Top Derivatives Data APIs, Datasets, and Databases
Find the top commercial Derivatives Data sets, feeds and streams.
Derivative Reference Data
Japan+ 30 others
|Use Case||Portfolio Valuation, Portfolio Management + 1 more|
Derivatives End-of-Day Pricing
Derivative Corporate Actions (DerivActions)
Japan+ 33 others
|History||10 years of past data available|
|Use Case||Risk Management, Portfolio Valuation + 1 more|
OTC-Data Swap Curves
Short Interest Data
|Use Case||Stock Picking|
Swaption Volatility Data
FX Option Volatility Data
Global End-of-Day Pricing Data
|History||10 years of past data available|
|Use Case||Stock Valuation, equity valuations + 2 more|
Historical Global End-of-Day Pricing Data
|History||13 years of past data available|
|Use Case||Investing, Asset Management + 3 more|
|Use Case||Data Governance|
Top Derivatives Data Providers, Vendors, and Companies
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The Ultimate Guide to Derivatives Data 2020
Learn everything about Derivatives Data. Understand data sources, popular use cases, and data quality.
Table of Contents
What is Derivatives Data?
Derivatives data is a sub-category of financial market data. This type of data refers to information that is generated from the value of various instruments in the financial market. These instruments include the prices of commodities and their natures, currencies, stocks and stocks indices, bonds and many other securities being traded in the financial market. Derivatives data is based on the performances of the instruments in the financial market, and it can be used to gain insights on the market.
How is Derivatives Data collected?
Derivatives data is collected through various sources. These sources include market research firms, securities exchanges, news aggregators, brokers, traders, online services and investors. These sources all record and analyze the performances of earlier mentioned market instruments or entities, and the data compiled is what we refer to as derivatives data. These sources utilize 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) and information gotten from brokers and traders (from day to day market activities). This data is then compiled into accurate derivatives datasets.
What are the typical attributes of Derivatives Data?
Derivatives data feeds possess an extensive list of attributes. Because it concerns the financial market and the trading of numerous securities, derivatives data combines all of the attributes of the financial and stock markets performances. If you’re looking to buy derivatives datasets, then the attributes you should look out for include:
• Bidding attributes: derivatives data contains the bidding prices and asking prices of securities in the financial markets, which in turn is determined by their performances
• Trading Attributes: data on the details of trading activities for particular periods
• Financial ratios: financial ratios are concerned with the analysis on the performances of securities
What is Deriviatives Data used for?
Derivatives data is mostly important in the aspect of optimizing portfolios. Portfolio optimization involves the selection of securities and financial market instruments, combining them to achieve the best returns or yields when investments have been made on them. Since derivatives data is centered on the derived performances of the aforementioned securities, then it is these same performances that are used to avoid unreasonable risk. Derivatives data helps to analyze the information from datasets, and predict the future performances of the selected securities in the market in order to make a profitable portfolio that has the lowest risk as is possible.
How can a user assess the quality of Derivatives Data?
The best derivatives data will possess the following quality aspects. Derivatives data should be:
• Relevant: for derivatives data to be considered of best quality, it needs to serve the purpose of providing information on the particular security its user requires it for i.e. be relevant to its use case.
• Reliable: the information obtained from derivatives data needs to be trustworthy at all times. This is because derivatives data is used to optimize portfolios, and any misinformation can lead to a wrong combination of assets.
• Authentic: derivatives data must be based on figures and facts, not subjective opinions and preferences.
Popular Derivatives Data Use Cases
Find out the most common applications of Derivatives Data.