Presented By O'Reilly and Cloudera
Make Data Work
31 May–1 June 2016: Training
1 June–3 June 2016: Conference
London, UK
Thomas Wiecki

Thomas Wiecki
Quantitative Researcher, Quantopian

@twiecki

Thomas Wiecki is the lead data science researcher at Quantopian, where he uses probabilistic programming and machine learning to help build the world’s first crowdsourced hedge fund. Among other open source projects, he is involved in the development of PyMC—a probabilistic programming framework written in Python. A recognized international speaker, Thomas has given talks at various conferences and meetups across the US, Europe, and Asia. He holds a PhD from Brown University.

Sessions

11:15–11:55 Friday, 3/06/2016
Data science & advanced analytics
Location: Capital Suite 8/9 Level: Intermediate
Thomas Wiecki (Quantopian)
Average rating: ***..
(3.50, 6 ratings)
Thomas Wiecki explores the prevalence of backtest overfitting and debunks several common myths in quantitative finance based on empirical findings. Thomas demonstrates how he trained a machine-learning classifier on Quantopian's huge and unique dataset of over 800,000 trading algorithms to predict if an algorithm is overfit and how its future performance will likely unfold. Read more.