What is Mutual Funds Data? Examples, Providers & Datasets to Buy

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

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 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.

Where Can I Buy Mutual Funds Data?

You can explore our data marketplace to find a variety of Mutual Funds Data tailored to different use cases. Our verified providers offer a range of solutions, and you can contact them directly to discuss your specific needs.

How is the Quality of Mutual Funds Data Maintained?

The quality of Mutual Funds Data is ensured through rigorous validation processes, such as cross-referencing with reliable sources, monitoring accuracy rates, and filtering out inconsistencies. High-quality datasets often report match rates, regular updates, and adherence to industry standards.

How Frequently is Mutual Funds Data Updated?

The update frequency for Mutual Funds Data varies by provider and dataset. Some datasets are refreshed daily or weekly, while others update less frequently. When evaluating options, ensure you select a dataset with a frequency that suits your specific use case.

Is Mutual Funds Data Secure?

The security of Mutual Funds Data is prioritized through compliance with industry standards, including encryption, anonymization, and secure delivery methods like SFTP and APIs. At Datarade, we enforce strict policies, requiring all our providers to adhere to regulations such as GDPR, CCPA, and other relevant data protection standards.

How is Mutual Funds Data Delivered?

Mutual Funds Data can be delivered in formats such as CSV, JSON, XML, or via APIs, enabling seamless integration into your systems. Delivery frequencies range from real-time updates to scheduled intervals (daily, weekly, monthly, or on-demand). Choose datasets that align with your preferred delivery method and system compatibility for Mutual Funds Data.

How Much Does Mutual Funds Data Cost?

The cost of Mutual Funds Data depends on factors like the datasets size, scope, update frequency, and customization level. Pricing models may include one-off purchases, monthly or yearly subscriptions, or usage-based fees. Many providers offer free samples, allowing you to evaluate the suitability of Mutual Funds Data for your needs.

What Are Similar Data Types to Mutual Funds Data?

Mutual Funds Data is similar to other data types, such as ETF Data, Private Equity Data, Venture Capital Data, Investors Data, and Hedge Funds Data. These related categories are often used together for applications like Portfolio Optimization.