RavenPack | September 19, 2017
This panel addresses why the investment community should pay attention to this growing industry that is set to disrupt the way we analyze financial markets.
Moderator: Marko Kolanovic, Global Head of Quantitative and Derivatives Strategy, J.P. Morgan
Although asset managers might be distracted by regulatory pressures and the uncertain political climate, alternative data which draws alpha from non-traditional sources beyond market data and fundamentals, is becoming the primary driver of active investment performance.
Investors are using new inputs from sentiment derived from big data, web scraping pricing data to develop real-time economic indicators of inflation to mining online job postings to gauge employment.
RavenPack's 5th Annual Research Symposium
, that took place September 19, 2017 in New York City.
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High inflation has returned in developed markets after decades of lying low. In our latest paper, we show how to build an inflation-based asset allocation strategy using sentiment data and we illustrate that sentiment-based strategies outperform models that depend merely on past observed inflation values.
This year's RavenPack Research Symposium brought two intense days of knowledge sharing in London and New York, from 25 top experts in natural language processing, quantitative investing and machine learning. Together, we explored how firms can leverage new language models to generate alpha, better manage risk and respond to calls for more sustainable investment practices.
Human capital is at the heart of value creation. Our latest research demonstrates how unprecedented workforce insights, sourced from over 200 million job postings, can generate more alpha.