# SGG Research publishes ECQDI study on quantitative patterns in earnings calls | SGG Research

Source: https://sggresearch.com/press/ecqdi-whitepaper

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First whitepaper publication · 29 July 2026

# SGG Research publishes ECQDI study on quantitative patterns in earnings calls

The ECQDI paper introduces a deterministic text factor based on quantitative patterns in external analyst contributions, and shows where this second perspective on earnings calls complements a stock ranking.

SGG Research's ECQDI whitepaper introduces Earnings Call Quantitative Dynamics and Intensity as a separate research input for US equities. The project examines the quantitative character of external analysts' contributions to earnings calls, with earlier calls from the same sector providing context for the measurement.

The rationale is that questions can reflect how analysts test assumptions, interpret reported performance and examine the scale of a company's activities. Those observations differ from the participation history captured by ECPND. They may help a researcher describe an earnings-call discussion in another way, but a plausible interpretation alone does not establish investment usefulness.

The paper frames that usefulness as a portfolio question: what changes when a fixed ECQDI application is added to an otherwise unchanged stock-ranking process? Consistent timing, a common candidate universe and shared costs are essential to that comparison. Different selection strengths and portfolio policies may produce different outcomes, making the application rule part of the research rather than an incidental choice.

Under the same rule as in the ECPND paper, lower priority for the weakest 20% of scores among the most volatile fifth of stocks, ECQDI complemented rankings produced by a model. Averaged across two Qlib models, weekly rebalanced portfolios gained 30 basis points over three months, 87 over six and 195 over twelve, with the twelve-month interval above zero; the contribution is clearest for the Qlib reference model. Applied to a momentum ranking, ECQDI made no measurable contribution, and the paper reports that result alongside the favourable ones. All three SGG Research papers use the same baselines, portfolio rules and costs, so their results can be read side by side. The results are historical; the threshold and the volatility filter were chosen after reviewing them, and a forward evaluation is recording new decisions as they happen.

The paper gives researchers a framework for examining quantitative discussion alongside other equity inputs, including participation history. It keeps the measurement separate from the investment process in which it may be used. ECQDI is a research factor to be evaluated in the user's own models and workflows, not a recommendation to buy or sell securities.

## 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.

[Read the ECQDI whitepaper](https://sggresearch.com/whitepaper/ecqdi-question-intensity)[Get the research package](https://sggresearch.com/#validate-pricing)

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