Blogs

Experts on a recent webinar said that hedge funds and other buy-side trading desks are coping with faster reactions and market reversals in response to data releases and earnings sentiment.

We covered topics such as retail order routing and the debate over payment for order flow (PFOF). We examined the resurgence in alternative trading systems (ATSs), the rise of outsourced trading desks for the buy side, and efforts to regulate fixed-income trading platforms as registered venues.

With everyone seeking up-to-the minute data, analysts and investment managers utilized foot traffic from geolocation data to quantify retail sales and disruptions to the global supply chain. The rise of new marketplaces should remove some of the onerous work of sourcing, collecting, and normalizing data feeds from multiple vendors.

At times like these, two major factors come into play:  first, your trading technology’s ability to process and manage the data coming into the platform, and secondly, how well-established automation is within the firm. 

Fundamental investment managers are mining alternative data, but some worry that the same data sets have been sold to too many people and the strategies may be overcrowded.

Banks and investment firms have increased their consumption of alternative data sets, but there are still challenges around selecting the most relevant data for trading purposes, according to panelists at a recent industry fintech conference.

Asset managers are looking for ways to mine alternative data sets for investment ideas, recognizing that stock pickers cannot rely on traditional research.

The explosion of alternative data sources, such as satellite images, sentiment analysis, and geolocation data, is having a profound impact on the field of quantitative investing. FlexTrade’s Ivy Schmerken investigates.

As hedge funds and quantitative asset managers hunt for unique sources of alpha, Wall Street’s attention is turning to analysis of location data generated by mobile phones. Location data from mobile phones is now at the forefront of the push to combine data science techniques with machine learning techniques to produce actionable information on company fundamentals. FlexTrade’s Ivy Schmerken investigates.

While early movers in the big data analytics industry have mainly been quant hedge funds and systematic fund managers, is the next wave going to come from discretionary fund managers? FlexTrade’s Ivy Schmerken investigates.