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Momentum and Reversal Simply Reactions to Noise?

| | Posted in: Momentum Investing

What causes asset price momentum? In his May 2012 paper entitled “Is Momentum a Self-fulfilling Prophecy?”, Steven Jordan presents a simple, abstract model explaining the pervasiveness and robustness of evidence for intermediate-term momentum and long-term reversal. The essential assumptions of his model are: (1) demand for an asset is noisy and flat or downward sloping with price; (2) supply of an asset is noisy and flat or upward sloping with price; and, (3) some traders believe that lagged price trends tend to persist and act on this belief, with their actions scaled by the magnitude of lagged noise. He assumes that demand and supply slopes are linear to simplify formulas. Deriving time series behaviors from this model, he concludes that:

  • Momentum traders observe price noise and trade on it as information, thereby imparting predictive power to lagged noise. In other words, momentum trader beliefs transform noise into signal, and momentum trading is self-fulfilling.
  • This process exhibits overreaction, such that intermediate-term momentum trading results in long-term reversal.

In summary, the mere existence of noise (uninformed trading) and belief in trend persistence in a market may be sufficient to sustain tradable asset price momentum and long-term reversal.

Cautions regarding conclusions include:

  • As for asset pricing hypotheses generally, assumptions about market characteristics and trader behaviors are simplified.
  • Conclusions are qualitative, not quantitative. They do not explain observed magnitudes of momentum profitability.
  • Derivations assume frictionless trading. If/when trading frictions are material relative to momentum gross profitability, conclusions may change.
  • The author does not rule out the possibility that price momentum actually predicts asset value, but the research described in “A Multi-momentum Potential” supports belief that a material part of price momentum is independent of value dynamics.
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