Arbeitspapier
Information Theoretic Optimality of Observation Driven Time Series Models
We investigate the information theoretic optimality properties of the score function of the predictive likelihood as a device to update parameters in observation driven time-varying parameter models. The results provide a new theoretical justification for the class of generalized autoregressive score models, which covers the GARCH model as a special case. Our main contribution is to show that only parameter updates based on the score always reduce the local Kullback-Leibler divergence between the true conditional density and the model implied conditional density. This result holds irrespective of the severity of model misspecification. We also show that the use of the score leads to a considerably smaller global Kullback-Leibler divergence in empirically relevant settings. We illustrate the theory with an application to time-varying volatility models. We show that th e reduction in Kullback-Leibler divergence across a range of different settings can be substantial in comparison to updates based on for example squared lagged observations.
- Sprache
-
Englisch
- Erschienen in
-
Series: Tinbergen Institute Discussion Paper ; No. 14-046/III
- Klassifikation
-
Wirtschaft
Hypothesis Testing: General
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- Thema
-
generalized autoregressive models
information theory
optimality
Kullback-Leibler distance
volatility models
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Blasques, Francisco
Koopman, Siem Jan
Lucas, André
- Ereignis
-
Veröffentlichung
- (wer)
-
Tinbergen Institute
- (wo)
-
Amsterdam and Rotterdam
- (wann)
-
2014
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:41 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Blasques, Francisco
- Koopman, Siem Jan
- Lucas, André
- Tinbergen Institute
Entstanden
- 2014
Ähnliche Objekte (12)
Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models
Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects
Missing Observations in Observation-Driven Time Series Models
A General Framework for Observation Driven Time-Varying Parameter Models
A Multilevel Factor Model for Economic Activity with Observation Driven Dynamic Factors
Observation-Driven filters for Time-Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics
Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models
In-Sample Bounds for Time-Varying Parameters of Observation Driven Models
Observation driven mixed-measurement dynamic factor models with an application to credit risk
Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk
In-Sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation Driven Models
Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model
Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models
Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects
Missing Observations in Observation-Driven Time Series Models
A General Framework for Observation Driven Time-Varying Parameter Models
A Multilevel Factor Model for Economic Activity with Observation Driven Dynamic Factors
Observation-Driven filters for Time-Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics
Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models
In-Sample Bounds for Time-Varying Parameters of Observation Driven Models
Observation driven mixed-measurement dynamic factor models with an application to credit risk
Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk
In-Sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation Driven Models
Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model
Predicting Time-Varying Parameters with Parameter-Driven and Observation-Driven Models
Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects
Missing Observations in Observation-Driven Time Series Models
A General Framework for Observation Driven Time-Varying Parameter Models
A Multilevel Factor Model for Economic Activity with Observation Driven Dynamic Factors
Observation-Driven filters for Time-Series with Stochastic Trends and Mixed Causal Non-Causal Dynamics
Feasible Invertibility Conditions and Maximum Likelihood Estimation for Observation-Driven Models
In-Sample Bounds for Time-Varying Parameters of Observation Driven Models
Observation driven mixed-measurement dynamic factor models with an application to credit risk
Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk
In-Sample Confidence Bands and Out-of-Sample Forecast Bands for Time-Varying Parameters in Observation Driven Models