SATISFACTION AMONG YOUNG INVESTORS OF INDONESIAN
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.