Predictive
New Bloomberg study finds demand for election-related alt data
In a survey conducted with Coalition Greenwich, the data giant revealed a strong desire among asset managers, economists and analysts for more alternative data from the burgeoning prediction markets.
Messy MBSs? Startup uses deep learning to predict mortgage-backed securities markets
As interest rates rise and house prices fall after a steady period of the opposite dynamic, investors are looking for more accurate ways to price these factors into the value of mortgage-backed securities.
FactSet blends ML, NLP for predictive data analysis
The vendor is drawing on its vast collection of data to develop predictive signals for credit ratings, shareholder activism and more.
Academics use granular data for futures market predictions
Researchers at NYU’s Courant Institute of Mathematical Sciences are using granular futures data from BMLL for research on less-covered futures markets.
In the world of financial data, context—not content—is the new king
For years, the mantra of the market data world has been ‘content is king.’ But with trading strategies now more dependent on being able to see the big picture, the value of context could quickly overtake the data itself.
Waters Wrap: Mid-tier market data providers look to reinvent themselves
Anthony loves when his opinions spark debate. Following responses to a recent column on consolidation among mid-market data technology vendors, he provides something of a case study, which looks at how Exegy is evolving after its acquisition of Vela.
Charles River, Wave Labs team up for enhanced OEMS
The strategic partnership will involve a three-part integration including system connectivity, combined visualization and the creation of client feedback loops.
Dutch asset manager turns to decision trees for currency predictions
APG has improved prediction accuracy for G10 currency movements after adopting decision tree-based machine learning.
SF quant firm uses 'nearest neighbor' machine learning for equities predictions
Creighton AI is using a regression-based approach to machine learning to help make predictions about the excess return of a stock relative to the market.
Brown Brothers Harriman continues AI ‘transformation’ of fund accounting unit
A new tool that helps business users test and validate their own POCs is set to join the bank’s ranks alongside its other AI projects implemented over the last two years: Linc, Guardrail, and Ants.
Quoniam AM turns to machine learning for non-linear stock relationships
The Frankfurt-based asset manager is using machine learning to look at the performance of stocks with low returns, high-growth.
Leveraging Interconnection and the Cloud for Faster, Smarter Business Decisions
How the Covid-19 pandemic accelerated the digital transformation and the move to cloud-based services for capital markets firms, and the extent to which such offerings will continue to find traction across the industry.
PanAgora’s CIO & head of sustainable investing explain firm’s ESG framework, best practices
Waters Wavelength Podcast Interview Series: PanAgora’s George Mussalli and Mike Chen hit on topics including building predictive models using point-in-time data, and balancing ESG portfolios.
BlackRock looks to predictive ESG data, rather than point-in-time
Mary-Catherine Lader says that the asset manager is building out new modeling tools to help users better understand how the decisions a company makes today can affect their performance in the future.
Arabesque AI to Launch New Prediction Engine Using Machine Learning
The firm is working with different machine-learning methods for portfolio construction, and expects its AI system to go live early next year.
MarketAxess Eyes Predictive Capabilities for Fixed Income Liquidity
The trading platform is working to develop its pre-trade automation capabilities to predict a bond’s likelihood of execution, and helping buy-side clients navigate fixed income trading protocols.
Waters Wrap: The M&A Market Heats Up (And Some Quantum Computing News)
What do Liquidnet and Trading Technologies (and others) have in common? Anthony explains. He also discusses advancement—and disillusionment—in the quantum space.
On Democracy and Alt Data's Democratization: Preparing For the US Election
Advancements in modeling and the rise of alt data have made the process of prepping for the US presidential election more complex, but hopefully more accurate.
Clearwater Analytics to Roll Out New Performance, Risk Modules for Flagship Platform
The modules, which use machine learning to derive predictive insights, are scheduled to go live in Q1 2021.
UBS Evidence Lab Uses Hospital Data to Profile Regional Recoveries
The unit is combining foot-traffic data and proprietary datasets derived from hospitals to develop a better understanding of outbreaks and predict a timeline for recovery.
Wavelength Podcast Ep. 207: Vaccine Tracking and Other Alt Datasets
Wei-Shen and Tony talk about alt datasets relating to the pandemic.