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Simulated models suffer intrinsically from validation and comparison problems. The choice of a suitable indicator quantifying the distance between the model and the data is pivotal to model selection. However, how to validate and discriminate between alternative models is still an open problem...
Persistent link: https://www.econbiz.de/10010490842
and smoother and the simulation smoother which do not rely on a linear Gaussian observation equation. Furthermore, results …
Persistent link: https://www.econbiz.de/10011348357
models. We illustrate this by means of an empirical replication of a widely cited study, as well as a simulation exercise. …
Persistent link: https://www.econbiz.de/10011747829
We provide a simulation smoother to a exible state-space model with lagged states and lagged dependent variables. Qian … efficient simulation smoother, which relies on mean corrections for unconditional vectors. When applied to a factor model, the … proposed simulation smoother for the states is efficient compared to other state-space models without lagged states and …
Persistent link: https://www.econbiz.de/10012000564
estimated by VARs, local projections, and simulation methods. We show that the use of our criteria significantly affects …
Persistent link: https://www.econbiz.de/10013070607
general enough to apply to impulse responses estimated by VARs, local projections, and simulation methods. We show that our …
Persistent link: https://www.econbiz.de/10012709425
importance of both choice of forecast or simulation horizon and choice between minimizing point or distribution based loss … measures. Our empirical analysis centers around the implementation of a series of simulation and prediction experiments, as … in setting U.S. monetary policy, and our simulation experiments are based on a comparison of simulated and historical …
Persistent link: https://www.econbiz.de/10009777938
This paper proposes a generalized exponential moving average (EMA) model, a new stochastic volatility model with time-varying expected return in financial markets. In particular, we effectively apply a particle filter (PF) to sequential estimation of states and parameters in a state space...
Persistent link: https://www.econbiz.de/10012935606
I develop a new method for approximating and estimating nonlinear, non-Gaussian state space models. I show that any such model can be well approximated by a discrete-state Markov process and estimated using techniques developed in Hamilton (1989). Through Monte Carlo simulations, I demonstrate...
Persistent link: https://www.econbiz.de/10013048908
In this paper, using simulations, we compare specification procedures for testing the null hypothesis of a Gaussian distribution for the innovations of GARCH models. More precisely, Cramer-von Mises and Kolmogorov-Smirnov type statistics are computed for empirical processes based on the...
Persistent link: https://www.econbiz.de/10013107338