Insights

Two Sigma researchers provide an overview of some of the most interesting lectures and sessions at JSM 2018, and highlight some of the most important challenges statisticians face going forward.

We constructed a Chinese trade sensitivity factor and examined how it responds to developments in the evolving US-China trade dispute.

Distributed transactions suffer from poor performance due to two major limiting factors. First, distributed transactions suffer from high latency because each of their accesses to remote data incurs a long network delay. Second, this high latency increases the likelihood of contention among distributed transactions, leading to high abort rates and low performance. The authors present Sundial, an in-memory distributed optimistic concurrency control protocol that addresses these two limitations.

An interview with Andy Pavlo, an assistant professor of databaseology in the Computer Science Department at CMU to discuss his current research and outlook on the future of database management.

MiSoSouP is a suite of algorithms for extracting high-quality approximations of the most interesting subgroups, according to different interestingness measures, from a random sample of a transactional dataset.

Two Sigma’s Labs team recently performed an in-depth survey of the extensive literature on the Sharpe ratio and published its findings in a new Technical Report.

Two Sigma Data Clinic partnered with the New York Hall of Science to use visitor behavior data to improve an interactive exhibit.

In the machine learning research community, it is generally believed that there is a tension between memorization and generalization. This paper examines the extent to which this tension exists, by exploring whether it is possible to generalize by memorizing alone.

Two Sigma’s Co-Founder discusses algorithmic investing, self-driving cars, blockchain, education, and more.

The authors survey and discuss methods proposed in the literature for estimating the Sharpe ratio; computing confidence intervals around a point estimation of the Sharpe ratio; and performing hypothesis testing on a single Sharpe ratio and on the difference between two Sharpe ratios.