Recorded Webinar: Integrating Intelligent Machine Readable News30 November 2021
Intelligent machine readable news is a powerful tool in the arsenals of trading and investment firms seeking competitive advantage. It turns unstructured data into actionable insight and can be used, for example, to uncover market trends, identify correlations and evaluate sentiment. In turn, it can inform quant strategies and predictive models.
While machine readable news feeds typically provide a mix of real-time alerting, low-latency or ultra-low latency news, analytics, and historical news archives directly to applications, their value to traders and investors is dictated by how well they are integrated with internal systems.
This webinar will consider:
- The extent of intelligent machine readable news
- Use cases of low-latency and ultra-low latency news feeds
- Challenges of integrating feeds with existing internal systems
- Practical approaches, technologies and tools supporting integration
- Benefits of getting integration right, pitfalls to avoid
More about our speakers:
Saeed Amen is the founder of Cuemacro. Over the past 15 years, Saeed has developed systematic trading strategies at major investment banks including Lehman Brothers and Nomura. He is also the co-author of The Book of Alternative Data: A Guide for Investors, Traders and Risk Managers and author of Trading Thalesians: What the ancient world can teach us about trading today (Palgrave Macmillan).
Through Cuemacro, he 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.
Major quant funds and data companies such as Bloomberg have been among his clients. He has presented his work at many conferences and institutions, including the ECB, IMF, Bank of England and Federal Reserve Board. He is also a co-founder of the Thalesians.
Creed & Bear
Andrea has worked as a Quant Portfolio Manager and Researcher for over 20 years. He started his career in Frankfurt where he worked as a Quant Researcher and PM for Commerzbank and Deka Investment and then moved to London to lead the quant offering at Sarasin. Andrea has recently joined Black Alpha Capital, a London based hedge fund. Andrea’s research interests include the application of machine learning models to financial time series. Currently Andrea and his team pursue several research projects on market anomalies and mid-frequency trading signals for global macro portfolios.
Andrea graduated in Economics and spent a year at the Department of Mathematics in the University of Venice.
Gurraj Singh Sangha
Chief Quantitative Investment Officer
Mr. Sangha is the former Global Head of Data Science , Risk, and Market Intelligence for State Street Verus where he helped lead a risk and investment strategy team for an artificial intelligence platform that integrates machine learning, natural language processing, portfolio and risk management, and human experiences to explore connections and extract relevant insights between market-moving events and multi-asset class portfolios. Mr. Sangha is an accomplished global macro portfolio manager, strategist, and risk manager, with over 20 years’ experience. He has advised firms on developing quantamental approaches to trading — strategies at the intersection of structural, statistical, and fundamental trading, utilizing data science, machine learning on both structured and unstructured data, and behavioral analytics. Further, he has led several investment strategy and risk management teams and held a number of senior positions, including Chief Investment Strategist at a $6 billion global macro volatility hedge fund, and Senior Global Macro Trader at a $400 million hedge fund. Mr. Sangha began his career at Goldman, Sachs & Co.,in the Global Investment Research Division. He received honors at the International Mathematics Olympiad, served on the Canadian Mathematics Olympic Team, and is a Magna Cum Laude graduate of Brown University.
Sergio Gago Huerta
Managing Director of Media Solutions
Sergio leads the Media Solutions operating unit for Moody’s Analytics which features the NewsEdge suite of real-time news-based solutions. He is leading advances in artificial intelligence and machine learning and applying these developments to news and other media content for companies seeking timely, highly-relevant information to fuel decision making as news breaks. With previous experience at Rakuten, Zinio, VCG, Tangelo and AresDevelopment, Sergio brings over two decades of executive management experience leading highly technical organizations to drive digital transformation. He holds an MBA and Quantum Computing graduate degrees.
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