Dynamics of Value-Tracking in Financial Markets

TL;DR

This paper examines how market prices track underlying asset values, highlighting the impact of trader types on tracking accuracy and identifying conditions under which value-tracking fails.

Contribution

It introduces the 'deciblack' as a measure of tracking error and models how non-valuation traders cause significant tracking breakdowns without changes in asset value.

Findings

Large tracking errors occur with enough non-valuation traders.

A threshold exists where value-tracking fails regardless of underlying value.

Market dominance by non-valuation traders threatens efficient price discovery.

Abstract

The efficiency of a modern economy depends on what we call the Value-Tracking Hypothesis: that market prices of key assets broadly track some underlying value. This can be expected if a sufficient weight of market participants are valuation-based traders, buying and selling an asset when its price is, respectively, below and above their well-informed private valuations. Such tracking will never be perfect, and we propose a natural unit of tracking error, the 'deciblack'. We then use a simple discrete-time model to show how large tracking errors can arise if enough market participants are not valuation-based traders, regardless of how much information the valuation-based traders have. We find a threshold above which value-tracking breaks down without any changes in the underlying value of the asset. Because financial markets are increasingly dominated by non-valuation-based traders, assessing how much valuation-based investing is required for reasonable value tracking is of urgent practical interest.