Quantocracy’s Daily Wrap for 03/04/2019

In the spring of 2017, Yahoo pulled a fast one on the crowd by suddenly changing the technical coding rules for accessing its financial data, leaving countless R users high and dry, including yours truly. Numerous R files that had been meticulously written, revised and maintained over months and years were suddenly broken. Not fun. As frustrating as that day was (not to mention the weeks that

According to psychology literature, mood increases from Thursday to Friday and decreases on Monday. In general, people tend to evaluate future prospects more optimistically when they are in a good mood than when they are in a bad mood. In equity markets, the presence of optimism or pessimism that is unrelated to fundamentals, usually called sentiment, delivers clear, testable cross-sectional

The rise of big data, application of machine learning and other technological developments in recent years have transformed the quantitative finance industry, and The Quant Conference has been conceived as a unique event to provide an educational forum for delegates to hear about current trends in the cutting-edge field of quantitative finance. The Quant Conferences speaker roster of industry

Commodity Futures contracts were established in 1865, but commercially available data starts in 1959, leaving an 80+ year period of unstudied history. In our latest academic paper Two Centuries of Commodity Futures Premia Chris Geczy and I use hand-collected futures data to extend the well-known cross-sectional Value, Momentum and Basis factors in commodity futures back to 1877. This paper

It can be difficult to disentangle the difference between luck and skill by examining performance on its own. We simulate the returns of investors with different prediction accuracy levels and find that an investor with the skill of a fair coin (i.e. 50%) would likely under-perform a simple buy-and-hold investor, even before costs are considered. It is not until an investor exhibits accuracy in

This is a summary of the recent performance of a wide range of excellent Tactical Asset Allocation (TAA) strategies, net of transaction costs. These strategies are sourced from books, academic papers, and other publications. While we dont (yet) include every published TAA model, these strategies are broadly representative of the TAA space. Learn more about what we do or let AllocateSmartly help

Long-only factor portfolios can be used for benchmarking smart beta ETFs Results highlight minor tracking errors Likely explained by relatively homogenous factor definitions by ETF issuers INTRODUCTION Investment professionals are not known for their creativity, but that is perhaps only because people outside of the finance industry do not understand the intricacies of finance. Significant amounts