Options Data: Definition, Uses, Datasets & Data Sources

Options Data Explained

Background and Introduction to Options Data

With a handful of options data available to access, such as call options and put options; the data is used to help make the best decision for the broker. There are different indicators that can be used in options datasets to determine the stock market direction. The standard indicator is the Put-Call Ratio (PCR).

This has been used for a long time and works by dividing the number of traded put options by the number of traded call options. Due to its simplicity, it is one of the most common ratios used by brokers and investors to assess whether to invest in a market or stock.

Examples of options data include information on the price, volume, and open interest of various options contracts, as well as details about the strike price, expiration date, and implied volatility. Options data is used by traders and investors to analyze market trends, identify trading opportunities, and make informed decisions in options trading. In this page, you’ll find the best data sources for options data, options databases, and options data providers, including stock options data.

Types of Options Data

There are different types of options data available to buy.

End-of-day data

End-of-day options data are datasets which are updated at the end of the market day. These datasets contain information about all the options on the market in at the end of that specific market day and are useful when looking at options intelligence as a whole but do not provide real-time insights and analytics.

Intraday options data

Intraday options data are datasets which are updated over the course of the working day at regular and routine intervals. These intervals change depending on the dataset you have accessed, for example you could have a dataset which provides updated options data every 5 minutes.

Real-time options data

Another type of options data which is available to buy is real-time data. These databases provide real-time options data intelligence and can be useful for people looking to know the most up-to-date options prices. Each different type of options data has many uses for traders and brokers depending on their personal needs. They can use these options insights and intelligence to ensure they are making the very best trading decisions and with the hope of generating as much profit as possible. The stock and options market are both notoriously volatile, so it is understandable that traders would want to be as well informed when it comes to their trading decisions as possible.

Each different type of options data has many uses for traders and brokers depending on their personal needs. They can use these options insights and intelligence to ensure they are making the very best trading decisions and with the hope of generating as much profit as possible. The stock and options market are both notoriously volatile, so it is understandable that traders would want to be as well informed when it comes to their trading decisions as possible.

Common Attributes

Options data comes with various attributes that make it useful. These attributes include, but are not limited to: stocks, quotes, numbers, price points, issues with prices, and market statistics. There are often additional attributes that are added depending on the specific use of the data being collected and where it is being collected from. For example: options data for traders would include the stock prices and fluctuations. This then helps them make a better buying or selling decision based on the price points for that particular stock or bond.

Options Data Uses

The options data that is collected can be used by stock brokers and traders who are looking to change or optimize their trading strategies. They can use this information as a guide to make trades in the future, by creating predictive models and charts. The data can show how the future value of specific stocks may change. Since the stock and bond market is constantly changing, the data collected specifically from this information source is compliled and used for brokers to generate alpha and reduce their losses.

Options datasets work by providing meaningful insights into the movement of the underlying security. But, as options data points tend to show a very high level of volatility in a very short period of time, this data needs to be correctly analyzed with the right indicators to provide worthwhile insights. When used correctly, options data intelligence can provide key pointers to investors as to the best stocks to invest in and because of this experienced traders and investors have been using these datasets for a long time in both short-term trading and long-term investments.

How can a user assess the quality of Options Data?

The quality of options data is assessed through the information that is presented. Accuracy can be can be verified by comparing the stock prices in one dataset to another source, and checking whether they’re consistent. Use reputable stock exchange data sources, like Bloomberg, to benchmark your dataset against their expert market calculations. Watching for inconsistencies in any dataset is important to get the best and most accurate data collected.

Due to the constant fluctuation in the pricing of options on the stock market, it is important to find options datasets and APIs which have the most up-to-date data that is constantly updated with the latest options prices. Without this, traders would find it hard to base their investing decisions around the latest intelligence. However, a good quality options database will also include historical options insights. By having a historical overview of the different options prices, traders can best evaluate the state of the market and determine where are the best places for them to invest their money or buy stocks.

Options Datasets Pricing

Like many different datasets, the amount of information available in an options dataset or API can vary widely depending on the use case of the dataset. Options databases which contain a lot of historical options data will have a higher price than other options datasets due to the vast amount of data they contain. Additionally, because the collection of options data and preparation of options datasets can require a lot of analysis, it is likely that options datasets will cost more than datasets which contain raw data alone. When it comes to using options data, traders want the most complete and well-analyzed information available and for this raw options data needs to be deeply analyzed to highlight areas, like less obvious trends and patterns.