Trading in Multiple Venues
Trade SES Launch
Whitepapers
AML Family of Products
Events
Staff Changes

Trading in Multiple Venues

OptiRisk is now supplying daily trading strategies actively in three global venues. The virtual execution of strategies are taking place through Interactive Brokers (IB) account. The daily trading portfolios are for S&P 500(US) and for Hang Seng (Hong Kong). In India the actual execution of strategies is taking place through SMC Capital. SMC Capital have many financial activities which may be succinctly put as Trading and Quantitative Investment Management. In the US we are providing live trading signals to Alfalab who are trading through Exante Brokers. In summary:

Live Trading in India NIFTY 50
Strategies (SMC Capital)

Live Trading in US S&P 500
Strategies (AlfaLab) Brokers Exante

Virtual Trading in US S&P 500
Strategies (SMC Capital) Brokers (IB)

Virtual Trading in Hong Kong Hang
Seng ( Haitong Securities) Brokers (IB)

Our virtual trading portfolio on the Hang Seng index is now available to view on our Trade SES website. Follow our strategy and view performance measures such as:

(i)    Sharpe ratio

(ii)   Sortino ratio

(iii)  Maximum drawdown

(iv)  Days to recovery

(v)   Beta (vi) Turnover percentage

Trade SES Launch

We have now launched our Trade SES portal which is a partnership between OptiRisk and SMC Capital. In this portal you will find

(i) Backtesting results and

(ii) Virtual trading results for many of the major trading venues.

Whitepapers

WE publish technical reports of our internal research and research with our alternative data providers. Once the preliminary investigations are over they are published as Whitepapers. A few such Whitepapers are in the pipeline, and the research findings will be presented in our forthcoming Finance conferences.

Read our newly published paper on:

Title: Construction of Asset Filter Based on Analyst Recommendations

Abstract:

The recommendation of financial analysts plays an important role in making investment decisions. The method of constructing a portfolio using such recommendations does not rely on quantitative models instead it relies on research of the analysts and their qualitative views. We explore paradigms of modelling whereby the qualitative research outputs of the analysts are introduced in quantitative models of portfolio construction. Read more……….

Key Words: Analyst Recommendations; Filters; NIFTY50 Index

https://optirisk-systems.com/publications/whitepapers/

AML Family of Products

AMPLDev

Our in-house optimization modelling product AMPLDev, incorporates Linear Programming, Integer Programming and Stochastic Programming modelling features. We updated AMPLDevSP making it compatible with high-dpi displays. We have started testing a new version, a major revision based on AMPL API, which will include data modelling and a visualization tool. A beta version will be made available soon.

AMPL IDE

OptiRisk Systems is a partner of AMPL Optimization and also a contractor for the support and maintenance of AMPL IDE. The recent development of AMPL IDE includes major upgrades in the underneath platform. Many performance improvements and bugfixes are addressed for the next major release.

AMPLAPI

OptiRisk, in partnership with AMPL Optimization, is maintaining and enhancing six API for AMPL, enabling access of all AMPL features from C++, Java, .NET, Matlab, R and Python

On-Line Tread Profile Measurement System (OptiRisk India)

OptiRisk India was part of developing an Industry 4.0 application - On-Line Tread Profile Measurement System - for a leading tyre manufacturer. The System was developed with the concept of Smart Factory that makes the industrial production entirely automated & interconnected.

The On-line Tread Profile (OTP) measurement System is responsible for capturing the tyre tread data from the sensor and camera placed in the Production unit, processing the data and storing it in the Database. The captured data will be analyzed and displayed in a tabular format and as a graphical representation for each Tread. The Tread data that do not match the Design criteria will be highlighted in the Report & the user will be alerted. A Fault tolerant Network Topology is implemented to avoid Single point of Failure.

Events

Upcoming Events:

In partnership with UNICOM Seminars, we will be presenting at: "Financial Evolution: AI, Machine Learning and Sentiment Analysis". This is part of a global series, where the remaining locations are:
Zurich, Switzerland, 29 October 2019
Venue - Hilton Zurich Airport
Recently, our team of AMPL developers have presented in the 30th European Conference on Operational Research (EURO 2019), Dublin, Ireland, 23 - 26 June 2019.EURO 2019 is the largest and most important conference on Operational Research and Management Science (OR/MS) in Europe, in the following sessions:
Session TB-49, Software tools for optimization modeling and solving [L249],
Tuesday, June 25, 10:30-12:00
Ansuman Swain, Gautam Mitra, Christian Valente, A Visualization Tool for AMPL Using MDDB Features
Session WA-49, Software for large-scale optimization III [L249], Wednesday,
June 26, 8:30-10:00
Christian Valente, Gautam Mitra, Ansuman Swain, Representation and solution of Stochastic Programming Formulations in AMPL
Past Events:
Earlier in 2019, OptiRisk's team travelled to present at the conference "Financial Evolution: AI, Machine Learning and Sentiment Analysis" in the following locations:
Mumbai, India, 14 March 2019
Venue - National Stock Exchange
Hong Kong, 20 March 2019
Venue - [United Centre, Admiralty] Stephenson Harwood Conference Room
London, 25 – 26 June 2019
Hilton London Kensington

Staff Changes:

Joined

We're delighted to welcome 3 staff members who have joined us recently. They are:

Dhruv Rana, Research Analyst & Software Engineer
Based in Delhi, India, Dhruv has prior experience in the financial sector working as a Data Scientist. He obtained a Masters from Institute of Chemical Technology (ICT), Mumbai.
Rahul Yadav, Research Analyst & Software Engineer
Also based in Delhi, India, Rahul has 3 years of experience in algorithmic trading, data science and big data. He holds a Bachelors and Masters degree in Mathematics and Scientific Computing from Indian Institute of Technology (IIT), Kanpur.
Pietro Campi, Research Intern
Splitting his time between London and Milan, Pietro joins us to conduct a project on Deep Learning models for financial applications. He is currently completing a MSc in Computer Science at Università degli studi di Milano-Bicocca, Italy.

Leaving:

Xiang Yu:
After an association of nearly 8 years during which she contributed in many ways in the company's development Dr Xiang Yu has left us for a Business Development position with a Larger Listed Company. She leaves with our blessings and we wish her success in her new position.
Yulu Qiu:
Afterone year and three months of service first as an intern and then as a full time employee, Yulu has decided to relocate in Mainland China. She has now resumed working for OptiRisk as our country representative in China.
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This newsletter was compiled by Aqeela Rahman and supported by Prof Gautam Mitra.