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How QuantumStreet AI Tackles the Journey From Signal to Portfolio

AI is becoming increasingly sophisticated at identifying patterns and generating investment signals from disparate sources of financial and market data. But for systematic investors, those signals still have to be converted into something much more concrete: a portfolio that determines which assets to hold, in what proportions, and with what degree of conviction. Doing that…

Moving Up the Value Chain: 3AI on AI, Alternative Data and Investment Intelligence

Traditional financial and market information now sits alongside news, sentiment, analyst estimates and a growing universe of alternative datasets, creating an increasingly rich information environment for investment firms. But access to more data doesn’t necessarily translate into better investment decisions. Firms still have to establish which information has genuine predictive value, turn disparate datasets into…

Beyond the API: FactSet on Making Financial Data Ready for Agentic AI

The effectiveness of an AI agent ultimately depends on the quality, context and structure of the information it can access. For investment firms, that puts familiar challenges around data quality, provenance and integration firmly back on the agenda – while potentially changing what they expect from their data providers. “When you’re selling data, you’re not…

Bridgewise and the Expanding Universe of Sentiment Data

Investment firms today face a growing challenge with alternative data: how to turn an ever-expanding universe of unstructured content into something that can be analysed systematically. Social media, news articles, disclosure documents and, increasingly, podcasts can all contain information relevant to investment decisions. But before that material can be useful to quantitative or discretionary investors,…

Alternative Data in Capital Markets Handbook 2026

Alternative data adoption in capital markets has moved into a more disciplined phase. Simply possessing a dataset is no longer a differentiator – the priority now is how data is sourced, synthesised and deployed, and how quickly granular, disaggregated signals can be turned into validated, decision-ready insight. The 2026 edition of the Alternative Data in…

What a $3bn YipitData Valuation Says About the Value of Alternative Data

Carlyle-backed YipitData is reportedly exploring a sale that could value the alternative data and analytics provider at between $2.5 billion and $3 billion, offering a useful indication of how investors are valuing proprietary data assets as artificial intelligence reshapes the information industry. The prospective sale comes as the rapid development of AI is prompting investors…

Rethinking Alternative Data Infrastructure with Aerospike

Investment firms have never had access to more data. From corporate filings and social media to satellite imagery, transaction data and other alternative sources, the range of information that can potentially feed the investment process continues to expand. But as AI becomes embedded more deeply into research and investment workflows, the challenge is shifting. Simply…

How EventVestor Puts Alternative Data in Context

For investment firms looking to extract signals from alternative data, finding an interesting dataset is only part of the challenge. Moving that data from research into production brings a different set of requirements around quality, timeliness, consistency and historical accuracy. Those requirements are particularly important for quantitative investment firms, where apparently small discrepancies in timestamps,…

Facteus Expands Data Coverage with a Focus on Signal Continuity

As alternative data becomes more deeply embedded in investment research and quantitative models, the quality of a dataset is increasingly about more than its size. Coverage and granularity remain important, but so too does the ability to maintain a consistent, representative signal as underlying data sources and panels evolve. That challenge is central to the…

Multiplying the Value of Unstructured Data

Financial institutions have spent years expanding the range of data available to investment, trading and risk teams. Increasingly, however, the challenge is not obtaining more data but making sense of what they already have. Unstructured data is estimated to account for 80-90% of the information generated withinfinancial institutions, encompassing everything from regulatory filings and earnings-call…