Recent Quant Links from Quantocracy as of 08/16/2025

In the early 90s, the quant forefathers (Fama and French) introduced their now-canonical factor models: first three, then five, and eventually seven, explaining much of the variation in US equity returns. Today, these models are used to understand what easy-to-replicate risk factors managers are being exposed to. Allocators will want to pay for only the truly unique return sources that cant

Weve all used on/off type trading signals at some point. But you can nearly always extract more insight with a simple adjustment that focuses on using data efficiently. Let me show you how using a crypto trend example. The problem with binary signals Youve seen them everywhere. If price is above the 20-day moving average, be long. If its below, be short. Thats a binary signal.

Today, Pythons ecosystem offers an abundance of tooling to support every aspect of the development workflow. From dependency management to static analysis, from linting to environment setup, there are more options than ever. This article presents a modern, opinionated toolchain for Python development in quantitative research and development. The focus is code quality, ensuring that your

Partisan Bias in Professional Macroeconomic Forecasts Benjamin S. Kay (Federal Reserve), et al. June 2025 Using a novel dataset linking professional forecasters in the Wall Street Journal Economic Forecasting Survey to their political affiliations, we document a partisan bias in GDP growth forecasts. Republican-affiliated forecasters project 0.3-0.4 percentage points higher growth when Republicans

This post demonstrates that country allocation with macroeconomic factors can materially enhance the returns on international equity portfolios in dollar terms. We identify a range of economic developments that, according to standard theory and in conjunction with market inattention, should predict the outperformance of countries either through exchange rate appreciation or higher local-currency