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Abstract
This paper looks at various definitions of momentum then investigates a particular definition of momentum via a statistical model where the asset price is assumed to follow a log Ornstein–Uhlenbeck process. Momentum is a term that is widely used to describe price behaviour but is not clearly defined in terms of statistical models. The results we derive show that asset price momentum is determined by price autocorrelation and that positive momentum, as commonly understood, would require explosive behaviour in log prices.
Highlights
Technical analysts employ many techniques in seeking profitable opportunities, one of which is the use of charts
This paper looks at various definitions of momentum investigates a particular definition of momentum via a statistical model where the asset price is assumed to follow a log Ornstein-Uhlenbeck process
The results we derive show that asset price momentum is determined by price autocorrelation and that positive momentum, as commonly understood, would require explosive behaviour in log prices
Summary
Technical analysts employ many techniques in seeking profitable opportunities, one of which is the use of charts. [9] measure return momentum as the change in risk premium for a percentage change in firm value, where they find that a firm’s revenues, costs, and growth options combine to determine the dynamics of its return autocorrelation and show that this insight helps momentum strategy to be profitable This provides a technical definition of return momentum, it is cross sectional, not single asset momentum. Unlike previous momentum literature that focuses on the relative performance of securities in the cross-section, we emphasize that this paper intends to investigate momentum within asset price process. Our work focuses on price momentum, the same approach can be applied to other time series such as returns and earnings
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