Sentiment Analysis

>>Sentiment Analysis
Sentiment Analysis 2018-08-29T12:18:38+00:00

OptiRisk has conducted extensive research in the field of Sentiment Analysis in general and News Sentiment Analysis in particular. Our sentiment analysis is predominantly focused on the applications in the Banking Financial Services and Insurance (BFSI) sector.

There have been many technical White Papers several research papers in peer reviewed Journals. Noteworthy are two major publications The Handbook of News Analytics in Finance (2011) and  Handbook of Sentiment Analysis in Finance  (2016).

A major application of our Sentiment Analysis is in the generation of trading signals using sentiment meta data, risk analytics and predictive analytics.

Sentiment analysis in finance
SES

Background: The investment industry manages funds in excess of $60tn globally. Managers of ‘Active’ funds seek to deliver a return in excess of the broad market and charge fees of 0.3- 1.0% per annum, whereas ‘passive’ funds use models which track indices and carry much lower fees. In recent years, there has been a trend towards designing hybrid ‘enhanced index’ or ‘index-plus’ funds with a similar cost to index-trackers, but with some of the upside potential of the active funds.

To date alternative strategies have either used popular portfolio construction methods with oversimplified risk models (mean variance optimization on tracking error), or have used more sophisticated risk models (simulation-based) but have had to adopt weaker portfolio construction methods.

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SES

SENRISK is an EU-funded project that aims at developing a credit risk assessment tool, in which sentiments of news, social media and reports are included in the risk assessment of corporate and sovereign bonds. Sovereign debt is monitored enabling small and medium-sized investors to determine internal country and company ratings. Our tool investigates all current country and company information and market sentiment as well as historical time series to enable a quantitative as well as qualitative analysis of bonds’ inherent risk.

Key facts:

  • Duration: 24 months (Workpackage/Tasks List)
  • Project Cost: 1.414.040 €

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