The AI and big data revolution have energized the financial market in ways not seen since the introduction of electronic trading in the 1980’s.
The concept behind deep learning is surprisingly easy to understand. Through thousands of iterations of trial and error, artificial neural networks are able to classify profitable states of a tradable asset as measured through a compilation of data signals.
The question remains: With the influx of new alternative data sources flooding the market, how can one measure the efficacy of an alternative data signal?
Join Lucena’s CEO Erez Katz and learn about an innovative approach to automating the ingestion, validation and enhancement of an alternative data source for forecasting asset prices.
No data science or deep learning experience required for this session.
"The Journey of an Alternative Data Signal" Will Cover:
- - Trends in Alternative Data and Quant Funds
- - A Deep Dive into the Data Validation Process
- - Why Feature Engineering is Crucial
- - How Deep Learning and CNNs are Applied to Stocks
- - How Empirical Evidence of Data’s Value is Proven
- - Q&A
Whether you're an investment professional looking to utilize Alternative Data for decision making or a data provider looking to tap into your data's potential in the financial markets this discussion has something for you. Enjoy!