Heterogeneous Trembles and Model Selection in the Strategy Frequency Estimation Method

2019 ◽  
Author(s):  
James R. Bland
Keyword(s):  
Model Selection ◽  
Frequency Estimation ◽  
Estimation Method

scholarly journals Quantifying Drivers of Forecasted Returns Using Approximate Dynamic Factor Models for Mixed-Frequency Panel Data

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 56-90
Author(s):  
Monica Defend ◽  
Aleksey Min ◽  
Lorenzo Portelli ◽  
Franz Ramsauer ◽  
Francesco Sandrini ◽  
...  
Keyword(s):  
Panel Data ◽  
Model Selection ◽  
Estimation Method ◽  
Selection Criterion ◽  
Factor Models ◽  
Dynamic Factor ◽  
Dynamic Factor Models ◽  
Mixed Frequency ◽  
Model Selection Criterion ◽  
Mixed Frequency Data

This article considers the estimation of Approximate Dynamic Factor Models with homoscedastic, cross-sectionally correlated errors for incomplete panel data. In contrast to existing estimation approaches, the presented estimation method comprises two expectation-maximization algorithms and uses conditional factor moments in closed form. To determine the unknown factor dimension and autoregressive order, we propose a two-step information-based model selection criterion. The performance of our estimation procedure and the model selection criterion is investigated within a Monte Carlo study. Finally, we apply the Approximate Dynamic Factor Model to real-economy vintage data to support investment decisions and risk management. For this purpose, an autoregressive model with the estimated factor span of the mixed-frequency data as exogenous variables maps the behavior of weekly S&P500 log-returns. We detect the main drivers of the index development and define two dynamic trading strategies resulting from prediction intervals for the subsequent returns.

The scaled RCS measurement method for lossy targets via dynamically matching the reflection coefficients in the THz band

2021 ◽  
Author(s):  
Shuang Pang ◽  
Yang Zeng ◽  
Qi Yang ◽  
Bin Deng ◽  
Hong-Qiang Wang
Keyword(s):  
Cross Section ◽  
High Frequency ◽  
Measurement Method ◽  
Dielectric Material ◽  
Frequency Estimation ◽  
Estimation Method ◽  
Physical Optics ◽  
Reflection Coefficients ◽  
Effective Solution ◽  
Terahertz Band

Abstract In the terahertz band, the dispersive characteristic of dielectric material is one of the major problems in the scaled radar cross section (RCS) measurement, which is inconsistent with the electrodynamics similitude deducted according to the Maxwell’s equations. Based on the high-frequency estimation method of physical optics (PO), a scaled RCS measurement method for lossy objects is proposed through dynamically matching the reflection coefficients according to the distribution of the object’s facets. Simulations on the model of SLICY were conducted, the inversed RCS of the lossy prototype was obtained using the proposed method. Via comparing the inversed RCS with the calculated results, the validity of the proposed method is demonstrated. The proposed method provides an effective solution to the scaled RCS measurement for lossy objects in the THz band.

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