Earnings calls are full of signals investors can miss. Our new Transcripts AI Model uses advanced AI to analyze management commentary and Q&A, helping investors identify differentiated alpha across global markets. Read the white paper: tinyurl.com/3k3f63uc

When should a factor carry more weight? Our new Factor Timing research explores whether changing market conditions can help forecast the relative performance of individual factors. Read more: tinyurl.com/2zwrjp4j

ICYMI, A-Team Insight covered the launch of our Transcripts AI Model, including its predictive performance, 90-day horizon, limited post-earnings decay, and how investors should evaluate AI-driven research. Read the article: tinyurl.com/yc36s5hr

Does AI introduce look-ahead bias? We tested TAIM against point-in-time ChronoBERT models and found no significant performance difference. Request the paper: tinyurl.com/5n7upnpk

ExtractAlpha has been named Best Data Provider to the Buy-Side in the Data Management Insight Awards USA 2026. Proud of the team behind the research, data and signals that earned this recognition.

Markets evolve. Factor weights should too. Our latest research explores dynamic signal weighting using market regimes and crowding indicators. Read the research: tinyurl.com/bdhkfpkp

Factor crowding can quietly erode alpha. Our latest research explores how stock-level crowding indicators can help identify vulnerable signals before they become a drag on performance. Read the research: tinyurl.com/ywrva4mz

New research from ExtractAlpha: See how the Transcripts AI Model transforms earnings call transcripts into differentiated alpha signals using advanced AI. Download the white paper: tinyurl.com/939sp99j

AI isn't just changing investment research. It's changing what investors expect from the firms building AI models. How much transparency is enough to trust an AI-driven investment signal? Our CEO, Vinesh Jha, shares his perspective with A-Team Insight: tinyurl.com/yc36s5hr

AI has changed how investment signals are built. It hasn't changed how they should be evaluated. @ATeamInsight spoke with ExtractAlpha Founder & CEO Vinesh Jha about transparency, signal crowding, validation, and trust in AI-driven investing. Read post: tinyurl.com/yc36s5hr

Most transcript signals focus on sentiment. The new Transcripts AI Model uses advanced AI to identify predictive language patterns from English and Japanese earnings call transcripts. See our announcement: tinyurl.com/mry4fuej

Not all signals deserve the same weight. New research from ExtractAlpha shows how regime classification and factor crowding can improve signal aggregation and portfolio resilience. Read more: tinyurl.com/3dkb7t5t

The SEC wants to reduce quarterly reporting. Our research suggests the market may already be looking beyond the current quarter. We found that out-quarter estimates have become increasingly valuable signals. Read the research note: tinyurl.com/3fvvf2cm

Our latest research shows that out-quarter earnings revisions have become increasingly valuable signals for systematic investors. If your models still focus primarily on FQ1 estimates, it may be time to look further ahead. Download the research note: tinyurl.com/2hta22mf

What if employees know before investors? Changes in management quality, culture, retention often occur long before they appear in earnings results. The new signal transforms workforce intelligence into a predictive stock-selection signal: tinyurl.com/4rmck2nu

Some of the most important signals about a company's future performance never appear in financial statements, they appear inside the organization. Explore our new Japan Employee Sentiment Signal by requesting the white paper: tinyurl.com/2tz2s44z

We're finding faster ways to turn data into investment decisions. Read about why ExtractAlpha was recently recognized as @TradingTechIns Best Alternative Data Integration Platform: tinyurl.com/29x9szc2

Consensus forms faster than ever. A new dataset appears. Capital flows in. Backtests look great. Then the edge compresses. Alternative data alone is no longer enough. The advantage belongs to firms building signals that remain difficult to crowd: tinyurl.com/vk7te98f

Honored to be recognized as Best Alternative Data Provider at the 2026 @WatersTech Asia Awards. This award reflects the work of an exceptional team and the continued support of our clients and partners around the world. hubs.li/Q04jDmb_0

The market isn’t short on data. It’s short on differentiated interpretation. We focus on turning noisy alternative data into investable signals designed for institutional workflows. Reach out to evaluate differentiated signals: tinyurl.com/2tr9f3da #Quant #AltData #Alpha