Noncausality and asset pricing
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Matthijs Lof
Abstract
Misspecification of agents’ information sets or expectation formation mechanisms may lead to noncausal autoregressive representations of asset prices. Within the class of linear (vector) autoregressions, annual US stock prices are found to be best described by noncausal models, implying that agents’ expectations are not revealed to an outside observer such as an econometrician observing only realized market data. A simulation study shows that noncausal asset prices are observed when the data are generated by asset-pricing models featuring heterogeneous expectations.
I thank Bruce Mizrach (the editor), two anonymous referees, Katja Ahoniemi, Markku Lanne, Henri Nyberg, Pentti Saikkonen, and participants at the 19th Symposium of the Society for Nonlinear Dynamics and Econometrics in March 2011 and at a CeNDEF seminar at the University of Amsterdam in May 2011 for useful comments. The OP-Pohjola Group Research Foundation and the Academy of Finland are gratefully acknowledged for financial support.
- 1
This paper only deals with stationary time-series, excluding the ‘borderline’ possibility of a unit root process that is not invertible but fundamental (Alessi, Barigozzi, and Capasso 2011).
- 2
Forni et al. (2009) propose an alternative approach by applying large-dimensional factor models, which increase the econometrician’s information set and thereby avoid nonfundamentalness.
- 3
The simulations are also carried out for different values of a and c between -1 and 1 and for different sample sizes (500 and 1000). As long as a and c are not too close to zero (i.e. the simulated data are not white noise), the results are similar to those in Table 2 and are therefore not explicitly reported.
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Articles in the same Issue
- Stochastically weighted average conditional moment tests of functional form
- Do Latin American Central Bankers Behave Non-Linearly? The Experiences of Brazil, Chile, Colombia and Mexico
- Empirical analysis of ARMA-GARCH models in market risk estimation on high-frequency US data
- Quasi-maximum likelihood estimation of multivariate diffusions
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- Noncausality and asset pricing
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