SGG Research has opened early access to Earnings Call Participation Network and Dynamics (ECPND), an alternative data factor for US equity research. The service delivers timestamped, versioned scores through an authenticated API, allowing quantitative researchers and investment teams to evaluate participation information within their own models and portfolio processes.
The launch connects three parts of the research programme: a daily factor dataset, a public study of its historical contribution and a delivery service for ongoing use. Researchers can begin with a free sample of two years of daily historical scores, ending eight weeks before the package date, before deciding whether to subscribe to current data.
A different observation from the earnings call
Earnings calls record both what a company says and which external professionals choose to engage with it. Analysts bring sector knowledge, company coverage and research priorities to those discussions. Their participation can reflect work and expectations formed before the call. Recurring participants also connect companies, creating a history of attention that extends beyond a single quarterly event.
ECPND turns that participation history into a bounded research score. The underlying network evolves as further eligible observations become available, so a company can have a current score even on a day when it has no new call. The score is designed to complement an existing equity-research process; it is not a probability of a price increase or a predicted return.
A published comparison with the baseline held constant
The ECPND whitepaper evaluates weekly US equity portfolios formed from the same Qlib / LightGBM predictions, with and without the participation factor. Capital, execution rules and trading costs are shared. The study covers 245 weekly starting dates from January 2022 to September 2026, four fixed model seeds, and both buy & hold and weekly rebalancing. Each reported holding period includes only completed formations.
For buy & hold, the primary comparison records mean paired return differences of +17 basis points over three months, +54 over six months and +107 over twelve months, after the stated cost of 10 basis points per executed trade. The six-month 95% block-bootstrap interval is +13 to +99 basis points; the three- and twelve-month intervals include zero. Weekly portfolios overlap, and these are SGG Research's historical calculations under the disclosed assumptions, not an independently audited result or a live investment track record.
The paper sets out the baseline, timing convention, portfolio rules and sensitivity checks so readers can assess what the comparison does and does not establish. The free research package includes historical scores, study results, cohort comparisons and a worked selection example. Its two-year score sample supports evaluation over those supplied dates; it does not reproduce the entire study window by itself.
Ongoing data for existing research workflows
The API provides a current score set with observation and publication information and version identifiers. Hourly checks look for relevant changes and publish updated data when required. The checking frequency describes data maintenance; it does not prescribe an hourly trading strategy. Customers can retrieve the dataset on a schedule suited to their own decision process.
ECPND early access is priced at USD 1,850 per month, billed quarterly at USD 5,550 plus applicable taxes. Coverage, permitted use and subscription terms are set out on the product and terms pages. The service supplies factor data and analytics for internal research, with API documentation and integration support.
Continuing the research beyond the historical study
SGG Research is also recording prospective ECPND portfolio decisions and subsequent outcomes through its forward-testing process. That record is at an early stage and is kept separate from the historical results. Further work examines selection strength, portfolio exposures and implementation assumptions, alongside the separate ECQDI text factor and research into combining the two inputs.
The aim of early access is to make a documented research input available for testing in other models and workflows. The published history provides a reason to investigate the factor; the customer's own universe, costs and portfolio design determine how it should be evaluated.
About SGG Research
SGG Research develops alternative data factors for US equity research. Its work examines who participates in earnings calls, how connections evolve across companies, and the quantitative content of external analyst contributions. SGG Research delivers versioned factor scores, historical datasets and documented studies for independent evaluation in customers' own models and workflows. Its products are data analytics and research services, not financial advice.
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