AI is transforming the way traders analyze the stock market. Discover large amounts of data to uncover patterns, trends, and opportunities that may otherwise be unnoticed. However, for these models to provide true value, they need to train on clean, high frequency data. Below we highlight five major vendors that provide key training datasets that enhance today’s AI-driven stock market analysis.
Firstrate data
Firstrate Data is a wide range of financial data vendors offered across multiple asset types, including stocks, ETFs, FX, cryptocurrency, indexes, futures, and options. For stock and ETFs, data is available in both split-only split and dividend adjustment formats. This contrasts with many generic vendors that only provide split-only, tuned data. Dividend adjustment data can be essential if the AI training model is trying to explain small (<3%) price movements.
Optional data is only available at daily intervals, but provides an internal resolution up to a one-minute bar.
tickdata.com
TickData provides the highest resolution time frame for “tick” data, a per-trade sequence. The resolution of this data is very valuable when AI models are examining market microstructures such as temporal imbalances between highly correlated stock tickers and microspikes that last only a few seconds.
TickData offers both transaction data types and citation data types (most vendors focus solely on providing transaction data that has been executed). Adding estimate data is extremely helpful in understanding the more complete situation in the market at any time. It also provides data on illiquid stocks that trade intermittently during trading days but regularly update citations that can infer current market prices.
cbinsights
While many data providers focus solely on pricing data, Cbinsights offers a wealth of contextual data on corporate, industry and market trends. Funding information, acquisition data, technology trend analysis, employment trends, and customer surveys are all included in the CBINSIGHTS product offering. This type of alternative data not only enhances market price data and provides more context for stock price changes, but also helps AI models infer broader trends and opportunities.
alphasense.com
Alphasense focuses on unstructured data and sentiment analysis through natural language processing. The platform summarises and processes millions of text, audio and video documents, including revenue calling, SEC filing, news reports, interviews and stock market analyst reports.
For AI developers, Alphasense offers a large repository of text, audio and video data to train models on financial information. All data is in the public domain and can be used in training without copyright violations.
Additionally, the platform also provides unique data on customer, employee and analyst sentiment.
NASDAQ data link (formerly Quandl)
A NASDAQ data link is actually an aggregation of data sets from multiple “alternative data” vendors. This data covers a very broad spectrum, including credit card spending data, geospatial data, satellite imaging data and transportation data. These datasets focus primarily on providing a broader industrial or macroeconomic perspective. By layering this type of data over market data, AI models can make wider macro connections between individual stocks, as well as predicting stock price behavior under different economic circumstances.
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