Quantocracy’s Daily Wrap for 05/20/2019

In Part 3 of the series we reviewed the relationship between returns and correlation of the 2-asset portfolio UPRO and TMF. The basic equal weight strategy was very compelling in terms of total return and CAGR. However, the strategy is susceptible to large drawdowns, especially in situations where US equities and long term bonds are out favor, for example in the 2015 and 2018 periods. We also went

Last week we introduced a signal that appeared to generate statistically significant performance results for performing country rotation. This week, we walk through the steps taken to explore the robustness of the signal. We first explore out-of-sample data with sector and emerging market country indices. Unfortunately, definitional differences and limited data impact our ability to pass

Here are my 8-thoughts and 1 solution idea about Campbell Harvey and Yan Liu recently released paper on their influential concept of the factor zoo. To sum it up, it says that there are too many data-mined factors out there and that we should be using much higher t-statistics to accept factors. Ironically, which is perhaps subtlety intentional, it feels like the mega-list of factors in the paper

The performance of the Momentum factor in the US has been poor since 2000 Fundamental valuation spreads were ineffective for improving the performance Combinations with other factors and factor volatility filters would have yielded better results INTRODUCTION John H. Cochrane of the Hoover Institution at Stanford University described the ever-growing number of factors in the investment industry as

FDA drug approvals, legal verdicts, mergers, share buybacks, and the occasional CEO podcast appearance, are all examples of events that impact stock prices. Though not as quantifiable as technical indicators, real life events clearly affect prices. In an attempt to further explore the relationship between events and stock prices, I gathered historical price data from the IEX API and scraped events