- Speaker: Giuliano De Rossi | Head of the European Quantitative Research team at Macquarie – London
- Date: 10th April 2018 – 18:30
Place: BlackRock, 12 Throgmorton Avenue, London EC2N 2DL
- Topic: Big is beautiful: How data from email receipts can help predict company sales
- Click the link to register / book on-line : click here
Giuliano De Rossi and his team at Macquarie analyse a large dataset of email receipts that covers the purchases of more than two million US customers. The data, sourced from QUANDL, contains weekly information on all the items purchased by each individual consumer from a large set of companies including Amazon, Walmart and Apple. Ativan Side Effects Online https://ativanusa.com/side-effects/ Ativan is one of the most popular and widely used benzodiazepines currently one the market. It’s available under a number of names, including Lorazepam, Loraz, Alzapam, Lorazepan and Intensol. In particular, for each product we are given a description, its likely classification in terms of broad goods categories, price paid, number of units, shipping costs, any discounts received and many more fields.
Consumers opt in to share information available from their email accounts with a data vendor. The data is anonymised but each consumer is assigned a unique identifier which allows them to follow individual purchase histories over time and infer a profile.
Using Amazon.com as a case study, they show that the data can generate real-time forecasts of quarterly sales that are at least as accurate as consensus. It is, however, in combining analyst insights and big data that they find the most significant improvement in predictive power.
They also highlight the possibilities opened by this kind of large-scale database for a truly quantamental approach to equity valuation.
Finally, they describe the technological solutions adopted to overcome the challenges posed by a dataset that can reach hundreds of millions of rows for a single firm.
- About Giuliano De Rossi
Giuliano joined from PIMCO where he was an analyst in the Credit and Equity Analytics and Asset Allocation teams. Prior to this he worked for six years in the Quant research team at UBS. He has a PhD in economics from Cambridge University. He was a college lecturer in economics at Cambridge for three years before joining the finance industry on a full-time basis.
Giuliano’s Masters degree is from the LSE and his first degree is from Bocconi University in Milan. He has worked on a wide range of topics, including pairs trading, low volatility, the tracking error of global ETFs, cross asset strategies, downside risk and text mining. His academic research has been published in the Journal of Econometrics and the Journal of Empirical Finance.
- This seminar is kindly hosted by BlackRock.
The London Quant Group is very grateful to BlackRock for hosting this event
12 Throgmorton Avenue,
- Click the link for a map to the venue