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InTraCoM presents at "AI, Machine Learning and Sentiment Analysis Applied to Finance"- con

About the conferfence:

Artificial Intelligence is deemed to be the main driver of the 4th Industrial Revolution. Investment in AI has grown at a phenomenal rate with companies investing $26-39bn in 2016. Adoption in 2017, however, remains low. As a result, this has spurred companies from every industry to seize the trend and innovate – from virtual assistants to cyber security to fraud detection and much more. The majority of C-level executives have identified and agree that AI will have an impact on their industry. However, only 20% of C-level executives admit they have already adopted AI technology in their businesses, according to research conducted by McKinsey. So, there is plenty of scope for change and improvement. The Finance industry is anticipated to lead the way in adoption of AI with a significant projected increase in spending over the next three years.

Until recently, practitioners have faithfully relied upon neo-classical models to measure performance, whether it’s in financial organisations or marketing corporations. AI is the new technology that offers an automated solution to these processes. It has the capability to replicate cognitive decisions made by humans and also remove behavioural bias adherent to humans.

Machine learning and sentiment analysis are specific techniques that are applied in AI. These techniques are maturing and rapidly proving their value within businesses. In order to process and understand the masses of data out there, machine learning and sentiment analysis have become essential methods that open the gateway to data analytics. To keep up with the ever-expanding datasets, it is only natural that the techniques and methods with which to analyse them must also improve and update.

InTraCoM's presentation (Andreas Zagos) refers to patent related approaches:

How to measure intangible assets – the missing factor for value investing Intangible assets cover up to 84% of the company value in tech companies. The question is how to measure the intangible assets, namely patents and utiliy models. Intracom will present their indicator based approach on pattern recognition on big data for determining monetary values of patent portfolios – the “IP value factor”. The monetary value was used for backtests on different indexes and the results of those tests will be presented. The “IP value factor” is uncorrelated and generates alpha in sector neutral backtests.

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