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Best Mutual Funds Datasets, Databases & APIs

What is Mutual Funds Data?

Mutual funds data provides intelligence on combinations of securities. It is used by investors and traders in the securities markets to identify profitable portfolios and alpha generation opportunities. Datarade helps you access the best mutual funds data feeds and APIs.Learn more

Recommended Mutual Funds Data Products

11 Results

Realtime and Historical Global ETF data and Mutual Funds prices

by Finage
(ETFs) and mutual funds data. ... Finage provides real-time, delayed, end-of-day, and historical pricing data for exchange-traded funds
Available for 6 countries
2.9K Symbols
10 years of historical data

Mutual Funds API by Finnworlds

data on mutual funds. ... The mutual funds data is subdivided into three main categories: General data on a mutual fund.
Available for 54 countries
12 years of historical data
Pricing available upon request

Tradefeeds Mutual Funds API and Database

The Mutual Funds API provides comprehensive big data on mutual funds. ... The Mutual Funds API is a format of obtaining data on real-time and historical mutual funds including
Available for 249 countries
15 years of historical data
Pricing available upon request

QuoteMedia Mutual Funds, ETFs, UITs and REITs

Mutual Funds and ETF data delivered for visualization and display, ready for integration into any system ... • Over 88,000 share classes • Mutual Funds • Unit Investment Trusts • Index Funds • Closed-End Funds
Available for 2 countries
10 years of historical data
Pricing available upon request

EDI Offshore Reporting Funds - largest proprietary database of Fund Manager details

-Identification of constant NAV funds to provide assurance that there is no missing data. ... The Offshore Reporting Funds service is a partnership between Exchange Data International (EDI) and Financial
Available for 249 countries
Pricing available upon request

US Mutual Fund and Closed-End Fund Data

Cannon Valley Research provides comprehensive pricing and reference data on US Mutual Funds. ... Coverage of over 9,000 open-ended mutual funds (> 30,000 share classes) and 500 US listed Closed-End
Available for 1 countries
4 years of historical data
Pricing available upon request
Free sample available

RIMES ETF Fund Level data - Worldwide

Leveraging our award-winning Managed Data Services, RIMES normalizes, validates and enriches ETF data ... RIMES ETF offering provides high-quality ETF fund level data directly from issuers from all over the
Available for 249 countries
7.5K +, ETFs/ETPs
100% Bespoke Format
Available Pricing:
Monthly License
Yearly License
Usage-based
Free sample available

EPFR Core Offerings - Fund Flows and Allocations Data

tracks 132,000 share classes with more than $50tr in AUM We track both traditional and alternative funds ... EPFR Fund Flows and Allocations data helps financial professionals understand where money is moving,
Available for 58 countries
140K Share classes
25 years of historical data
Pricing available upon request
Free sample available

RIMES ETF Multiple Basket Data

Leveraging our award-winning Managed Data Services, RIMES normalizes, validates and enriches ETF data ... source in order to provide superior transparency, data quality and use case flexibility.​
Available for 249 countries
7.5K + ETFs/ETPs
100% Fit-For-Purpose Format
Pricing available upon request
Free sample available

EPFR Stock Allocations and Flows

The data shows a total dollar flow and average allocation into a stock by funds sharing a common geographical ... focus and can be filtered by active, passive, mutual fund and ETF.
Available for 54 countries
18K Securities
11 years of historical data
Pricing available upon request
Free sample available

More Mutual Funds Data Products

Discover related mutual funds data products.
249 countries covered
15 years of historical data
The Mutual Funds API is a format of obtaining data on real-time and historical mutual funds including equity (stock) funds, bond (fixed-income) funds, growth...
54 countries covered
12 years of historical data
Mutual Funds API is a data delivery format that allows you to get instantly general and financial performance data on mutual funds. In addition, you obtain d...
USA covered
4 years of historical data
Cannon Valley Research provides comprehensive pricing and reference data on US Mutual Funds. The database is updated daily. This includes open and Closed-End...
140K Share classes
58 countries covered
25 years of historical data
EPFR Fund Flows and Allocations data helps financial professionals understand where money is moving, how fund managers are investing that money, and what imp...
18K Securities
54 countries covered
11 years of historical data
Daily/Monthly Total Dollar Flow-sum of monthly stock allocations and monthly/daily fund flows. Average Allocation-Equal/Fund-weighted average percentage allo...
7.5K +, ETFs/ETPs
100% Customizable
249 countries covered
RIMES ETF offering provides high-quality customizable ETF data directly from source in order to provide superior transparency, data quality and use case flex...
54 countries covered
12 years of historical data
Mutual Funds API is a data delivery format that allows you to get instantly general and financial performance data on mutual funds. In addition, you obtain d...
249 countries covered
15 years of historical data
The Mutual Funds API is a format of obtaining data on real-time and historical mutual funds including equity (stock) funds, bond (fixed-income) funds, growth...
18K Securities
54 countries covered
11 years of historical data
Daily/Monthly Total Dollar Flow-sum of monthly stock allocations and monthly/daily fund flows. Average Allocation-Equal/Fund-weighted average percentage allo...
140K Share classes
58 countries covered
25 years of historical data
EPFR Fund Flows and Allocations data helps financial professionals understand where money is moving, how fund managers are investing that money, and what imp...
USA covered
4 years of historical data
Cannon Valley Research provides comprehensive pricing and reference data on US Mutual Funds. The database is updated daily. This includes open and Closed-End...
2 countries covered
10 years of historical data
QuoteMedia offers comprehensive coverage for U.S. and Canadian Mutual Funds and Exchange Traded Funds (ETFs), as well as Unit Investment Trusts (UITs) and Re...
Finnworlds
Based in Bulgaria
Finnworlds
Finnworlds is a data provider offering Financial Institution Credit Rating Data, Stock Market Sentiment Data, Core Financial Data, Financial Entities Data, a...
datarade.ai - Cannon Valley Research profile banner
Cannon Valley Research
Based in USA
Cannon Valley Research
Cannon Valley Research provides comprehensive data on US listed Closed-End Funds, including pricing, metadata and holdings.
datarade.ai - Exchange Data International profile banner
Exchange Data International
Based in United Kingdom
Exchange Data International
With EDI you get high quality, affordable financial data customized to precisely fit your operational requirements.
ISO9001
Certified
ISO27001
Certified
datarade.ai - RIMES Technologies profile banner
RIMES Technologies
Based in USA
RIMES Technologies
We provide specialist managed data services and regtech solutions to asset managers, owners, servicers and banks worldwide. We deliver cloud-based services t...
Global
ETF Coverage
350+
clients worldwide
60/100
Serving top asset managers
datarade.ai - EPFR Global profile banner
EPFR Global
Based in USA
EPFR Global
EPFR’s Flows and Allocations data provides a unique view on investor and fund manager sentiment across global markets, helping buy and sell-side institutions...
25 years
History
Buyside
Data sourced direct from
$50 Tr
Tracked AUM
datarade.ai - QuoteMedia profile banner
QuoteMedia
Based in USA
QuoteMedia
QuoteMedia, Inc. offers comprehensive financial market data and research solutions for online brokerages, clearing firms, banks, public corporations, media p...

The Ultimate Guide to Mutual Funds Data 2023

Learn about mutual funds data analytics, sources, and collection.

What is Mutual Funds Data?

Mutual funds data is information on investment vehicles structured of funds pooled together by numerous investors, in a bid to invest the pooled resources into securities such as bonds, stocks, and money market instruments. Mutual funds data provides information on portfolios and portfolio performances, particularly historical returns, to existing investors, as well as projected yields on returns for potential investors.

How is Mutual Funds Data collected?

Data on mutual funds is usually collected the same way that most financial market data is collected. Various sources are involved in mutual funds data collection, including news aggregators, brokers, investors, traders, securities exchanges and markets, research firms and online services. The information from these sources is recorded and analyzed with a particular focus on the performances of the securities in a mutual fund. There is also the utilization of various tools, methods and measures such as graphs, figures, charts, statistics, news related to securities trading, market analytics, expert opinions, public records (especially information from regulatory instructions).

What are the typical attributes of Mutual Funds Data?

A mutual funds data should include the following:
Day returns: this refers to the change in the fund’s value in the last 24 hours or 2 days. It is updated daily.
Launch date: refers to the day the fund was started. An older fund is of less risk, considering it still exists after a period of time.
Category and sub-category of fund: the category and sub-category of the fund are determined by its main objective for being set up.
Returns 3Y: this is a backward projection of the fund to see how much yield it would have generated three years from the present date.
Risk: the probability of the fund not yielding investment returns.

What is Mutual Fund inflow/outflow?

In the event that a mutual fund or ETF has a higher net inflows, fund managers (mutual funds) are considered to have more cash at their disposal to trade. Mutual funds inflow translates to a rise in the demand for the underlying assets. In contrast, high outflow means that investors have less cash at their disposal, leading to a fall in demand for the underlying assets. In a nutshell, when investors are putting more money into mutual funds, there’s an increase in inflows, reflecting wider investor optimism, while greater outflows tend to show a general mood of apprehension amongst investors.

What is Mutual Funds Data used for?

Mutual funds data is primarily useful in portfolio optimization. Selecting a profitable portfolio that is low in risk can be difficult. With information on risks, returns 3Y, grow ratio, category and sub-category, return and maturity provided by mutual funds data, it is easier to combine securities in a portfolio that yields profitable returns, while at the same time managing risk. Additionally, mutual funds data is essential for making investment decisions, as well as in making stock market predictions. Lastly, for analyzing portfolios, as a stock broker must do, mutual funds data proves extremely useful.

What are the 3 types of Mutual Funds?

The three major types of mutual funds include money market funds, bond funds and stock funds.

• Money market funds – Money market funds are considered the funds with the lowest associated risk, because, by law, they are only able to be invested in standard quality and short term investments that are advanced by the US government, US corporations, and state and local governments. The dividends paid for money market funds are a true indicator of short-term interest rates. Even though they produce smaller returns when compared to other mutual funds, the fact that they are taken on a short term basis significantly reduces risks of loss.

• Bonds funds – Unlike money market funds, bonds funds are not restricted to short-term investments only. The fact that they are can be spread over a longer period of time means that the yields are more likely to be higher even though the risks are also accelerated. Examples include US Treasury and company bonds.

• Stock funds – Also known as equity funds, these mutual funds are valued very highly. Stock funds are the most volatile mutual funds and are considered to pose the highest potential risks for investors because stock prices can rise and fall dramatically depending on various market factors. Stock funds are further classed into growth funds, income funds, index funds and sector funds.

How to calculate risk using Mutual Funds Data?

The information provided by mutual funds data can be used to determine the investment risks that are associated with stocks, bonds and mutual fund portfolios. There are five major indicators of investment risks for mutual funds that include Alpha, Beta, R-squared, Standard Deviation and the Sharpe ratio. As key statistical measures, these five major historical forecasters of investment risk and volatility forms the basic components of Modern Portfolio Theory (MPT). Once the five indicators are determined, they form the basis for MTP which is a standard financial methodology that is applied in the assessment of the performance of equity, fixed-income and mutual fund investments.

Do Mutual Funds have maturity dates?

Unless an investor buys Equity Linked Savings Schemes (ELSS) or Fixed Maturity Plans (FMP), mutual funds do not usually have a maturity date. However, mutual funds lack liquidity. This means that they allow an investor to request that their shares be converted into liquid cash at any given moment. Nonetheless, unlike stocks which trade at any time of the day, in the majority of cases, mutual funds redemption can only take place at close of the trading day.

How can I interpret Mutual Funds Data?

Upon buying mutual funds data from a data marketplace, one of the hurdles that an investor will most likely face is the interpretation of data. The first step to interpretation of mutual funds data is in understanding that they offer a great deal of information pertaining to their portfolio and historical returns to current and potential investors. The most important aspects of the data include:

• A day returns – how much the fund’s value has changed in the last 1 day.
• Launch data – the date when the fund was launched.
• Category – tells you about the fund’s core purpose.
• Growth rating – historical data analysis of the mutual funds.
• Returns 3Y – backdated returns an investor could have earned if they invested three years ago.
• Min SIP amount – the lowest amount of money an investor can inject into the fund that is needed in a monthly basis.

Interpreting mutual funds data usually involves tackling each of these data points separately to derive the insights necessary for decision-making.

What is Mutual Funds Data analysis?

Mutual funds collect money from public investors and use it to acquire other securities that may include stocks or bonds. Therefore, the value of a mutual fund company is tied down on the overall performance of the stocks the company consciously decides to buy. Buying a mutual fund therefore simply means investing in its portfolio performance. Given that a share of a mutual fund involves investments in many differing stocks, there is need for analysis of data to determine the best performing portfolios before the common pool of public funds can be used to buy mutual funds. Therefore, mutual funds data analysis is the primary analysis of the fund’s growth or value, median market cap, rolling returns, standard deviation and a further narrowing down of its portfolio performance by sector, geographical location, or industry. Through proper data analysis of mutual funds, it is possible for investors to highlight a given fund’s attractiveness when compared to others.

What is a Fund screener?

Investors looking to buy mutual funds data online or who are searching for mutual funds data subscriptions services are most likely to encounter mutual funds screeners on countless websites and data trading platforms. These fund screeners give users the opportunity to only select trading instruments that are best suited for a given mutual fund profile. They enable users to sieve out mutual fund data as per market capitalization, price, prospective dividend yield, available volume of funds and the nominal return on investment. Because the pool of mutual funds data is very large, fund screeners enable investors to evaluate thousands of mutual funds within a short space of time. Hence, investors have the opportunity to save time by selecting the funds that do not meet their requirements and separating them from those that meet their user-defined metrics.

How can a user assess the quality of Mutual Funds Data?

Like any other financial market data, mutual funds data must be reliable. Users of this data must know they can rely on its accuracy to make decisions based on mutual funds information. Mutual funds data must also be timely. It must be updated regularly to reflect market conditions so as not to give outdated information. Mutual funds data must also be precise, leaving no room for errors or mistakes, as important investment decisions are to be made based on its information. Lastly, it must be relevant to the user’s desired use case.

Where can I buy Mutual Funds Data?

Data providers and vendors listed on Datarade sell Mutual Funds Data products and samples. Popular Mutual Funds Data products and datasets available on our platform are Realtime and Historical Global ETF data and Mutual Funds prices by Finage, Mutual Funds API by Finnworlds by Finnworlds, and Tradefeeds Mutual Funds API and Database by Tradefeeds.

How can I get Mutual Funds Data?

You can get Mutual Funds Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Mutual Funds Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time Mutual Funds Data APIs, feeds and streams to download the most up-to-date intelligence.

What are similar data types to Mutual Funds Data?

Mutual Funds Data is similar to Alternative Data, ESG Data, Merger & Acquisition Data, Commodity Data, and Currency Data. These data categories are commonly used for Portfolio Optimization.

What are the most common use cases for Mutual Funds Data?

The top use cases for Mutual Funds Data are Portfolio Optimization.

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Datos de fondos de inversión (ES)