Sold by: Brain
Deployed on AWS
Brain Machine Learning proprietary platform is exploited to generate a daily stock ranking based on the **predicted future returns for the following 10 trading days** for a universe of the largest 1000 US stocks.
The model implements a voting scheme of machine learning classifiers that non linearly combine a variety of features with a series of techniques aimed at mitigating the well-known overfitting problem for financial data with a low signal to noise ratio.
Overview
Brain Machine Learning Stock Ranking for Next 10 Days (Live Feed)
Overview
Brain Machine Learning proprietary platform is exploited to generate a daily stock ranking based on the predicted future returns for the following 10 trading days for a universe of the largest 1000 US stocks. The model implements a voting scheme of machine learning classifiers that non linearly combine a variety of features with a series of techniques aimed at mitigating the well-known overfitting problem for financial data with a low signal to noise ratio.
Live Data
The dataset provides a daily feed updated each day within 06:00 AM UTC.
Each revision contains only the latest updated data for the next 10 days prediction time horizon.
Historical Data
The historical data can be obtained for testing purposes by following one of these methods:
- by downloading previous revisions
- by contacting us to at support@braincompany.co
- by subscribing to the free trial product Brain Machine Learning Stock Ranking (History Trial) . Please note that here all time prediction horizons are included for testing while in the live feed only a specific time horizon is included.
Highlights
- Enhance quantitative models and long short strategies by adding a multi-factor ranking that non-linearly combines stock specific market data (price, volume, fundamentals) with market regimes indicators and calendar anomalies using advanced Machine Learning techniques.
- Rely on a robust Machine Learning approach that incorporates a series of techniques to mitigate the overfitting problem that often plagues financial data with a low signal to noise ratio. The model uses a dynamic universe that is rebalanced each year to avoid survivorship bias.
- Discover signal value and explore model data with free trial access to approximately 10 years of daily rankings history.
Feed Details
Brain Machine Learning Stock Rankings are generated daily and based on the predicted future returns of a dynamic universe of the largest 1000 US stocks for the following 10 trading days. The universe is updated yearly.
Model inputs include stock specific features such as fundamentals and price-volume related metrics, market data such as volatility and other financial stress indicators, and calendar related signals such as day or month anomalies.
Disclaimer
The content of this dataset is not to be intended as investment advice. The material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provvaluee investment advisory or other services by Brain. Brain makes no guarantees regarding the accuracy and completeness of the information expressed in the dataset.
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
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Dimension | Description | Cost/month |
|---|---|---|
Product Access | Dimension that grants access to the product for subscribers. | $1,700.00 |
Dimensions summary
This listing uses a single contract-based dimension called Product Access (Units). You buy access to the product for a fixed term, rather than paying per query or per volume of usage. There are no tiers, instance sizes, or usage add-ons to choose between. Access delivers a daily stock ranking based on predicted returns for large US and European stocks across multiple time horizons. The data arrives with daily frequency through a dedicated S3 bucket. Because one dimension governs pricing, your cost does not scale with data volume within the contract term.
Top-of-mind questions for buyers
One unit grants subscriber access to the daily stock ranking dataset. You receive predicted-return rankings for the largest US and European stocks across multiple time horizons: 2, 3, 5, 10, and 21 days. The rankings update daily and cover a stock universe refreshed each year.
The data arrives at daily frequency through a dedicated S3 bucket assigned to you. More than 10 years of history are available for testing. You retrieve files from that bucket rather than calling a metered API, so delivery does not add a separate usage charge.
No. This listing uses one contract dimension, so cost does not scale with how often you download files or how many stocks you analyze. Access covers the full ranking universe for your term. You pay for access, not per query or per data volume.
braincompany.co
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Vendor refund policy
No refunds are offered for this product, for more information please contact us at support@braincompany.co
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Additional details
You will receive access to the following data sets.
Data set name | Type | Historical revisions | Future revisions | Sensitive information | Data dictionaries | Data samples |
|---|---|---|---|---|---|---|
Brain Machine Learning Stock Ranking for Next 10 Days (Live Feed) | All historical revisions | All future revisions | Not included | Not included |
Resources
Vendor resources
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