We discuss the economic model and the econometric properties of the
Convolution Autoregressive Process of order 1 (C-AR(1)), with focus on the
simplest gaussian case. This is a first order autoregressive property in
which the innovations are dependent of the lagged value of the process. We
show that the model may be generated by the presence of extrapolative bias
in expectations. Extrapolative expectations bring about excess volatility
and excess persistence in the dynamics of the variable. While excess
volatility cannot be identified if one only observes the time series of
the variable, identification can be achieved if the expectations of the
variable are observed in the forward markets. We show that the model is
well suited to generate the excess variance of long maturity prices
documented in the Giglio-Kelly variance ratio test. We finally discuss
possible extensions of the model beyond the gaussian case both by changing
the specification of the expectations model and setting a non linear data
generating process for the fundamental process.
Referente: Alessandra Petrucci
Il seminario sara' tenuto Mercoledì 18 Aprile 2018 ore 12.00 presso l'™aula 32 del DiSIA, Viale Morgagni n.
59 - 50134 Firenze.
Tutti gli interessati sono cordialmente invitati a partecipare.