Quant & AI Experts in Commodities
Data-driven quantitative modelling and analytics for commodities businesses, quant hedge funds, broker dealers, prop. traders and family offices
AI & Data-Driven Commodities & Investments
Data-Driven Commodities Derivative Trading
Power your commodity derivatives strategies using data-driven insights. Our backtesting engine employs advanced algorithms based on market structures such as backwardation / contango to evaluate your trading ideas. Identification of lucrative spreads, arbitrage opportunities and pinpointing the most profitable pricing days. Capitalise on production trends with confidence using derivatives. Explore the potential of your trading strategies before you enter the market.
Risk Quantification in Commodity Businesses
Quantify the risk inherent in your commodities trading business using VaR / CVaR analysis to dissect potential losses. Know beforehand how much percentage of your trades will be at loss. Optimise your hedging strategies using VaR / CVaR as a tool and use derivatives with confidence to safeguard from sudden price movements due to geopolitical events, demand and supply fluctuations etc.
AI-Powered Backtesting for Investment Strategies
Measure the potential performance and identify profitability and risk in any investment idea or trading strategy with underlying futures, options, swaps, credit, bonds, equity, forex, etc. Invest with confidence by thorough evaluation of your strategy across hundreds of ideas such as iron condor, straddle, strangle etc, using AI enabled backtest.
Algorithmic Trading with Artificial Intelligence
Revolutionize trading strategies with our AI-driven Algo Trading solution, leveraging advanced algorithms to make precise decisions based on market patterns and real-time indicators. Supercharge your trading, harness price-action data, analyse patterns with high speed for best alpha-generating outcomes.
Investment Funds Analytics
Generate higher returns, and better monitor the risk through advanced analytics driven by AI models. Maintain transparency with investors, regulators, risk committees. Seamless data integration with your underlying portfolio investments across all asset classes. European investment funds can also meet PRIPS, AIFMD, KIID & UCITS requirements.
Big Data Credit Scoring
Reduce non performing loans and increase profitability across all lending products - retail loans, credit cards, personal loans, unsecured loans, MSME credit. Build, train and backtest high performance machine learning models with lending data and alternate data sources. Acquire more customers that will otherwise remain underbanked.
Quantitative analytics & AI for commodities and derivatives to capture fleeting market opportunities with superior speed and agility
We help commodities businesses, quant hedge funds, broker dealers, prop. traders and family offices to quantify risks and remove emotional bias while making critical trading decisions. Through a combination of best-of-breed data scientists, data analysts, quant experts and leadership, our comprehensive approach enables enhanced alpha generation for your commodity trading strategies and optimized investment portfolio performance.
Our Clients have trusted Convexium for more than 15 years (since 2007) for bringing their innovative ideas into disruptive reality. We have helped financial institutions like funds and banks to measure market risks, credit risks, costs, potential returns and performance scenarios. Convexium is a division of Netsity, which is a full stack software development company, with hundreds of successful case studies across the globe, a hands-on leadership team, and highly committed project teams.
Let’s talk about how Convexium could help you optimise your commodities trading strategies, quantify risk and enhance investment portfolios. Provide your information here to book an appointment with our experts.
Derivatives Strategy and Investment Risk using Quant Modelling, AI and Big Data
Quantitative Modelling
Assess your investment and commodities derivatives strategy risk-reward profile using cloud-based quantitative reports. Analyse metrics such as kurtosis, probabilistic sharpe ratio, omega ratio, skewness, volatility, risk-adjusted returns, daily VaR, drawdowns, profitability and many more. Our cloud-based customizable dashboards offer comprehensive analysis of your strategy through features like box plots, underwater plots, distribution plots, top drawdowns charts, and more. Identify the optimal pricing days for your spreads, liquid alternatives to illiquid contracts and arbitrage opportunities from anywhere and anytime and remove emotional bias in your decisions.
Our quant modelling process helps commodities businesses, quant hedge funds, broker dealers, prop. traders and family offices by rigorous backtesting in a recreated environment replicating conditions like supply / demand of commodities markets, geopolitical events and currency fluctuations. We collect in-house data and from sources like S&P, Bloomberg, and Thomson Reuters and transform using Python libraries like Pandas and NumPy. We then model your strategy using powerful tools like TensorFlow, NumPy, SciPy, PySpark and evaluate them through customizable cloud-based dashboards and reports made using Matplotlib, Seaborn, Plotly. This iterative approach allows for continuous optimization and fine-tuning, ensuring your strategies yield best results.
Contact us now to discuss your Risk Analytics & Model development requirements.
Artificial Intelligence and Machine Learning
AI in commodity derivatives goes beyond traditional VaR, using advanced scenario analysis and ML to optimize hedging with spot data, news feeds, and alternative data. AI-powered trading limits predict optimal entry/exit points for maximum profit and minimal loss. AI models don’t just analyze the past; they identify profitable spreads, arbitrage opportunities, and ideal “pricing days” for optimized trades. Even real-time data like crude oil production is factored in, allowing the ML models to suggest data-driven futures strategies for superior results.
Machine learning developers at Convexium can help you accelerate your model development, model training, testing, and evaluation. Backed by experienced data scientists and wealth of experience in Logistic and Linear Regression, Random Forest, Bayesian Networks, Support Vector Machine, Neural Network, Lasso Regression, R, Python, we can seamlessly integrate and deploy the models within your Fintech business processes.
Contact us now to discuss your problem statement and what machine learning models can help you in making faster decisions.
Heterogeneous Data Integrations for Modern Platforms
Pre-built data connectors unlock a vast data ecosystem for commodities paper trading desks, risk / derivatives trading departments (Quant), commodity derivatives broker dealers. They empower you with seamless fundamental, market, and tick data integrations, so that you don’t get bogged down by manual data loading process. With data from leading providers like FactSet, Bloomberg, S&P Market Intelligence Platform and Thomson Reuters, alongside real-time data feeds from exchanges such as NYSE and ICE, you can conduct thorough market analysis, respond with agility to market fluctuations, and keep your trading strategy development fueled by the most up-to-date information available.
At Convexium, we handle various data formats, from FTP and APIs (like Bloomberg’s B-PIPE) to SQL databases and through native cloud-based ingestion tools like AWS Database Migration Services and Azure Data Factory, we ensure seamless replication of database changes into Delta Lake. Our team composed of Data Engineers, ETL Developers, Data Architects, Data Analysts, and Data Scientists leverages technologies such as Apache Kafka for data ingestion and Python for pipeline development and efficient data movement and transformation. We empower your team to focus on what truly matters – developing and executing winning commodity derivatives trading strategies.
Contact us now to unlock a vast ecosystem with our data connectors and expert team at Convexium.
Big Data
For commodities paper trading desks and their risk/derivatives trading departments (Quant), big data modelling offers unparalleled insights into market trends and risk factors. By harnessing big data like images, satellite, sentiment, weather, search engine, logistics and other alternative data sources, traders can gain a comprehensive understanding of market sentiment, market trends, dynamics, supply chains. Sentiment analysis tools provide valuable insights into bullish and bearish market sentiments, enabling traders to make informed decisions and mitigate risks effectively. Additionally, the incorporation of weather data and commodity prices enhances predictive capabilities, allowing for more accurate forecasting of supply-demand dynamics and price movements. This holistic approach empowers you to optimize strategies and maximize profitability in commodity markets.
At Convexium, our team of data scientists and machine learning developers specializes in leveraging cutting-edge technologies to perform big data modelling for commodities paper trading desks and their risk/derivatives trading departments (Quant). Through the utilization of advanced tools and techniques such as Apache Spark, Apache Flink, and Hadoop, we extract valuable insights from diverse datasets including images, satellite imagery, sentiment analysis data, weather data, commodity prices data, and logistics data.
Contact us now to unlock unparalleled insights and optimize your commodity trading strategies with our expertise in big data modeling.
Scalability and Delta Lakes
In the high-stakes world of quantitative trading, traditional data storage solutions can be an anchor, hindering your ability to react swiftly and capitalize on fleeting market opportunities. Modern data infrastructures cut through these limitations with a cutting-edge approach built on the power of scalable cloud platforms like AWS, Azure, and GCP. This ensures your infrastructure effortlessly adapts to your evolving needs, regardless of data volume. This agility is a game-changer for hedge funds, commodity desks, and anyone utilizing risk models like VaR/CVaR.
At the core of this scalability lies Delta Lake, a revolutionary storage layer built on top of your existing data lake. Delta Lake empowers algorithmic traders with a unique set of features. First, it boasts unmatched scalability, effortlessly handling petabytes of data with billions of partitions and files. This allows you to store vast amounts of historical and real-time market data for comprehensive analysis. Second, Delta Lake’s ACID transactions ensure data consistency and integrity, even during concurrent modifications. This is crucial for backtesting strategies and conducting risk analysis with confidence. Finally, Delta Lake’s “time travel” capability allows you to easily access and analyze historical versions of your data, perfect for backtesting strategies and identifying patterns to inform future trades.
At Convexium we further leverage technologies like Apache Spark and Apache Flink to enable parallel processing of complex trading algorithms on your Delta Lake data. This combination of scalable infrastructure and Delta Lake’s powerful features translates to real-world advantages for algorithmic trading, allowing you to make data-driven decisions that lead to superior trading performance.
Contact us now to revolutionize your quantitative trading strategies with our expertise in modern data infrastructures and Delta Lake technology at Convexium.
About Us
Convexium is a leading provider of Quantitative and AI services, specializing in risk management and strategy optimization for commodities markets. We help traders navigate the complexities of oil & gas, metals, agriculture, energy, and carbon credits markets by providing quantified risk insights and analysis. With our team of highly skilled quants, we aid in developing data-driven, high-performing physical and paper-based trading strategies so that you minimize your risk and capitalize on opportunities with confidence. With over 25+ years of experience and our seasoned team of quants, data scientists, AI / ML experts, and domain specialists we have helped financial institutions like funds and banks to measure market risks, credit risks, costs, potential returns and performance scenarios. We help our clients maximize their profit and minimize losses by providing comprehensive risk analysis, strategic insights, and tailored services that align with their investment objectives.
Convexium is a wholly owned division of Netsity Systems (P) Ltd. We have successfully taken up the challenge of providing our clients with analytics solutions and data science expertise to service your globe-spanning financial services business.
We are headquartered in India, with a dedicated 10,000 sq.ft. of center-of-excellence, and global representative offices in UK, USA, Europe, and Southeast Asia. Our team of experienced business analysts, risk management experts, quants blend our technology solutions with their Fintech domain understanding to offer you flexible and configurable solutions that empower your sales, marketing, underwriting, risk, investment, operations, compliance and customer support departments.
Leadership
CEO
Avnish Gupta
Avnish is an experienced technical architect, building scalable and secure data infrastructure, enabling growth and higher profitability for the Fintechs. He co-founded Convexium (Financial Analytics division of Netsity) in 2007 and has helped many financial institutions develop technology frameworks, design and architect technology solutions, manage full stack development teams. His razor sharp focus is on aligning project outcomes with client’s business goals, their funding targets, top line growth and strategic initiatives. Avnish is a Fintech expert and has successfully executed projects by bringing in his extensive knowledge with machine learning, data science, blockchain technology, and fintech software frameworks. He holds Engineering Degree in Computer Science from Pune University (B.E. batch of 1993).
Head of Products
Gautam Sabhnani
Gautam, a seasoned investment professional with a passion for guiding HNWI and family office clients towards financial success. He ensures that the financial strategies developed are tailored to clients specific circumstances. Using a deep understanding of the financial markets and a client-centric approach, Gautam has established a reputation as a trusted advisor in the investment industry. With 30+ years of experience in the financial industry, he specializes in financial advisory, investment planning and portfolio management, offering tailored solutions that align with each client’s unique financial situation and objectives.
Quant Analyst & Co-Founder - Quant & AI
Arnav Gupta
As a Co-Founder of the Quant & AI division, Arnav plays a crucial role in driving innovation in financial analysis. He leverages sophisticated financial metrics, statistical methods, and data science techniques to empower clients for informed decision-making. He employs a multifaceted approach to risk management, utilizes industry-standard tools for data analysis and visualization, and builds accurate robust model based on strategies. In a dynamic market, Arnav leverages advanced quantitative analysis, helping traders optimize strategies, make confident and accurate trading decisions based on the backtesting results of their current strategies. Arnav’s meticulous data preprocessing and model evaluation ensure clients receive comprehensive insights and reliable guidance. Catering to a diverse clientele including commodity players, family offices, hedge funds, and brokers, he is a quantitative analyst with a major in Mathematics.
Advisor - Energy Commodities
Amin Mirarab
Amin has experience in the fast-paced world of commodity trading, with strong analytical skills he is effectively able to assess financial data and market trends. With a proven track record of success in buying, selling, and blending petroleum products he understands the consumer behaviour. Advisor to most major Commodity trading companies specializing in the Oil commodities. He also brings expertise in developing effective hedging strategies to mitigate risks and maximize profits. Amin holds a bachelors degree in Management (2013) and an MBA in Finance (2018)
Head of Artificial Intelligence
Geeta Gupta
Geeta heads the Fintech Analytics division, where she identifies the machine learning models, development frameworks, big data infrastructure components and maps them to the real world business problems. With a solid understanding of various technologies, she works closely with the financial institutions, product companies, developer communities, and experts. She co-founded Convexium in 2007 (Financial Analytics division of Netsity) and has extensive experience in defining use-cases, helping with building solution architecture, and walk through the journey of finding product-market fit. She is very much hands-on with full stack AI model development and works closely with technical team at Convexium. Geeta holds M.Tech. in Data Science (2022), Masters of Computer Applications (MCA, 1997) and BSc Computers degree (1994).
Chief Data Architect & Co-Founder - Quant & AI
Aditi Gupta
Aditi constructs robust data-driven architectures, focusing on scalability, speed, and optimization for executing high-performance risk models and trading strategies. By harnessing Python and other quantitative libraries, Aditi facilitates the development of scalable data pipelines and deployment of advanced metrics, ultimately mitigating market volatility and maximizing risk-adjusted returns for clients. She plays an important role in delivering actionable insights through intuitive and interactive interfaces, driven by her meticulous processing, cleansing, and integration of real-time and historical data. Aditi works with commodities traders, hedge funds, broker dealers, and family offices, empowering them to excel in the dynamic world of finance through advanced mathematical and statistical models.
Head of Strategy
Rajnish Gupta, CFA
Rajnish has extensive experience of hedge funds industry, lending business, SME credit, supply chain management with bulk buyers of agriculture commodities, inclusive finance and value chain financing with farmer groups and collectors. He co-founded Convexium in 2007 (Financial Analytics division of Netsity) and has also helped hedge funds scale up their operations, streamline middle office functions, have robust risk management frameworks, and meet regulatory compliance requirements as per various fund regimes in Europe. Rajnish holds Chartered Financial Analyst, CFA (ICFAI, 1997) and MBA in Finance (1996), alongwith Bachelor of Science degree majoring in Computers Science (1994).
Head of Data Ops
Rajnish Paul
Paul has extensive experience in project management handling major accounts in the financial services sector, telecom, healthcare, high growth startups and product companies in US and UK. He manages Devops at Convexium across the full Financial analytics development lifecycle, Code, Build, Test, Package, Release, Configure, and Monitor. His responsibility is to ensure development and operations teams are not siloed, teams use tools & practices to automate development processes. In all the projects at Convexium, Paul takes the ownership, gets development teams to move with speed, increase the pace of releases, reliability and improved collaboration. He holds Engineering Degree in Computer Science from Pune University. (B.E. batch of 1993).
Head of Compliance
Neeraj Agrawaal, CA
Neeraj is responsible for developing and executing a comprehensive Compliance and Regulatory strategy at Convexium. He also works in close coordination with our clients and advises them on legal structures, compliance framework, regulatory reporting, and risk management. Neeraj is a seasoned Chartered Accountant and he has experience of more than 20 years in advising clients on cross-border taxation issues, structured finance, corporate restructuring, asset financing, equity and debt offerings. He is a subject matter expert on Anti-Money Laundering (AML) and Know Your Customer (KYC) matters.