Forecasting Commodity Prices with Geospatial Insights
Quant price forecasts for agricultural commodity traders and procurement professionals
The imperative has never been greater for traditional market participants to keep up with alternative data and algorithmic trading. Join Descartes Labs as we discuss how proprietary geospatial data can be used to enhance machine and human intelligence for data-driven trading and procurement. We will also share how Descartes Labs makes this capability operational, driving customer ROI by:
- Providing trade strategies and decision assurance to merchant traders
- Designing smart procurement programs for CPGs, to mitigate the impact of price volatility
Our specialists will share their perspectives on market forecasting for agricultural commodities, offering answers to common questions including:
- How do I distinguish when markets are driven by fundamental factors versus macro factors?
- How do I make my trading or purchasing strategies more responsive to market disruption?
- How do I determine local weather and acreage to better understand commodity prices?
- How do I ensure no data leakage or overfitting in my forecasting models?
- And more!
The webinar will conclude with a live Q&A; questions can be asked during the webinar or pre-submitted using the registration form.
Aya Ibarra | Head of Consumer Goods and Retail
Prior to Descartes Labs, Aya Ibarra spent over seven years at IBM helping clients all over the world and IBM itself augment business decisions with artificial intelligence. Along the way, she has been able to help clients accelerate their innovations by applying artificial intelligence methods to other emerging technologies such as viral multi-media, e-commerce, internet of things, and blockchain. At Descartes Labs, she leads our consumer goods and retail business where she sees a transformational shift in the way we understand demand, supply, and the environments these businesses operate within. When she is not talking about gigantic data sets and what you can do with them, she likes to travel, cook new recipes, and support the arts.
Tom Siddiqui | Head of Agriculture
Tom Siddiqui leads Descartes Labs’ Agriculture business, bringing the benefits of geospatial data science to merchant traders and inputs players. Tom is a trusted advisor to companies in commodities trading, agribusiness, and capital markets on driving return on investment from advanced analytics, machine learning, and alternative data. Prior to Descartes Labs, Tom led global business development and the US office of Coalition, an S&P Global company. He has a degree in history and political science from Oxford University.
Eduardo Franco | Market Forecasting Business Lead
Eduardo Franco spent the first 5 years of his career in finance, despite his training in industrial engineering, working on structured credit and debt trading desks before earning a Masters in Applied Urban Science & Informatics at NYU. The skills he obtained there in geospatial, as well as machine and deep learning (then taught by Yann Lecun), landed him at Descartes Labs as a computer vision specialist. He served as principal scientist and project lead on various efforts across various domains (including agriculture, ocean freight, energy, and power) and now leads the Market Forecasting Team where he leverages his technical and business expertise to deliver complex market solutions, powered by geospatial data. He reads dense history books for fun, enjoys skiing and the outdoors, and likes spending hours tending fires to smoke food.