"A Data Science Approach to Managing Crowd-Sourced Systematic Trading Strategies” by Dr. Jess Stauth скачать в хорошем качестве

"A Data Science Approach to Managing Crowd-Sourced Systematic Trading Strategies” by Dr. Jess Stauth

This talk, titled, "Statistical Algorithm Selection: A Data Science Approach to Managing Systematic Trading Strategies Developed by "The Crowd"" was given by Dr. Jessica Stauth at QuantCon NYC 2018. The field of quantitative finance has experienced rapid adoption of machine learning techniques at nearly every stage of the typical workflow, e.g. new signal identification, signal combination, portfolio optimization, and trading. We explore how the techniques of machine learning might be applied to a unique new problem: identifying trading strategies which are likely to produce "alpha" in a real market setting from a pool of millions of backtests created by Quantopian's 180,000+ member online community. We will review challenges including: Compiling our (imbalanced) data set of simulation results Designing features based on transactions, returns, holdings, and more? Defining a goal (what should we select for?) Facing the problems of non-stationarity, overfitting, and interaction terms Dr. Jessica Stauth is former Managing Director of Portfolio Management, Research, and Trading at Quantopian, where she and her team were in charge of selecting the algorithms from the Quantopian community. Dr. Stauth holds a Ph.D. in Biophysics from UC Berkeley, where her research focused on computational neuroscience. You can find the slides for this talk at http://bit.ly/stauthqc18. To learn more about Quantopian, visit www.quantopian.com. Disclaimer Quantopian provides this presentation to help people write trading algorithms - it is not intended to provide investment advice. More specifically, the material is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory or other services by Quantopian. In addition, the content neither constitutes investment advice nor offers any opinion with respect to the suitability of any security or any specific investment. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.