OptiRisk Systems UK
(Incorporating Indian Division)
   AMPL Family of Products
   Eurostars Project: SENRISK
   New Whitepapers
   Events
   Optirisk India
   New Staff and Summer Interns
   Partnership and Joint Venture
   Our Key Clients
Welcome to our Summer 2017 newsletter. Scroll down to find out what we have been up to!
AMPL Family of Products
AMPL IDE
OptiRisk Systems has completed its implementation and delivery of AMPL IDE. AMPL Optimization will soon release the alpha version. AMPL IDE features and more are also included in our product AMPLDev. AMPLDev incorporates Linear Programming, Integer Programming and Stochastic Programming modelling features as well as special purpose solvers, namely, CPLEX and FortSP.
AMPL API
Over the last two years OptiRisk under a contract from AMPL Optimization have developed AMPL APIs which connects AMPL models to programs written in (i) Java (ii) MATLAB (iii)C++ (iv) .NET(C#). The APIs for Python and R are on the bench and beta versions will be soon completed.
Eurostars Project: SENRISK
In January 2017, we officially started the Eurostars funded project, SENRISK – Sentiment news and market analysis of sovereign and corporate bonds for credit risk assessment. The consortium consists of four partners: PS Quant (Austria), Fraunhofer ITWM (Germany), Acatis (Germany) and the managing partner OptiRisk Systems (UK). In the forthcoming 24 months the consortium will develop a Decision Support System featuring analytic models for credit risk assessment, that consider sentiment from macroeconomic and firm specific news and announcements. TheDSS delivers a timely estimate of sovereign and corporate bond yields and credit risks.
New Whitepapers
On our website, we have recently released the following whitepapers:
•   Using Market Sentiment to Enhance Second Order Stochastic Dominance Trading Models
•   News Augmented GARCH (1,1) Model for Volatility Prediction
Events
Past Events
Optimum Decision Making and Risk Analysis Applied to Finance (28 November - 2 December 2016), Rio de Janeiro, Brazil
March 2017, India and Hong Kong
OptiRisk partnered with Indian Institute of Management Calcutta and UNICOM seminars to successfully hold their first ever conferences in Bangalore and Hong Kong. The events gathered leading researchers and subject experts on the topics of AI, Machine Learning and Sentiment Analysis. Read our blog post here.
June 2017, London
•   Log Optimal Growth & Kelly Strategy, 26 June 2017
•   Sentiment Extraction and Applications for Financial Prediction, 27 June 2017
•   AI, Machine Learning and Sentiment Analysis Applied to Finance, 28 – 29 June 2017
•   Novel Data Sources and Contents for Financial Markets, 30 June 2017
Forthcoming Workshops:
OptiRisk is presenting the following workshops:
•   Optimum Decision Making and Risk Analysis Applied to Finance, 21 – 25 September 2017, Chennai, India
•   Optimum Decision Making and Risk Analysis Applied to Finance, 27 November – 1 December 2017, London
OptiRisk is presenting at following other events:
Workshop on Stochastic Programming
Honoring Maarten van der Vlerk
10-11 August 2017
Sponsored by the University of Groningen
Optirisk India
Sales and Order Management System
Sales and Order Management System (SOMS) streamlines sales process. It eliminates manual and paper based operations, resulting in increased productivity, reduced cost (operational and working capital) and improved profitability. It is a web as well as mobile-enabled application (supports both connected and offline modes) to capture current inventory and sales orders. It also helps the manager to track/ monitor the sales team's activity and productivity. The system generates optimal routes and offers map navigation for the sales representatives.
OptiRisk India has developed the Sales and Order Management System (SOMS) which is undergoing trial with a food and beverages companies.
Yard Management System
Yard Management System (YMS) manages the movement of cars within the large yards of a manufacturing facility, warehouse, or distribution centre, and improves recording of stock locations. YMS is a web as well as android application, which captures geo-location of planned bay layouts of the yard. It helps the jockey to park and retrieve the cars in the yard with ease, using the android application. It also helps the manager to monitor the geo-location of jockeys and the parked cars in real-time.
Recently, OptiRisk India has tested the Proof-Of-Concept of YMS with an automobile manufacturer.
New Staff and Summer Interns
New Staff
Jayadeep Shitole has joined OptiRisk in India as a Research Analyst and Software Engineer
Deepsheka Mishra has joined OptiRisk in India as Business Development (Projects Manager).
Summer Interns
OptiRisk has recruited 4 summer interns and supervises their applied finance industry based projects; the students are completing their Masters Programme in Computational Finance in UCL's Computer Science department. The interns are carrying out research on trading strategies, sentiment data and corporate bond yield prediction. This work will also form their Masters dissertation.
Their project titles are:
1. Using News & Social Media Data to Construct Momentum Strategies – Yu Ke Shi
2. Use of VIX as an asset in a Daily Trading Strategy – Xiao Ming Yang
3. Trading Strategy: using Calendar Spread of Crude Oil Futures via Kalman Filter – Xu Ren
4. Enhanced Corporate Bond Yield Prediction Method incorporating News Sentiment – Zhi Xin Cai
Partnership and Joint Venture
We have formed a joint venture company with Advanced Logic Analytics; the company is called: ALA-OptiLab. ALA-OptiLab has started to develop the Robo Advisor software. The Robo Advisor support tool is designed for ‘Life Cycle Financial Planning’; the tool makes recommendations for individual asset and liability management. We are in discussion with a financial advisory company with over 400 IFAs who will be the users of the Robo Advisor for their retail HNI clients.
Our Key Clients
We thank our key clients for their customs.
Share this Credits
 
This Newsletter was compiled by Aqeela Rahman and supported by Xiang Yu and Julie Valentine”.