Quant Investing Spotlight

How can investors employ quant tools in their portfolios?

Quantitative investing as we know it today originated in the 1980s. Several quant investment firms established around that time are still thriving today. But much has changed since then.

What the Future Holds for Quant Investing: Ten Hypotheses (Robeco)

Today’s quant models are developed manually. The authors of this paper anticipate that in the future, algorithms will at least partly take over this task.

Smart Beta and Index-Based Strategies (CFA Institute Research & Policy Center)

There is a common perception that index investing will dominate the future of investment. What does the data say about this prediction?

Taylor Swift’s Tour and Consumer Discretionary Stocks (State Street)

This analysis shows how alternative data and quant approaches can spot attractive opportunities for allocators.

Digital Charting and Visual Deception in Markets (The University of Sydney)

This paper examines how visual representations influence asset prices by shaping investors’ return and risk evaluations.

The Statistical Limit of Arbitrage (Becker Friedman Institute)

While the Sharpe ratio can be estimated consistently, it cannot be achieved by any feasible portfolio with weights constructed using historical data.

Passive Investors Are Trend Followers (Price Action Lab)

Although academia and practitioners have proposed many laws in finance and trading, it turns out that many concepts are simply a matter of convention.

Hedge Fund Due Diligence with Factor Model Monte Carlo (CAIA)

Market risk, or “systematic” risk, serves as a kind of summary measure for all of the risks to which financial assets are exposed.

AI, Textual Analysis and Hedge Fund Performance (Alpha Architect)

It remains to be seen if AI might outperform benchmark indices—something human active managers have persistently failed to accomplish.