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The effect of the great moderation on the US business cycle in a time-varying multivariate trend-cycle model
Creal, Drew; Koopman, Siem Jan; Zivot, Eric - 2008
accounts for time variation in macroeconomic volatility, known as the great moderation. In particular, we consider an … volatility processes and mixture distributions for the irregular components and the common cycle disturbances enable us to … that time-varying volatility is only present in the a selection of idiosyncratic components while the coefficients driving …
Persistent link: https://www.econbiz.de/10011376640
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Measuring asymmetric stochastic cycle components in US macroeconomic time series
Koopman, Siem Jan; Lee, Kai Ming - 2005
To gain insights in the current status of the economy, macroeconomic time series are often decomposed into trend, cycle and irregular components. This can be done by nonparametric band-pass filtering methods in the frequency domain or by model-based decompositions based on autoregressive moving...
Persistent link: https://www.econbiz.de/10011346480
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Measuring Asymmetric Stochastic Cycle Components
Koopman, Siem Jan; Lee, Kai Ming - 2005
To gain insights in the current status of the economy, macroeconomic time series are often decomposed into trend, cycle and irregular components. This can be done by nonparametric band-pass filtering methods in the frequency domain or by model-based decompositions based on autoregressive moving...
Persistent link: https://www.econbiz.de/10014062862
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Long run returns predictability and volatility with moving averages
Chang, Chia-Lin; Ilomäki, Jukka; Laurila, Hannu; … - In: Risks : open access journal 6 (2018) 4, pp. 1-18
This paper examines how the size of the rolling window, and the frequency used in moving average (MA) trading strategies, affects financial performance when risk is measured. We use the MA rule for market timing, that is, for when to buy stocks and when to shift to the risk-free rate. The...
Persistent link: https://www.econbiz.de/10011906234
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Maximum likelihood estimation of stochastic volatility models
Sandmann, Gleb; Koopman, Siem Jan - 1996
Persistent link: https://www.econbiz.de/10000953379
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Econometric analysis of financial derivatives: an overview
Chang, Chia-Lin; McAleer, Michael - In: Journal of econometrics 187 (2015) 2, pp. 403-407
Persistent link: https://www.econbiz.de/10011499624
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Leverage and feedback effects on multifactor Wishart stochastic volatility for option pricing
Asai, Manabu; McAleer, Michael - In: Journal of econometrics 187 (2015) 2, pp. 436-446
Persistent link: https://www.econbiz.de/10011499703
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Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance
Asai, Manabu; McAleer, Michael - In: Journal of econometrics 189 (2015) 2, pp. 251-262
Persistent link: https://www.econbiz.de/10011504522
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Long memory modelling of inflation with stochastic variance and structural breaks
Bos, Charles S.; Koopman, Siem Jan; Ooms, Marius - 2007
conditional variance is modelled by a stochastic volatility process. We develop a Monte Carlo maximum likelihood method to obtain … variance, in the order of integration, in the short memory characteristics and in the volatility of volatility. …
Persistent link: https://www.econbiz.de/10011373822
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Periodic seasonal Reg-ARFIMA-GARCH models for daily electricity spot prices
Koopman, Siem Jan; Ooms, Marius; Carnero, M. Angeles - 2005
Novel periodic extensions of dynamic long memory regression models with autoregressive conditional heteroskedastic errors are considered for the analysis of daily electricity spot prices. The parameters of the model with mean and variance specifications are estimated simultaneously by the method...
Persistent link: https://www.econbiz.de/10011346471