Enterprising Investor
Practical analysis for investment professionals

Quantitative Methods


Factor Premiums: An Eternal Feature of Financial Markets

These research results should give investors greater confidence in the robustness of factor premiums, reinforcing their utility in crafting effective investment strategies.

Market and Model Risk: Sequentially Interweaved Risk Dimensions

Risk managers must look at market and model risk through a single lens to see the complete picture of their market-related investment and trading risks, as well as management costs, complexities, time, and regulatory requirements.

Factor Strategies Belong in Your Completion Portfolio Toolkit

Why wouldn't you include factor strategies in your completion portfolio? A review of the two commonly used approaches for managing institutional assets highlights their symbiotic nature.

Why the New T+1 Settlement Cycle Matters: A Global Index Provider’s Perspective

Shorter settlement periods are meant to protect market participants. But the new T+1 settlement cycle for US equities may have undesirable knock-on effects for financial market participants around the world, including index fund managers.

Leveraging AI to Identify and Predict Financial Crises

Despite some current limitations, AI stands to offer significant advantages versus traditional approaches to identifying and predicting financial crises.

Implementation Shortfalls Hamstring Factor Strategies

Smart rebalancing rules help portfolio managers capture more of the return that is inherent in their factor strategies. Concentrating on “priority best” trading improves factor portfolio performance.

How to Build Better Low Volatility Equity Strategies  

Not all low volatility strategies are created equal. Many lack the diversification and risk control needed to guard against concentration and macro risk.

Harvesting Equity Premia in Emerging Markets: A Four-Step Process

There is hope for investors seeking a robust emerging market equity strategy to complement their other equity investments.

The Benefits of Using Economically Meaningful Factors in Financial Data Science

As machine learning (ML) and data science become ever more integrated into finance, which factors should we consider for our ML-driven investment models and how should we select among them?

ChatGPT: Copilot Today, Autopilot Tomorrow?

How can quant and fundamental analysts apply LLMs like ChatGPT? How effective a “copilot” can these technologies be?



By continuing to use the site, you agree to the use of cookies. more information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.

Close