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Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks 被引量:1
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作者 Claudio Morana 《Open Journal of Statistics》 2014年第4期292-312,共21页
In the paper, a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independentl... In the paper, a general framework for large scale modeling of macroeconomic and financial time series is introduced. The proposed approach is characterized by simplicity of implementation, performing well independently of persistence and heteroskedasticity properties, accounting for common deterministic and stochastic factors. Monte Carlo results strongly support the proposed methodology, validating its use also for relatively small cross-sectional and temporal samples. 展开更多
关键词 Long and Short Memory Structural BREAKS Common factors Principal Components Analysis fractionally integrated heteroskedastic factor vector autoregressive model
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