OptiRisk Systems UK Division

(Incorporating Indian Division)

Using our Sentiment Enhanced Signals (SES) analytic engine we provide daily trade signals for taking long and short positions in a trading portfolio. We use market sentiment data, together with an advanced prediction infrastructure and a combination of statistical and optimisation models to maximise portfolio returns. Moreover, this strategy monitors and minimizes the dynamic downside risk and consequently controls drawdown.

Key features of SES signals:

• Provides fully automated daily trade signals
• Uses real- time market data and news sentiment data
• Performs predictive analytics based on robust mathematical models
• Consistently beats the performance of major indices
• A dynamic strategy that controls drawdown

FTSE 100: Back testing Results for 2011-2015

• We have also been active in this project. After Victor Zverovich left AMPL Optimization this September, our team has worked closely with AMPL, our business partner. In particular we have worked with Robert Fourer and Felipe Brandao, the new recruits at AMPL to support and enhance their AMPL API and AMPL IDE products.
• In partnership with AMPL Optimisation we have also revised our stochastic programming product that is called AMPLDev_sp. Dr Christian Valente will present this at the INFORMS, Nashville: 13-16 November, 2016.
  Title: AMPL representation and solution of multiple stochastic programming (SP) formulations
  Abstract: Over the last twenty years we have developed stochastic optimisation modelling tools, namely, SPInE and SAMPL which extended AMPL constructs. The implementations involved pre-processing and specialised syntax for SP, CCP and ICCP models. To gain full access to the declarative and procedural features of AMPL, we have now developed templates and frameworks to describe this genre of models. We also present in a summary form FortSP, our SP and ISP solver.

The Knowledge resources include:

• Presentation slides from our leading conference series “Behavioural Models & Sentiment Analysis in Finance” for 3 consecutive years – 2014 (London), 2015 (London) and 2016 (Singapore).
• Recordings of the 2015 conference and webinars.
• A copy of “The Handbook of News Analytics in Finance” and “Handbook of Sentiment Analysis in Finance” (RRP: £95 each).

The Handbook of Sentiment Analysis is now available in an e-book format as well as on multiple online bookstores including Amazon and Alibris.

Endorsement of the Handbook of Sentiment Analysis in Finance by -Professor David J. Hand Emeritus Professor of Mathematics, Imperial College, London Chief Scientific Advisor, Winton Capital Management

‘The technology of extracting financial sentiment from news feeds and other such sources continues to advance. This volume, an update of the earlier Handbook of News Analytics in Finance, describes the current state of the art, illustrating the considerable progress over the past five years. It will provide an indispensible introduction to the area, as well as a comprehensive reference work.’

The price starts at £80: this collection of resources can be ordered as a combination of your choice or purchased as a full bundle for £495. For orders and enquiries, write to us at info@optirisk-systems.com or call us on (+44) 01895 819485.

• Sentiment Analysis Applied to (a) Financial Markets (b) Consumer Markets, Bangalore, India, 8-9 March 2017
• AI, Machine Learning and Sentiment Analysis Applied to Finance, Hong Kong, 14-15 March 2017
• LT- Accelerate, Brussels, 21-22 November 2016.

Dr. Xiang Yu will be presenting on Exploiting Market Sentiment to create Daily Trading Signals. We have created an innovative and dynamic trading strategy for equities where a major contribution of news sentiment is in the prediction of future distributions. Regression analysis on news sentiment and regime switching models are employed to digest market moods and account for changing market situations.

• New Developments in IT and Financial Innovation, London, 14-15 July 2016

OptiRisk systems was a knowledge partner during both- AI, Machine Learning and Sentiment Analysis Applied to Finance and Block chain and Financial Services – conferences organized by UNICOM Seminars in London on July 2016. We also presented our Handbook, along with other products, in the exhibition held alongside the conference.

Tilman Sayer and Xiang Yu of OptiRisk systems presented on the topic, ‘Beating Markowitz with Sentiment and Downside Risk Control.’ They presented a dynamic trading strategy for equity created by us, with particular focus to downside risk. The mathematical concept behind the approach is called stochastic dominance, where investment decisions are based on distributions rather than moments.

ORPSS is a cost effective transportation optimization software, which helps to reduce both operational and capital expenses.Building on the ORPSS model, OptiRisk India has developed Delivery Management System (DMS) and has secured an implementation order from SKM Marketing India to implement it.

DMS is a web as well as mobile-enabled application that automates the task of order capture and delivery management. This solution helps reduce cash-to-cash cycle and thus working capital requirement.The DMS solution is delivered through a cloud-based technology, which is easy to adopt and no up-front investment in software licences or in hardware is required.

For more details about the product please visit: http://solution.optiriskindia.com/ORPSS.04.02/login

• Eurostars project SENRISK(Sentiment news and market analysis of sovereign and corporate bonds for credit risk Assessment)

OptiRisk is the consortium leader of a recently awarded Eurostars project SENRISK, which will commence in January 2017 with our partners and consortium members from Germany and Austria. It deals with the development of 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. The tool will investigate 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.

We hired 6 interns for three months during the summer- Andrea Cantamessa, Yuan Yuan, Jamie Atkinson and Wenxuan Zhang from UCL, Maria Anzovino from University of Milan and Nicholas Eterovic from Bath University. Their research lead to the following white papers:

• Volatility Forecast with GARCH Model and News Analytics - Andrea Cantamessa
• Market Regime Identification using Hidden Markov Models - Yuan Yuan
• Volatility Forecast using GARCH, News Sentiment and Implied Volatility - Jamie Atkinson

• Kavya Reddy has joined as Administration and Finance Executive.

An economist steps over a $10 bill that's lying on the ground. His friend asks him why he didn't take the money. "It couldn't possibly be there," he explains. "If it were, somebody would've picked it up!"

- Well Known cliché about economists also quoted in Making Capitalism more Creative Bill Gates