Jeremy Large

NLP / economics

jeremy large
Fellow in Economics
St Hugh's College, University of Oxford

Jeremy Large is a financial economist in the Department of Economics at the University of Oxford. He is also an experienced algorithmic trader on global capital markets, with a track record in Global Macro, Foreign Exchange, Listed Equity and Commodity trading.

Jeremy has published research in the areas of Market Microstructure and Financial Econometrics. He lectures on these topics at graduate level, as well as in the area of Big Data and Machine Learning for Economics.

Jeremy held a Fellowship at All Souls College, Oxford from 2005 until 2008, when he joined the hedge fund AHL within Man Group Plc. In 2013 Jeremy joined the hedge fund, Tudor Investment Corporation, where he was a Quantitative Portfolio Manager.

Jeremy is an investor in social enterprise and participates in the activities of the organization, Ashoka, as a Member of the Ashoka Support Network.

 

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Estimating Very Large Demand Systems - NLP-inspired "good2vec" in consumer theory

Abstract

We present a discrete choice, random utility model and a new estimation technique for analyzing consumer demand for large numbers of products. In our model each product has an associated unobservable vector of attributes from which the consumer derives utility. We allow the consumer to purchase multiple products at once in a consumption bundle.
Because the number of bundles available is massive, a new estimation technique, which is based on the practice of negative sampling in NLP, is needed to sidestep an intractable likelihood function.
We prove consistency of our estimator, validate the consistency result through simulation exercises, and estimate our model using supermarket scanner data.