Almax Analytics Delivers Real-Time News Analytics for Capital Markets

by Finance Magnates Staff
  • The fintech firm has utilised AI to deal with information overload in the capital markets.
Almax Analytics Delivers Real-Time News Analytics for Capital Markets
Finance Magnates

Almax Analytics , a software platform delivering actionable insights, today announced that it has emerged from stealth (development) with a customer-ready product for the financial markets. After debuting in January 2016 as an 'Innovative Company to Watch' by KPMG Luxembourg, Almax has quickly built demand and aroused investor interest, thereby closing the seed round in April 2016 to develop this first to market technology.

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Balazs Klemm, founder and Chief Executive, commented: “We are excited to present our product to the market and have worked hard to deliver this technology. On behalf of the company I need to thank our loyal supporters and the Almax team for their commitment and patience. We look forward to growing the business and already engaged in Series A financing discussions.”

Information Overload Solved

Almax Analytics solves the problem of information overload with actionable insights. It does this by putting the content of news into context and running deep analysis across the entire network of affected companies.

The software applies and combines cutting edge technologies of natural language processing (NLP), machine learning, network analysis and data visualisation in a novel way for an existing problem. The technology is easily accessed and deployed through a web-based platform and is subscription based.

Making quick decisions on the basis of earnings reports is common practice, but the window of opportunity to trade on new detailed information that is available in filings and in news is still open.

Peter Sarlin, co-founder and Head of Research, elaborated: “Almax Analytics is taking event-driven trading to a new level by enhancing standard rule-based event extraction engines with data-driven deep learning components. We can see an immense value in directly incorporating our advanced natural language processing engine with our proprietary quant models for automated trading strategies.”

Background

Founded in 2015, Almax Analytics addresses one of the greatest challenges facing capital market practitioners - the feasibility of humans reading and absorbing the sheer quantity of news available. For this reason, many important events and relationships go undiscovered. Almax analytics delivers actionable insights by putting the content of news into context and running deep analysis across the entire network of affected companies.

The analytics output of the Almax Analytics platform is highly valuable as it helps to generate alpha and manage risk and improves trading with efficient intelligence and data gathering.

Categorically falling under the Fintech subsector of artificial intelligence and big data analysis, Almax Analytics offers a 'first to market' solution for traders and asset managers building and executing on strategies across all asset classes.

Almax Analytics , a software platform delivering actionable insights, today announced that it has emerged from stealth (development) with a customer-ready product for the financial markets. After debuting in January 2016 as an 'Innovative Company to Watch' by KPMG Luxembourg, Almax has quickly built demand and aroused investor interest, thereby closing the seed round in April 2016 to develop this first to market technology.

Join the industry leaders at the Finance Magnates London Summit, 14-15 November, 2016. Register here!

Balazs Klemm, founder and Chief Executive, commented: “We are excited to present our product to the market and have worked hard to deliver this technology. On behalf of the company I need to thank our loyal supporters and the Almax team for their commitment and patience. We look forward to growing the business and already engaged in Series A financing discussions.”

Information Overload Solved

Almax Analytics solves the problem of information overload with actionable insights. It does this by putting the content of news into context and running deep analysis across the entire network of affected companies.

The software applies and combines cutting edge technologies of natural language processing (NLP), machine learning, network analysis and data visualisation in a novel way for an existing problem. The technology is easily accessed and deployed through a web-based platform and is subscription based.

Making quick decisions on the basis of earnings reports is common practice, but the window of opportunity to trade on new detailed information that is available in filings and in news is still open.

Peter Sarlin, co-founder and Head of Research, elaborated: “Almax Analytics is taking event-driven trading to a new level by enhancing standard rule-based event extraction engines with data-driven deep learning components. We can see an immense value in directly incorporating our advanced natural language processing engine with our proprietary quant models for automated trading strategies.”

Background

Founded in 2015, Almax Analytics addresses one of the greatest challenges facing capital market practitioners - the feasibility of humans reading and absorbing the sheer quantity of news available. For this reason, many important events and relationships go undiscovered. Almax analytics delivers actionable insights by putting the content of news into context and running deep analysis across the entire network of affected companies.

The analytics output of the Almax Analytics platform is highly valuable as it helps to generate alpha and manage risk and improves trading with efficient intelligence and data gathering.

Categorically falling under the Fintech subsector of artificial intelligence and big data analysis, Almax Analytics offers a 'first to market' solution for traders and asset managers building and executing on strategies across all asset classes.

About the Author: Finance Magnates Staff
Finance Magnates Staff
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About the Author: Finance Magnates Staff
  • 4221 Articles
  • 109 Followers

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