Machine learning shows promise in grouping assets better and predicting regime shifts, say fund managers.
BlackRock, MSCI, and La Française are some of the firms looking to replace traditional, linear risk models.
The quant firm’s Seth Weingram lays out his principles for the effective use of machine learning.
Machine learning can tell stories from large datasets to drive alpha, say quants.
Simonian, formerly head of quantitative research at Natixis, will produce research and advise for clients.
Buy-siders have limited their usage of deep learning techniques due to haziness over their inner workings.
For over 50 years, modern asset management has been guided by the Capital Asset Pricing Model and the theories of Harry Markowitz. Yet, a father-and-son team in Boston says it’s wrong—and they can prove it.
Firms are using machine learning and natural-language processing tools—no longer to grab an edge, but merely to remain competitive.
Waters examines some of the most important events in financial technology of the past 25 years.
Waters speaks with Acadian's CTO about raising the next generation of tech leaders.
The relatively nascent alternative data industry is creating challenges for asset managers, specifically when it comes to a lack of historical data and a lack of talent that can interrogate the data.
Everyone’s excited about the potential untapped alpha promised by “alternative data,” yet those who work with it are far from excited about the prospect of evaluating unwieldy and unstructured datasets. Max Bowie looks at the practical challenges of…
Seiji Ishii will be responsible for driving the index provider’s growth in Japan.
The firm has changed its relationship status with Microsoft Bing, saying that it finds more value in orthodox sources of data, reports Risk.net’s Luke Smolinski.
The perfect data governance strategy is a unicorn, data executives say; yet from setting policies and data quality evaluation to metadata generation, all large financial firms need one. As many firms augment strategy in this area to become more data…
By some estimates, investment in alternative datasets will exceed $7 billion by 2020. At the same time, machine learning and other AI techniques are evolving at a rapid pace. The combination of the two will be significant.
Faye Kilburn investigates quantitative funds' attempts to sift gold from the torrent of alternative datasets.
Boston-based quantitative fund manager Acadian Asset Management’s recently announced partnership with Microsoft will see the firm implement a combination of trading signals received from Microsoft’s Bing Predicts tool with its own predictive analysis to…
The US firm will experiment with Bing’s data, aiming to develop new ways of predicting asset prices.
Linking performance attribution and risk has clear benefits, but fragmented approaches are making it hard for firms to unify processes and underlying data. Clive Davidson outlines the key challenges, and how firms are addressing them.
Quantitative fund manager implements predictive macroeconomic indicators system from Microsoft to boost investment forecasting.
Some firms are seeing benefits in having core platform suppliers manage their data requests, rather than maintaining direct relationships with data vendors.
Good data governance is not about technology
The lesson to be learned from 2015 is that improvements in data governance planning need to continue.