Hedge Funds / Asset Managers / Institutional Investors
machineByte data & research is used by buyside firms – hedge funds, asset managers, pension funds, insurers and other institutional investors who are either not yet active in machine learning and alternative data, are seeking peer-based case studies and approaches, or are looking to further expand their expertise and use of AI techniques. machineByte data & research provides users with a blueprint to the current approach by buysiders to machine learning and alternative data and what best practices are already being adopted by peers.
Alternative Data Companies
For alternative data companies, machineByte data & research provides a landscape for how buyside firms are approaching alternative data – what data are they buying vs. exploring, how much budget they are allocating to alternative data, what analysis on alternative data they are doing internally, how they are/seeking to leverage alternative data in specific asset classes, portfolios & strategies, etc. machineByte data & research covers a wide range of datasets being used or explored by buyside firms, including market indicators, social media, web, ESG, satellite, shipping, geo-location and corporate action data, among other areas. From machineByte data & research, alternative data companies will also find content and feedback from buyside investors on what areas of alternative data they would like explored and delivered for portfolio management purposes over the next 12 months.
Traditional Data Companies
Traditional data companies are increasingly exploring machine learning techniques across their services and offerings. One recent example includes Bloomberg, which has implemented NLP to facilitate investment decisions based on correlations between a company’s stock price and news. machineByte data & research will allow traditional data companies to identify solutions and improvements to their current offerings that meet the demands of buyside clients across asset classes and markets.
Machine Learning Platforms
The adoption of AutoML platforms among buyside firms is low – there is a preference among portfolio managers to use internal tools, hire data scientists or bypass such platforms. Yet, a lack of adoption of AutoML is based on a lack of penetration from platform providers into portfolio management – from discussions with asset managers and institutional investors, portfolio managers not proficient in data science are exploring how to use these platforms to build, train and deploy machine learning models. Those firms running and operating AutoML platforms will use machineByte data & research to identify the opportunities for AutoML in asset management.
From alternative data offered by banks to quantitative research and systematic solutions, machineByte data & research identifies the areas in which buyside firms find opportunities in trading and investments, across asset classes and markets. Investment banks use machineByte data & research to identify types of research that are being demanded by portfolio managers, areas of opportunities for investment solutions that leverage machine learning and alternative data, and how clients judge banks’ alternative data offerings.
Other Service Providers
machineByte data & research provides insight on a number of areas that feed in to product development, idea generation, training and certification opportunities and even industry documentation. Those firms that will find such data and information crucial to best serving their buyside and technology clients, include:
Index Providers ¦ Exchanges ¦ Law Firms ¦ Accountancy Companies ¦ Trade Associations & More!
To contact machineByte’s head of research, data and consulting, please email Pat Fay: pat@machineByte.com.
For reports, bespoke data and research, please contact Chas Reese: chas@machineByte.com.Click here to purchase