Quantitative value explained: rules-based value investing

Value investing means buying shares that look cheap compared to what the business is worth. Quantitative value does this with data and fixed rules instead of gut feeling. This page explains how it works and what to watch out for.

Quick answer

Quantitative value is an approach that uses data, screens and fixed rules to find shares that look cheap and have sound business quality. Instead of judging each company by hand, the investor applies the same tests to a large group of companies, filters out risky ones and ranks the rest by valuation. It aims to reduce emotional bias in value investing.

Key takeaways

• Quantitative value applies value investing through data and rules.
• It screens many companies with the same tests.
• It removes companies with signs of accounting or financial risk.
• It ranks the rest by valuation and quality.
• Rules reduce bias but cannot remove investment risk.

What is quantitative value?

This approach combines two ideas. The first is value investing, which looks for shares priced below a fair estimate of their worth. The second is quantitative analysis, which uses data and set rules to make decisions.

The term was made widely known by Wesley Gray and Tobias Carlisle in their 2012 book of the same name. They argued that a careful, rules-based process can avoid many emotional mistakes that hurt value investors.

How does the process work?

The first filter is about avoiding trouble. Companies with very high debt, falling cash flow or unusual accounting can look cheap for a good reason. Removing them early cuts the chance of buying a value trap.

The ranking step often uses ratios like EBIT to enterprise value or the price to book ratio. The quality step then checks whether the business earns good returns and has a steady balance sheet.

How is it different from traditional value investing?

A traditional value investor studies each company deeply, meets management and forms a personal judgement. A quantitative value investor applies the same tests to hundreds of companies at once and follows the output.

This makes the process consistent and less affected by emotions like fear or excitement. The trade-off is that a model may miss facts that are not in the numbers, such as a change in management or a new law.

What are the risks?

Value shares can stay cheap for a long time, and there have been long periods when value as a style lagged the wider market. A model can also be built on data that looked good in the past but does not hold in the future.

Past performance is not indicative of future results. Data errors, costs and the discipline needed to follow rules through weak periods are all real challenges.

The key point to remember

Quantitative value is value investing with clear rules and data. It helps reduce bias and keeps the process consistent, but it does not remove risk or promise returns.

Frequently Asked Questions