Buy Implied Volatility Data
FinPricing Precious Metal Implied Volatility - Implied Volatility Data (USA & Australia)
FinPricing FX Implied Volatility Surface Data - Forex Data (Global)
FinPricing Cap Implied Volatility Surface Data Feed API - USA, Canada, Europe, Japan
FinPricing Swaption Implied Volatility Surface Data - USA, Europe, Australia
The Ultimate Guide to Implied Volatility Data 2021
What is Implied Volatility Data?
Implied volatility data is information about the market’s prediction of certain security’s value. The information is based on a metric that predicts the future fluctuation of the price of the security. Implied volatility does not forecast the direction in which the price change will progress. An example of this is if the security has high volatility, the price may shift upwards or downward drastically. It doesn’t always go upward. On the other hand, low volatility security won’t make any significant movement. Implied volatility data is useful in analyzing the possible movement of security.
What is Historical Volatility vs Implied Volatility?
While ‘volatility’ simply refers to a metric that measures the weight of the change in prices in a security, it can be further broken down into implied volatility and historical volatility. As the name suggests, implied volatility is a projected metric that is applied by options traders to determine probability. It applies the core facets of demand and supply to highlight the projected changes of an underlying stock within a given period of time.
On the other hand, for historical volatility, traders speculate the probable price changes of options by analyzing past trading ranges of securities and indexes. In this case, calculations for historical volatility are intrinsically based on the shifts from one closing price to the next for a given option. For the purpose of historical volatility data analysis, traders buy historical volatility data from data providers, where they shop for historical volatility data and use it to analyze previous price fluctuations of options and projecting future price changes based on these trends.
How is Implied Volatility Data collected?
Implied volatility data is gathered through different sources. These sources include online websites, trading platforms, stock markets, brokers, securities and exchange, and stock owners. These sources are scrutinized, as they provide different information based on the type of securities they’re concerned with. This information may be in the form of graphs, charts, statistics, preferences, and ownership analysis. Then data providers compile the data to become datasets and put them in data repositories.
Where do traders find Implied Volatility Data?
Investors find implied volatility data for given stocks either from financial news websites or from online data brokerage firms. These online data brokerage firms sell implied volatility data by providing information about the stock that could be listed on their platforms of databases. The providers offer the stocks’ present price range and give the number of days that are left until the forecast price comes to effect. Through subscription to financial data services, traders purchase implied volatility data from these online-based data providers.
How is Implied Volatility calculated?
Since implied volatility is an estimation, arriving at this estimation requires the ‘Black-Scholes model’, a method of price forecasting that is made up of the following key components:
• The market price of the option
• The underlying stock price
• The strike price
• The time of expiration
• The risk-free interest rate.
Given these core parameters, implied volatility is calculated by pulling the market price of an option, entering it into the Black-Scholes formula, and estimating the value of the volatility.
For investors, this estimation can be complex and time-consuming. As a solution, commercial data providers of options data carry out these necessary implied volatility calculations for given options and sell this data to investors to download
What are the typical attributes of Implied Volatility Data?
Implied volatility data is composed of a comprehensive list of attributes. Here are some common attributes of implied volatility data:
· Trading attributes: this refers to trading activities regarding a particular security.
· Price attributes: this refers to the price of the product – historical and current, as well as its availability in the stock market.
· Supply/Demand attributes: this refers to the available supply and demand of the security.
What is Forex Implied Volatility Data?
Foreign exchange (currency) implied volatility refers to the constant movement and changes in exchange rates in the world’s global foreign exchange market. This implied volatility can result in large losses or gains in the forex market and is considered the main cause of foreign currency risks. As far as the corporate world is concerned, forex implied volatility is often interpreted as the biggest credit risk that ought to be controlled with caution for the purpose of cushioning a company’s intrinsic value. The factors that have a direct bearing on this volatility range from inflation levels, interest rates fluctuations, geopolitical and socioeconomic stability, levels of imports and exports and a country’s monetary and fiscal policy.
What is Implied Volatility Data used for?
Implied volatility data is beneficial to investors and traders. This data helps them gain insights about the value of a security in the stock market. They also use this to optimize their portfolio and to increase profit based on the prediction of the market. This data also helps traders and investors in their trading strategies. Due to the practicality of this data, having an implied volatility data is a valuable tool for traders and investors.
What is SPY Implied Volatility Data?
SPY implied volatility data refers to information about the unpredictable movement in the price of SPDR S&P 500 Trust ETF, also referred to as the SPY ETF. SPDR S&P 500 is a popular fund that tracks the Standard & Poor’s 500 index, which is made up of 500 large and mid-cap United States stocks. The SPY is a diverse pool of assets, which distributes most of its funds into varying sectors of the economy such as information technology, healthcare, financial services, telecommunication services, consumer defense and real estate.
What is a Volatility screener/finder?
One of the biggest hurdles that investors face on a daily basis is the amount of work that is put into screening the large volume of companies trading on SEM in an effort to find the best stocks to buy or sell. It is a demanding task to sort out information that is considered useful from the masses of irrelevant data available on the internet. The same can be said about volatility data. However, a stock volatility screener is an important tool that helps investors to focus their efforts on stocks that matter in terms of meeting the right standards and suiting a trader’s strategy. Volatility screeners are critical filters which come in handy for an investor who has a specific idea of the type of companies they wish to invest in.
Can I buy an Implied Volatility Data feed?
Yes, it is possible to buy an implied volatility data feed, just as you can buy commercial implied volatility databases: from data vendors. Implied volatility data vendors provide data feeds on a daily basis for volatility surfaces for FX options that comprise of skew, that are distributed across major global currencies. Based on the delivery frequency, data frequency, reporting lag, history, coverage and availability, the cost of implied volatility data is determined. Data users can choose a pricing model for the data feed which works for them, depending on whether they want a volatility data subscription service, or would prefer to purchase the volatility data on a one time basis. It is also possible for a customer to purchase historical or real-time implied volatility data depending on their use case, and the data provided by the data vendor in question.
How can a user assess the quality of Implied Volatility Data?
The best quality implied volatility data has the following quality aspects. Implied volatility data should be:
Applicable: this refers to the applicability of data to serve the purpose of providing information on the type of questions the users want to be answered.
Timeliness: this refers to real-time data of implied volatility. The data must be accurate, free from error, and updated regularly.
Reliable: for implied volatility data to be high quality, it needs to come from credible sources. These sources must be verified and validated by certified financial market authorities.
Who are the best Implied Volatility Data providers?
Finding the right Implied Volatility Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular Implied Volatility Data providers that you might want to buy Implied Volatility Data from are FinPricing, Quandl, CME Group, Option Metrics, and ORATS.
Where can I buy Implied Volatility Data?
Data providers and vendors listed on Datarade sell Implied Volatility Data products and samples. Popular Implied Volatility Data products and datasets available on our platform are FinPricing Precious Metal Implied Volatility - Implied Volatility Data (USA & Australia) by FinPricing, FinPricing FX Implied Volatility Surface Data - Forex Data (Global) by FinPricing, and FinPricing Cap Implied Volatility Surface Data Feed API - USA, Canada, Europe, Japan by FinPricing.
How can I get Implied Volatility Data?
You can get Implied Volatility Data via a range of delivery methods - the right one for you depends on your use case. For example, historical Implied Volatility 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 Implied Volatility Data APIs, feeds and streams to download the most up-to-date intelligence.
What are similar data types to Implied Volatility Data?
Implied Volatility Data is similar to Stock Market Data, Alternative Data, ESG Data, Merger & Acquisition Data, and Proprietary Market Data. These data categories are commonly used for Portfolio Valuation.
What are the most common use cases for Implied Volatility Data?
The top use cases for Implied Volatility Data are Portfolio Valuation.