Dataset Name: cmind_eps_beat_miss
Group: reference_data
Vendor: Cmind
Data Starts at: 2018-01-01 00:00:00
Symbol Set: US Equities
Asset Class: Equity,ADRs,ETFs
Data Update Time(s): EOD daily
Data Update Frequency: day
Cmind Company EPS beat or miss prediction
The Cmind Earnings-Per-Share (EPS) predictor accurately predicts US company earnings beats and misses a full quarter ahead of the next release using frontier machine learning to extract signals from accounting statements, earnings transcripts, economic variables and consensus EPS.
The Cmind EPS Predictor is unique, accurate and consistent.
About Cmind
We are a team of successful entrepreneurs, AI experts, and accounting and asset management professionals who bring technology and marketing savvy to Cmind.
Cmind combines management commentary, leading-edge accounting principles, and Artificial Intelligence to provide portfolio managers, accountants, and lawyers with unique and timely forecasts of company risks and performance in valuation, credit spreads and sustainability. The Cmind platform identifies financial trends, anomalies, misconduct, societal impacts, and changes in sentiment and other linguistic signals through the fast and efficient analysis of financial statements, regulatory filings, transcripts, news, and industry-specific data. Cmind clients use its proprietary intelligence and insights to drive more informed investment and business decisions.
Data Contained in this Dataset
| Column | Type | Description |
|---|---|---|
| _seq | uint | Internal sequence number used to keep data rows in order |
| timestamp | string | Timestamp of the Data - America/New York Time. |
| muts | uint64 | Microseconds Unix Timestamp. An integer representation of a timestamp with microsecond precision that can be compared directly to other timestamps. |
| symbol | string | Trading Symbol or Ticker |
| CIK | string | Central Index Key |
| Calendar Year | int64 | Current EPS (Earnings Per Share) release - calendar year |
| Calendar Quarter | int64 | Current EPS (Earnings Per Share) release - calendar quarter |
| Prediction Probability | double | Cmind’s Revenue EPS (Earnings Per Share) probability (>0.5 means beat or else means miss) |
| Earnings Release Date | string | EPS (Earnings Per Share) release date |
| EPS Beats Prediction Generated | string | EPS (Earnings Per Share) Beat or Miss prediction generated date |
| Forecast Period | string | EPS (Earnings Per Share) prediction forecast quarter |
| Forecast Period_Year | int64 | EPS (Earnings Per Share) prediction forecast year |
| Forecast Period Earnings Release Date | string | EPS release date for the reporting quarter (Calendar Year, Calendar Quarter+1) |
| Prediction Last Revision Time | string | YYYY-MM-DD HH:MM:SS in EST time zone |
| Prediction Label | int64 | 1 for beat, 0 for miss |
| Prediction Revision History | string | EPS prediction revision history [Array] |
| Name | string | Company name |
| Currency | string | Company’s dominated currency |
| Current eps | double | Company’s current EPS (Earnings Per Share) |
| Current eps_est | double | Company analysts’ average EPS (Earnings Per Share) estimate for the existing quarter |
| Sector | string | Company sector |
| Industry | string | Company industry |
| Market Cap Group | string | Large/Medium/Small group for the company |
| MarketCap | double | Company’s market cap |
| Last Update Time | string | Updated timestamp for the record |
Important Dataset Notes
This dataset is not available for direct online purchase. Please contact sales directly at sales@CloudQuant.com. The data is available through our normal sales department who can provide you with current pricing and a quote for accessing this valuable dataset. This may be due to a number of reasons such as dataset intended use, size of the company (or investment fund) using the dataset, or for simple legal requirements that CloudQuant needs to ensure are in place prior to licensing the dataset to you.