Add to ORKGMisspecification of agents' information sets or expectation formation mechanisms maylead to noncausal autoregressive representations of asset prices. Annual US stock prices are found to be noncausal, 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 processes can be generated by asset-pricing models featuring heterogeneous expectations
In this paper, we compare the forecasting performance of univariate noncausal and conventional causa...
Noncausal autoregressive models with heavy-tailed errors generate locally explosive processes and t...
The price, return and volume series of virtually all traded financial assets share a set of commonly...
Misspecification of agents' information sets or expectation formation mechanisms maylead to noncausa...
This paper is concerned with univariate noncausal autoregressive models and their potential usefulne...
This paper is concerned with univariate noncausal autoregressive models and their potential usefulne...
The way in which market participants form expectations affects the dynamic properties of financial a...
The way in which market participants form expectations affects the dynamic properties of financial a...
In this paper, we propose a new noncausal vector autoregressive (VAR) model for non-Gaussian time se...
In this paper, we propose a Bayesian estimation and prediction procedure for noncausal autoregressiv...
In this paper, we compare the forecasting performance of univariate noncausal and conventional causa...
There is hope for the generalized method of moments (GMM). Lanne and Saikkonen (2011) show that the ...
In this paper, we propose a simulation-based method for computing point and density forecasts for un...
The list of financial market anomalies (empirically documented facts unexplained by standard models...
Gouriéroux and Zakoian (2013) propose to use noncausal models to parsimoniously capture nonlinear fe...
In this paper, we compare the forecasting performance of univariate noncausal and conventional causa...
Noncausal autoregressive models with heavy-tailed errors generate locally explosive processes and t...
The price, return and volume series of virtually all traded financial assets share a set of commonly...
Misspecification of agents' information sets or expectation formation mechanisms maylead to noncausa...
This paper is concerned with univariate noncausal autoregressive models and their potential usefulne...
This paper is concerned with univariate noncausal autoregressive models and their potential usefulne...
The way in which market participants form expectations affects the dynamic properties of financial a...
The way in which market participants form expectations affects the dynamic properties of financial a...
In this paper, we propose a new noncausal vector autoregressive (VAR) model for non-Gaussian time se...
In this paper, we propose a Bayesian estimation and prediction procedure for noncausal autoregressiv...
In this paper, we compare the forecasting performance of univariate noncausal and conventional causa...
There is hope for the generalized method of moments (GMM). Lanne and Saikkonen (2011) show that the ...
In this paper, we propose a simulation-based method for computing point and density forecasts for un...
The list of financial market anomalies (empirically documented facts unexplained by standard models...
Gouriéroux and Zakoian (2013) propose to use noncausal models to parsimoniously capture nonlinear fe...
In this paper, we compare the forecasting performance of univariate noncausal and conventional causa...
Noncausal autoregressive models with heavy-tailed errors generate locally explosive processes and t...
The price, return and volume series of virtually all traded financial assets share a set of commonly...