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Alternative Data for Investors
Complimentary CQF Institute Talk

Thursday, 10th October London and online

This talk will be led by Cuemacro founder, Saeed Amen.

Talk Overview:
In this talk, Saeed Amen will define what alternative data is, discussing the various challenges associated with its usage. He shall introduce the topic of natural language processing, and how it can be used to structure text based data and various Python tools which can be used to accomplish this. Later, he will discuss a number of different investor use cases for alternative data for a number of different types of datasets. Saeed Amen will include alternative datasets which have been derived from sources like images and text, as well as more traditional numerical sources. The use cases presented include forecasting EPS for publicly traded European retailers from satellite imagery, using FX flow data to trade FX spot and also machine readable news to trade FX. The content is based on parts of The Book of Alternative Data, by Alex Denev and Saeed Amen, which will be published on Wiley in 2020.

Speaker Biography:
Saeed Amen is the founder of Cuemacro. Over the past fifteen years, Saeed Amen has developed systematic trading strategies at major investment banks including Lehman Brothers and Nomura. He is also the author of Trading Thalesians: What the ancient world can teach us about trading today (Palgrave Macmillan) and is the coauthor of The Book of Alternative Data (Wiley), due in 2020. Through Cuemacro, he now consults and publishes research for clients in the area of systematic trading. He has developed many Python libraries including finmarketpy and tcapy for transaction cost analysis. His clients have included major quant funds and data companies such as Bloomberg. He has presented his work at many conferences and institutions which include the ECB, IMF, Bank of England and Federal Reserve Board. He is also a co-founder of the Thalesians.

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This talk is CPD Certified

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For any questions, please email us at cqfinstitute@fitchlearning.com