Are hedge funds worth your money? Hedge funds have developed from investment funds that were designed to lower the risk of your portfolio to a multitude of different investment styles with different goals. Their heyday was probably during the 90s and early 2000s when several star hedge fund managers rose to prominence and their assets under management grew significantly. However, since then hedge funds have been under scrutiny as their investment returns have been lacking and their ability to function as a diversification to a traditional stock and bond portfolio was put into question. As hedge funds have their own set of leverage and investment rules it is no wonder they have been accused of being greedy, unsuccessful and secretive. However, with this dataset you can make your own analysis.

Content This dataset covers monthly hedge fund returns starting from 1997. The date column refers to the last day of the month - the end date of the return period, if I understand correctly. There are 12 different hedge fund strategies covered and the return index series are formed as an aggregate of other hedge fund index providers.

The strategy explanations are in EDHEC website:

Convertible Arbitrage - https://risk.edhec.edu/conv-arb/ CTA Global - https://risk.edhec.edu/cta-global/ Distressed Securities - https://risk.edhec.edu/dist-sec/ Emerging Markets - https://risk.edhec.edu/emg-mkts/ Equity Market Neutral - https://risk.edhec.edu/equity-market-neutral/ Event Driven - https://risk.edhec.edu/event-driven/ Fixed Income Arbitrage - https://risk.edhec.edu/fix-inc-arb/ Global Macro - https://risk.edhec.edu/global-macro/ Long/Short Equity - https://risk.edhec.edu/ls-equity/ Merger Arbitrage - https://risk.edhec.edu/merger-arb/ Relative Value - https://risk.edhec.edu/relative-value/ Short Selling - https://risk.edhec.edu/short-selling/ Funds of Funds - https://risk.edhec.edu/fof/ Acknowledgements All credit for the maintenance and upload of the data goes to EDHEC. You should check their website for additional resources:

https://risk.edhec.edu/all-downloads-hedge-funds-indices

Inspiration The EDHEC hedge fund data is the data used in examples/vignettes of PortfolioAnalytics - a package for optimizing, testing and analyzing portfolio returns. You should be easily able to expand the analysis from the vignettes just by using the larger dataset available here:

https://cran.r-project.org/web/packages/PortfolioAnalytics/index.html

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

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

Investment funds can be distinguished by investment policy (equity funds, bond funds, mixed funds, real estate funds, hedge funds, other funds). This dataset covers outstanding amounts at the end of the period.

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

Sale-Or-Purchase-of-Stock Time Series for Jupiter Fund Management Plc. Jupiter Fund Management Plc is a publicly owned investment manager. The firm manages mutual funds, hedge funds, client focused portfolios, and multi-manager products for its clients. It invests in the public equity markets across U.K., Europe and global emerging markets. The firm also invests in fixed income markets, fund of funds products, hedge funds, and absolute return funds. Jupiter Fund Management Plc was founded in 1985 and is based in London, United Kingdom.

Are hedge funds worth your money?

Hedge funds have developed from investment funds that were designed to lower the risk of your portfolio to a multitude of different investment styles with different goals. Their heyday was probably during the 90s and early 2000s when several star hedge fund managers rose to prominence and their assets under management grew significantly. However, since then hedge funds have been under scrutiny as their investment returns have been lacking and their ability to function as a diversification to a traditional stock and bond portfolio was put into question. As hedge funds have their own set of leverage and investment rules it is no wonder they have been accused of being greedy, unsuccessful and secretive. However, with this dataset you can make your own analysis.

Content

This dataset covers monthly hedge fund returns starting from 1997. The date column refers to the last day of the month - the end date of the return period, if I understand correctly. There are 12 different hedge fund strategies covered and the return index series are formed as an aggregate of other hedge fund index providers.

The strategy explanations are in EDHEC website:

• Convertible Arbitrage - https://risk.edhec.edu/conv-arb/
• CTA Global - https://risk.edhec.edu/cta-global/
• Distressed Securities - https://risk.edhec.edu/dist-sec/
• Emerging Markets - https://risk.edhec.edu/emg-mkts/
• Equity Market Neutral - https://risk.edhec.edu/equity-market-neutral/
• Event Driven - https://risk.edhec.edu/event-driven/
• Fixed Income Arbitrage - https://risk.edhec.edu/fix-inc-arb/
• Global Macro - https://risk.edhec.edu/global-macro/
• Long/Short Equity - https://risk.edhec.edu/ls-equity/
• Merger Arbitrage - https://risk.edhec.edu/merger-arb/
• Relative Value - https://risk.edhec.edu/relative-value/
• Short Selling - https://risk.edhec.edu/short-selling/
• Funds of Funds - https://risk.edhec.edu/fof/

Acknowledgements

All credit for the maintenance and upload of the data goes to EDHEC. You should check their website for additional resources:

https://risk.edhec.edu/all-downloads-hedge-funds-indices

Inspiration

The EDHEC hedge fund data is the data used in examples/vignettes of PortfolioAnalytics - a package for optimizing, testing and analyzing portfolio returns. You should be easily able to expand the analysis from the vignettes just by using the larger dataset available here:

https://cran.r-project.org/web/packages/PortfolioAnalytics/index.html

China Retail Investor Sentiment Analytics provides sentiment analytics of Chinese retail investors based on 2 stock forums, Guba (GACRIS dataset) and Xueqiu (XACRIS dataset), the most popular stock forums in China from 2007.

By utilizing in-house NLP models which are dedicatedly optimized for Chinese stock forum posts and trained on a proprietary manually labeled and cross-checked training data, the dataset provides accurate text analytics of post content, including but not limited to quality, sentiment, and relevant stocks with relevance score. In addition to the aggregated statistics of stock sentiment and popularity, the dataset also provides rich and fine-grained information for each user/post in record level. For example, it reports the registration time, number of followers for each user, and also the replies/readings and province being published for each post. Moreover, these meta data are processed in point-in-Time (PIT) manner since 2019.

The dataset could help clients easily capture the sentiment and popularity among millions of Chinese retail investors. On the other hand, it also offers flexibility for clients to customize novel analytics, such as studying the sentiment (conformity/divergence) of users of different level of influence or posts of different hotness, or simply filtering the posts published by users which are too active/positive/negative in a time window when aggregating the statistics.

Coverage: All A-share and Hong Kong stocks, 300+ popular US stocks Update Frequency: Daily or intra-day

View LSEG's Lipper Fund Research Database, providing independent fund content to benchmark fund performance, manage risk, and more.

Stock Price Time Series for FactSet Research Systems Inc. FactSet Research Systems Inc., together with its subsidiaries, operates as a financial digital platform and enterprise solutions provider for the investment community worldwide. The company provides workstations, portfolio analytics, and enterprise data solutions, as well as managed services for supporting data, performance, risk, and reporting workflows. It offers subscription-based financial data and market intelligence on securities, companies, industries, and people that enable clients to research investment ideas, as well as analyze, monitor, and manage their portfolios. The company provides its services through its configurable desktop and mobile platform, data feeds, cloud-based digital solutions, and application programming interfaces. It serves investment professionals, including institutional asset managers, bankers, wealth managers, asset owners, partners, hedge funds, corporate users, and private equity and venture capital professionals. The company was founded in 1978 and is headquartered in Norwalk, Connecticut.

DAVP covers more than 2 million virtual portfolios created by 1.6 million users since 2013 and covers over 100 million rebalancing actions across all A-share stocks.

DAVP provides granular, record-level details for each rebalancing transaction, including the transition amount, price, and weight. Since 2022, it has also captured point-in-time (PIT) metadata on individual virtual portfolios, such as portfolio returns and popularity trends. This rich and structured dataset empowers clients to customize indicators based on their unique investment perspectives with ease.

In addition, by dividing the rebalancing records into different groups based on users’ experience, activity level, and portfolio diversity, DAVP provides easy-to-use derived insights into the investment strategy and behaviors of different groups of investors as below.

1)Popularity indicators. (e.g., number of rebalancing users/portfolios, number of rebalance, total rebalance weight/shares)

2)Sentiment indicators. (e.g., number of buy/sell users/portfolios, number of buy/sell weight/ shares, number of first buy users)

3)Market price indicators (e.g., buy/sell average/median price)

• Coverage: 5000+ A-share stocks
• History: From 2013-01-01
• Update Frequency: Daily

Comprehensive information is collected and published, quarterly on all Irish-resident investment funds. The main dataset details stock and transactions, with information on the scale, composition, geographical and sectoral exposures of funds’ assets and liabilities. Funds data are transmitted to the Central Statistics Office and the European Central Bank to feed into Irish and euro area balance of payments and national accounts statistics. The data are also a key input into the measurement of shadow banking based on Financial Stability Board definitions.

Concept: Portfolio investment is divided in assets and liabilities. Portfolio investment assets are transactions and positions realized through capital or debt securities, distinct from those included in direct investment or reserve assets. Flows constituted by the issue of credit securities commonly traded in secondary markets. It is divided in two main instruments: equity and investment fund shares; and debt securities. Equity and investment fund shares comprise all registers and instruments that recognize the creditors’ rights to the residual value of the company, once all creditors’ rights are liquidated. Debt securities are debt instruments require payments of interest or principal on a future moment. The debt instruments that can be traded in secondary markets affect this account. Securities with maturity inferior to one year are considered short term securities. Those of longer maturity are defined as long term securities. Portfolio investments liabilities are transactions and positions realized through capital or debt securities, distinct from those included in direct investment. Flows constituted by the issue of credit securities commonly traded in secondary markets. It is divided in two main instruments: equity and investment fund shares; and debt securities. Equity and investment fund shares comprises all registers and instruments that recognize the creditors’ right to the residual value of the company, once all creditors’ rights are liquidated. Debt securities are debt instruments require payments of interest or principal on a future moment. The debt instruments that can be traded in secondary markets affect this account. Securities with maturity inferior to one year are considered short term securities. Those of longer maturity are defined as long term securities.

Stock Price Time Series for Sprott Inc.. Sprott Inc. is a publicly owned asset management holding company. Through its subsidiaries, the firm provides asset management, portfolio management, wealth management, fund management, and administrative and consulting services to its clients. It offers mutual funds, hedge funds, and offshore funds, along with managed accounts. Further, the firm also provides broker-dealer activities. Sprott Inc. was formed on February 13, 2008 and is based in Toronto, Canada.

I'm fascinated how banking and large hedge funds are utilizing the huge amount of data they possess to drive the stock market in either direction. Many companies do gather these data and sell them again, while they are already public information. I'm a beginner in this world and I want to make majority of the scattered data available to everyone in one place to ease process of analysis with minimal cost possible. his dataset contains the prices for stocks since establishment until November 1st, 2021. The stocks divided based on the market index (Dow Johns, Nasdaq 100, S&P 500, and Russell 3000).

Hope you find dataset is useful.

Stock Price Time Series for CI Financial Corp. CI Financial Corp. is a publicly owned asset management holding company. Through its subsidiaries, the firm manages separate client focused equity, fixed income, and alternative investments portfolios. It also manages mutual funds, hedge funds, and fund of funds for its clients through its subsidiaries. The firm was founded in 1965 and is based in Toronto, Canada with additional offices in Vancouver, Canada; Calgary, Canada; and Montreal, Canada.

Baidu Search Index is a big data analytics tool developed by Baidu to track changes in keyword search popularity within its search engine. By analyzing trends in the Baidu Search Index for specific keywords, users can effectively monitor public interest in topics, companies, or brands.

As an ecosystem partner of Baidu Index, Datago has direct access to keyword search index data from Baidu's database, leveraging this information to build the BSIA-Consumer. This database encompasses popular brands that are actively searched by Chinese consumers, along with their commonly used names. By tracking Baidu Index search trends for these keywords, Datago precisely maps them to their corresponding publicly listed stocks.

The database covers over 1,100 consumer stocks and 3,000+ brand keywords across China, the United States, Europe, and Japan, with a particular focus on popular sectors like luxury goods and vehicles. Through its analysis of Chinese consumer search interest, this database offers investors a unique perspective on market sentiment, consumer preferences, and brand influence, including:

• Brand Influence Tracking – By leveraging Baidu Search Index data, investors can assess the level of consumer interest in various brands, helping to evaluate their influence and trends within the Chinese market.

• Consumer Stock Mapping – BSIA-consumer provides an accurate linkage between brand keywords and their associated consumer stocks, enabling investor analysis driven by consumer interest.

• Coverage of Popular Consumer Goods – BSIA-consumer focuses specifically on trending sectors like luxury goods and vehicles, offering valuable insights into these industries.

• Coverage: 1000+ consumer stocks

• History: 2016-01-01

• Update Frequency: Daily

Context

"Greed, for lack of a better word, is good"

The stock market has always intrigued me. Numbers, Charts, High-pressure environments, thinking on your feet, Wall Street, Hedge funds all of it!

To even begin to explore stocks, one needs to have a good amount of historical data and knowledge of a lot of technical details. Now, OHLC(Open High Low Close) data is available easily on many websites nowadays. But those as features are not enough to predict the stock prices. The stock market depends upon many many factors such as previous days performance, Global financial news, Public sentiment about the company, Mergers & Acquisitions, Moving Averages, etc

Feature Extraction is a tedious job to do, more so when we are talking about stocks. I have created this Pipeline to extract many Technical Indicators as well as lagged features for training Machine Learning algorithms for forecasting Stock Prices. One can also train multiple algorithms on multiple stocks and get an evaluation instantly on how did it perform.

Please check out the app below- https://stock-prediction-dashboard.herokuapp.com/

High-quality financial data especially which requires domain knowledge & expertise in quantitative methods is difficult to get and even if available it would be very costly. This was my motivation for creating and uploading this dataset on Kaggle, so anyone can leverage these extracted features and indicators to build and train their own machine learning models and identify patterns & trends.

Content

This dataset has around 64 features which include features extracted from OHLC, other index prices such as QQQ(Nasdaq-100 ETF) & S&P 500, technical indicators such as Bollinger bands, EMA(Exponential Moving Averages), Stochastic %K oscillator, RSI, etc.

Furthermore, It has lagged features from previous day price data as we know previous day prices affect the future stock price. Then, the data has date features which specify, if it's a leap year, if its month start or end, Quarter start or end, etc.

All of these features have something to offer for forecasting. Some tell us about the trend, some give us a signal if the stock is overbought or oversold, some portrays the strength of the price trend.

I will keep on adding all of the Nasdaq-100 companies to the dataset for the past 10 years approx. So when completed, this data will contain around 100 stocks.

Acknowledgements

This dataset belongs to me. I’m sharing it here so that people can build upon it and try and create some effective methods to predict the random walk.

Inspiration

Can you predict the unpredictable? Can you predict the Stock market movement using machine learning or deep learning techniques? To be precise, Can you generate realistic buy/sell signals for the next day based on future stock price estimates using time series modeling?

This dataset, titled the Mutual Fund Market Dataset, is a dedicated resource that delves deeply into a wide array of mutual fund schemes, their performance metrics, and market trends within India only. This dataset offers valuable insights for investors, financial analysts, and researchers, enabling them to make well-informed investment decisions and conduct thorough market research within the dynamic landscape of the Indian financial sector.

Key Features

How to Use This Dataset

1. Data Scientists: Employ for in-depth data analysis, modeling, and insightful data visualization.
2. Stock Brokers: Utilize for real-time fund performance monitoring and to provide informed investment recommendations.
3. Mutual Fund Investors: Leverage for tracking NAVs and making informed fund selections aligned with financial goals.
4. Researchers: Utilize for conducting comprehensive market studies, economic impact assessments, and academic research.
5. Financial Analysts: Assess compliance scores and ratings to optimize investment portfolios and provide data-driven recommendations.

Common-Stock Time Series for BlackRock Inc. BlackRock, Inc. is a publicly owned investment manager. The firm primarily provides its services to institutional, intermediary, and individual investors including corporate, public, union, and industry pension plans, insurance companies, third-party mutual funds, endowments, public institutions, governments, foundations, charities, sovereign wealth funds, corporations, official institutions, and banks. It also provides global risk management and advisory services. The firm manages separate client-focused equity, fixed income, and balanced portfolios. It also launches and manages open-end and closed-end mutual funds, offshore funds, unit trusts, and alternative investment vehicles including structured funds. The firm launches equity, fixed income, balanced, and real estate mutual funds. It also launches equity, fixed income, balanced, currency, commodity, and multi-asset exchange traded funds. The firm also launches and manages hedge funds. It invests in the public equity, fixed income, real estate, currency, commodity, and alternative markets across the globe. The firm primarily invests in growth and value stocks of small-cap, mid-cap, SMID-cap, large-cap, and multi-cap companies. It also invests in dividend-paying equity securities. The firm invests in investment grade municipal securities, government securities including securities issued or guaranteed by a government or a government agency or instrumentality, corporate bonds, and asset-backed and mortgage-backed securities. It employs fundamental and quantitative analysis with a focus on bottom-up and top-down approach to make its investments. The firm employs liquidity, asset allocation, balanced, real estate, and alternative strategies to make its investments. In real estate sector, it seeks to invest in Poland and Germany. The firm benchmarks the performance of its portfolios against various S&P, Russell, Barclays, MSCI, Citigroup, and Merrill Lynch indices. BlackRock, Inc. was founded in 1988 and is based in New York, New York with additional offices in A

Einstellung zum Geld und Verhalten bei der Anlage von Geld undVermögen. Themen: Ausgabebereitschaft für Bekleidung, Uhren, Schmuck,Wohnungseinrichtung, Wohneigentum, Altersvorsorge, Rücklagen,Antiquitäten, Kraftfahrzeuge, Urlaub, Reisen, Hobbys, Sport,Essen, Konzerte, Bücher, Fortbildung, Fernsehgeräte undVideogeräte; persönliche Ereignisse in den letzten fünf Jahrenin den Bereichen Beruf, Finanzen, Privatleben, Familie undHaushalt; Einstellung zum Geld, zum Sparen und zu ausgewähltenAnlageformen (Skala); Einstellung zur Kreditaufnahme;Informiertheit über Geldanlagemöglichkeiten;Sicherheitsorientierung oder Renditeorientierung bei derGeldanlage; Liquiditätsorientierung; Einstellung zum Bausparenund Sparneigung; Sparverhalten, Sparziele, Sparmotive; Spielenvon Lotto, Toto und sonstigen Lotteriespielen; derzeitaufgenommene Kredite und Angabe der privaten oder betrieblichenVerwendung; zurückgezahlte Kredite in den letzten fünf Jahren;Hypothekendarlehn; Zusammenleben mit einem Partner undzuständige Person in Fragen der Alltagsfinanzen sowie beigrößeren Anschaffungen; Entscheidungskompetenz imPartnerhaushalt; Verhalten bei der Informationsbeschaffung überSparverträge, Aktien, festverzinsliche Wertpapiere,Investmentfonds, Kredite, Bausparverträge, Baufinanzierung undLebensversicherungen; Anzahl der beschafften Informationen;Einschätzung der Rentenentwicklung; Notwendigkeit eigenerfinanzieller Altersvorsorge; Rentenanspruch als Pflichtmitgliedoder freiwilliges Mitglied; Beamtenpension; Zusatzversorgung imöffentlichen Dienst; betriebliche Altersversorgung; Kenntnisder zu erwartenden Rentenhöhe im Alter; Vertrauen inausgewählte inländische und ausländische Banken,Versicherungen, Industrieanleihen sowie Investmentfonds;Kenntnis von sogenannten Allfinanz-Angeboten; Kompetenz derHausbank sowie der Versicherungsgesellschaften bei ausgewähltenFinanzdienstleistungen; Einstellung zu Versicherungsgeschäftenbei der Bank und zu Bankgeschäften bei der Versicherung;wichtigste Kriterien für eine ideale Geldanlage; Einschätzungder derzeitig und zukünftig vorteilhaftesten Geldanlage sowieder am wenigsten vorteilbietenden Anlageform; Bekanntheitsgradsowie im eigenen Haushaltsbesitz befindliche Anlageformen;Angabe der selbst erworbenen Geldanlagen; Einstiegsalter beimKauf ausgewählter Wertpapiere und Edelmetalle; möglicheAnlageformen in den nächsten drei Jahren; Publikumsbank undAnlageformen, die man weiterempfehlen würde; Bekanntheitsgradvon Publikums- und Geschäftsbanken; Angabe der persönlichenBankverbindung; Hauptbankverbindung und Dauer der Bindung andie Hausbank; Hausbankwechsel; Besitz eines eigenen Girokontos,Sparbuchs, Wertpapierdepots oder von Termingeldern bei derHaupt- sowie einer Zweitbank; Bekanntheitsgrad und Besitz vonKreditkarten; besonders präferierte Kreditkarte;Bekanntheitsgrad von sogenannten Gold-Karten undBesitzinteresse; Besitz von Kreditkarten ausgewählter Firmen;Bekanntheitsgrad sowie Besitz und besondere Präferenz fürWertpapierfonds und Immobilienfonds; Kenntnis und Besitzausgewählter privater sowie öffentlicherLebensversicherungsgesellschaften; besonders präferierteLebensversicherungsgesellschaften; Besitz vonAussteuerversicherung für die Kinder, Sterbegeldversicherung,Ausbildungsversicherung und Lebensversicherungen;Eintrittsalter beim Abschluß der ersten Lebensversicherung;Absicht, weitere Lebensversicherungen abzuschließen, undPräferenz für eine Lebens- oder Kapitallebensversicherung;persönlicher Besitz von Hausratversicherung,Privathaftpflichtversicherung, KFZ-Haftpflichtversicherung,KFZ-Kaskoversicherung; Rechtschutzversicherung sowie privaterKranken- und Krankenhausversicherung; weitereVersicherungsnehmer für die vorgenannten Versicherungen imHaushalt; Kenntnis, Besitz und Präferenz ausgewählterBausparkassen bzw. Bausparverträge;Anzahl der Bausparverträge und Präferenz fürbestimmte Bausparkassen; Bausparverträge in der Tilgungsphase;Abschlußalter beim ersten Bausparvertrag; Interesse am Abschlußeines Bausparvertrages; detaillierte Angaben über Art undUmfang des Immobilienbesitzes; angemietetes Haus, Wohnung undFerienhaus; Besitz baureifer Grundstücke; land- undforstwirtschaftlicher Besitz; Art der geplantenRenovierungsarbeiten und Neueinbauten am Haus; Einstiegsalterbeim Immobilienkauf; geplante Anschaffung einer Immobilie inden nächsten fünf Jahren; Planungszeitraum; Eigennutz oderHaus- bzw. Wohnungskauf zum Vermieten; Kauf einesWochenend-oder Ferienhauses im In- und Ausland; Wohnstatus undBebauungsart; Baujahr des Hauses; Heizungsart und verwendeteHeizungsenergie; Ausstattung des Hauses bzw. der Wohnung mitGarten, Balkon und Terrasse; Wohnfläche; Sonderausstattung desHauses mit Fußbodenheizung, Wärmepumpe, Solaranlage, offenemKamin oder Kaminofen; Medienkonsum; Zeitschriftennutzung;Fernsehkonsum. Indizes: Geldanlagetyp; Mentalitätsgruppen; Lebensphase;Zeitschrift-TV-Nutzung. Demographie: Einkommen; Haushaltseinkommen; Haushaltsgröße;Gemeindegröße (nach Boustedt); Bundesland; Wochentag des Interviews. Attitude to money and conduct in investing money and wealth. Topics: willingness to pay for clothing, watches, jewelery, residencefurnishings, residential property, provision for old age, financialreserves, antiques, motor vehicles, vacation, trips, hobbies, sport,food, concerts, books, further education, television sets and videoequipment; personal events in the last 5 years in the areas ofoccupation, finances, private life, family and household; attitude tomoney, saving and selected forms of investment (scale); attitude toborrowing; extent to which informed about financial investmentpossibilities; safety orientation or returns orientation in financialinvestment; liquidity orientation; attitude to saving with a buildingand loan association and inclination to save; savings habits, savingsgoals, savings motives; playing Lotto, Toto and other lottery games;current borrowing and indication of private or business use; loansrepayed in the last 5 years; mortgage loan; living together with apartner and person responsible for questions of day-to-day finances aswell as in major purchases; ability to make decisions in partnerhousehold; conduct in gathering information on savings contracts,stocks, fixed-interest stocks and shares, investment funds, loans,building loan contracts, construction financing and life insurancepolicies; amount of information gathered; assessment of pensiondevelopments; necessity of personal financial provision for old age;right to a pension from compulsory or voluntary membership; civilservice pension; supplementary pension in the civil service; companyprovision for old age; knowledge about the anticipated amount ofpension in old age; trust in selected domestic and foreign banks,insurance companies, industry loans as well as investment funds;knowledge about the so-called ´Allfinanz´ offerings; ability of one´sown bank as well as of insurance companies in selected financialservices; attitude to insurance business at a bank and bank businesswith an insurance company; most important criteria for an idealfinancial investment; assessment of current and future mostadvantageous financial investment as well as of the least advantageousform of investment; degree of familiarity as well as forms ofinvestment found in one´s own household; specification of financialinvestments obtained personally; age at purchase of selected stocks andshares and precious metals; possible forms of investment in the nextthree years; public bank and forms of investment one would furtherrecommend; degree of familiarity of public and business banks;specification of personal bank; primary bank and length of tie to one´sbank; change of one´s bank; possession of a personal checking account,savings account, depot for stocks and shares or fixed-term deposits inthe primary as well as secondary bank; degree of familiarity andpossession of credit cards; especially preferred credit card; degree offamiliarity of so-called gold cards and interest in them; possession ofcredit cards of selected companies; degree of familiarity as well aspossession and particular preference for stocks and shares funds andreal estate funds; knowledge and possession of selected private as wellas public life insurance companies; particularly preferred lifeinsurance companies; possession of dowry insurance for the children,death benefit insurance, education insurance and life insurancepolicies; age at conclusion of the first life insurance; intent toconclude further life insurance policies and preference for straightlife or capital life insurance; personal possession of householdinsurance, personal liability insurance, automobile liabilityinsurance, automobile third party, fire and theft insurance, legalcosts insurance as well as private health and hospital insurance;others in the household having the above-mentioned insurance polices;knowledge, possession and preference for selected loan and buildingassociations or building loan contracts; number of building loancontracts and preference for certain loan and building associations;building loan contracts in the repayment phase; age at conclusion offirst building loan contract; interest in conclusion of a building loancontract; detailed information about type and extent of possession ofreal estate; rented house, apartment and vacation house; possession ofplots available for building; agricultural and forestry possession;type of renovation and addition planned for the house; age at purchaseof real estate; planned acquisition of real estate in the next fiveyears; planning time-frame; personal use or purchase of house orapartment to rent; purchase of a weekend or vacation home at home orabroad; residential status and type of building; year of constructionof house; type of heating and source of energy used; equipment of thehouse or apartment with garden, balcony and terrace; living space;special equipment in house: under floor

Common-Stock Time Series for Cohen & Steers Inc. Cohen & Steers, Inc. is a publicly owned asset management holding company. Through its subsidiaries, the firm provides its services to institutional investors, including pension funds, endowments, and foundations. It manages separate client-focused equity, fixed income, multi-asset, and commodity portfolios through its subsidiaries. The firm launches and manages equity, fixed income, balanced, and multi-asset mutual funds through its subsidiaries. Through its subsidiaries, it also launches and manages hedge funds. The firm invests in public equity, fixed income, and commodity markets across the globe through its subsidiaries. Through its subsidiaries, it invests in companies operating in the real estate sector, including real estate investment trusts, infrastructure sector, and natural energy resources sector for its equity and fixed income investments. The firm also invests in preferred securities for its fixed income investments through its subsidiaries. The firm is a leading global investment manager specializing in real assets and alternative income, including real estate, preferred securities, infrastructure, resource equities, commodities, as well as multi-strategy solutions. Cohen & Steers, Inc. was founded in 1986 and is based in New York.

DK Investment Funds I re-created the DK Investment Funds dataset – essentially cleaning it and making it more compact + added fined-tuned columns for visualization. The dataset contains of 346 Danish investment funds with asset classes such as stock, bonds and mixed stock/bonds funds + a few alternatives, real estate funds and unknows. Also available on GitHub repo: https://github.com/MartinSamFred/DKInvestmentFunds.git

Each row in the dataset contains a Danish investment fund

Uses Various analysis and visualization. Practice exercises etc.

Disclaimer The data and information in the data set provided here are intended to be used primarily for educational purposes only. I do not own any data, and all rights are reserved to the respective owners as outlined in “Acknowledgements/sources”. The accuracy of the dataset is not guaranteed accordingly any analysis and/or conclusions is solely at the user's own responsibly and accountability.

Acknowledgements/sources Data is available on: BankInvest: https://bankinvest.dk/ C WorldWide: https://cww.dk/ Carnegie Invest: https://www.carnegie.dk/ Danske Invest: https://www.danskeinvest.dk/w/show_pages.front?p_nId=75 Falcon Invest: https://falconinvest.dk/ Fundamental Invest: https://fundamentalinvest.dk/ IA Invest: https://iainvest.dk/ Maj Invest: https://majinvest.dk/ Multi Manager Invest: https://www.nordnet.dk/ Nordea Invest: https://www.nordeafunds.com/da Nykredit Invest: https://www.nykreditinvest.dk/ SGD Invest: https://www.nordeafunds.com/da SEB Invest: https://seb.dk/SEBinvest/ Sparinvest: https://www.sparinvest.dk/ Stockrate Asset Management: https://stockrate.dk/ Sydinvest: https://www.sydinvest.dk/ Wealth invest: https://wealthinvest.dk/ Bloomberg Dataset picture / cover photo: Nathan Dumlao (https://unsplash.com/)