The firm is developing themed asset categories for investors by finding new correlations in alternative datasets.
Many quants contend that you must be able to interpret machine learning in order to use it.
Quants searching for ESG signals have reached very different conclusions. Mostly they blame the data.
The bank's central data and technology group enables frontline ‘citizen developers’.
The vendor believes its planned dashboard of synthetic consumer spend data will help a wider audience on the buy side exploit predictive company revenue data.
The investment bank’s deputy chief digital officer says machines cannot predict markets, as the bank consolidates trading operations and builds an AI trading platform for fixed income and FX.
WatersTechnology looks at 16 projects in the capital markets that involve machine learning to show where the industry is heading.
To get a good deal in fast-moving FX markets, buy-side firms need to know the time. Some of them don’t.
Led by Bryan Cross (pictured), the asset manager's QED team aims to blend quant and fundamental to find unique solutions to new problems.
The investment manager's move to tackle unstructured data is starting with sell-side analyst reports.
Man Group's Gary Collier discusses the hedge fund's strategy of adopting a single platform for its funds.
The crowd-sourced trading platform is looking to create a competitive arena for quants to test their algorithms.
A deep-dive into how capital markets firms are using open-source tools to experiment with machine learning.
The latest big idea in machine learning is to automate the drudge work in model-building for quants
Quants are embracing the idea of ‘model-free’ pricing and deep hedging.
BlackRock, MSCI, and La Française are some of the firms looking to replace traditional, linear risk models.
Investment firms have the upper hand when dealing with expensive data vendors, says Investec’s Nico Smuts.
At Risk Live, executives from Goldman Sachs AM, Societe Generale and Morgan Stanley talked about the benefits and concerns for using alt data.
The quant firm’s Seth Weingram lays out his principles for the effective use of machine learning.
The founder and CEO of Imperative Execution looks at how trade execution is changing and what that means for the buy side.
The bank sees opportunity in providing more in-depth, quantitative data on a larger universe of ESG factors.
These new models sidestep Black-Scholes and could slash hedging costs for some derivatives by up to 80%.
Buy-siders have limited their usage of deep learning techniques due to haziness over their inner workings.