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Portmanteau tests for linearity of stationary time series
Psaradakis, Zacharias G.; Vávra, Marián - 2015
Persistent link: https://www.econbiz.de/10011350561
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Portmanteau tests for linearity of stationary time series
Psaradakis, Zacharias G.; Vávra, Marián - In: Econometric reviews 38 (2019) 2, pp. 248-262
Persistent link: https://www.econbiz.de/10012180732
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Forecasting realized (co)variances with a block structure Wishart autoregressive model
Bonato, Matteo; Caporin, Massimiliano; Ranaldo, Angelo - 2012 - Current Draft: November 2008
The increased availability of high-frequency data provides new tools for forecasting of variances and covariances between assets. However, recent realized (co)variance models may suffer from a 'curse of dimensionality' problem similar to that of multivariate GARCH specifications. As a result,...
Persistent link: https://www.econbiz.de/10010407673
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Market regime detection via realized covariances
Bucci, Andrea; Ciciretti, Vito - In: Economic modelling 111 (2022), pp. 1-15
Persistent link: https://www.econbiz.de/10013349063
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Non-linearity, persistence and spillover effects in stock returns : the role of the volatility index
Wu, Po-Chin; Pan, Sheng-Chieh; Tai, Xue-Ling - In: Empirica : journal of european economics 42 (2015) 3, pp. 597-613
Persistent link: https://www.econbiz.de/10011485602
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Robustness of alternative non-linearity tests for SETAR models
Chan, Wai-Sum; Ng, Man-wai - In: Journal of forecasting 23 (2004) 3, pp. 215-231
Persistent link: https://www.econbiz.de/10002027376
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Time series mean level and stochastic volatility modeling by smooth transition autoregressions : a Bayesian approach
Lopes, Hedibert Freitas; Salazar, Esther - 2006
Persistent link: https://www.econbiz.de/10003350097
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LSTUR regression theory and the instability of the sample correlation coefficient between financial return indices
Ginker, Tim; Lieberman, Offer - In: The econometrics journal 24 (2021) 1, pp. 58-82
Persistent link: https://www.econbiz.de/10012504449
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Application of feed-forward neural networks smoothing transition autoregressive models in stock returns forecasting
Giovanis, Eleftherios - In: Computational optimization in economics and finance …, (pp. 27-47). 2013
Persistent link: https://www.econbiz.de/10009734441
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Application of Feed-Forward Neural Networks Smoothing Transition Autoregressive Models in Stock Returns Forecasting
Giovanis, Eleftherios - 2010
In this paper we propose and examine new approaches in smoothing transition autoregressive (STAR) models. Firstly, a new STAR function is proposed, which is the hyperbolic tangent sigmoid function. Secondly, we propose Feed-Forward Neural Networks Smoothing Transition Autoregressive (FFNN-STAR)...
Persistent link: https://www.econbiz.de/10013138095