Information Theoretic Optimality of Observation Driven Time Series Models

By Francisco Blasques, S. J. Koopman, André Lucas. 2014

145 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/b814a0cb0b289e31e43babc73731008516f111a8

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Citations in the corpus

Forecasting football match results in national league competitions using score-driven time series models (2019, methodology): “The score-driven updating of parameters has a theoretical foundation, since the estimates of the time-varying parameter are optimal in a Kullback–Leibler sense, see Blasques et al. (2015), and therefore it is not a heuristic method.”
Spillover Dynamics for Systemic Risk Measurement Using Spatial Financial Time Series Models (2016, unknown): “The expressions may seem complicated at first, but we show below that their verification is often straightforward; see also Blasques et al. (2014b) for the verification of similar moment conditions in a wide range of observation-driven models.”
New HEAVY Models for Fat-Tailed Realized Covariances and Returns (2017, background): “Score-driven dynamics possess information theoretical optimality properties even if the model is mis-specified; see Blasques, Koopman, and Lucas (2015).”
Time‐Varying Transition Probabilities for Markov Regime Switching Models (2017, background): “Blasques et al. (2015) demonstrate that observation driven models with score dynamics improve upon the local Kullback–Leibler divergence of the statistical model from the true unknown data distribution.”
Time-Varying Systemic Risk: Evidence From a Dynamic Copula Model of CDS Spreads (2018, unknown): “In recent work, Blasques, Koopman, and Lucas (2014a) showed that the GAS model can be motivated information-theoretically, by showing that this approach minimizes the local Kullback–Leibler divergence between the true conditional density and the model-implied density, and Harvey (2013) motivated…”
Maximum Likelihood Estimation for Generalized Autoregressive Score Models (2014, unknown): “The optimality 2 properties of using the score function in (1) are investigated in Blasques et al. (2014a).”