scholarly journals Synthesis of hourly wind power series using the Moving Block Bootstrap method

2014 ◽  
Author(s):  
Julio Usaola
Keyword(s):  
Power Series ◽  
Wind Power ◽  
Bootstrap Method ◽  
Block Bootstrap ◽  
Moving Block Bootstrap

scholarly journals Models for Expected Returns with Statistical Factors

2020 ◽  
Vol 13 (12) ◽  
pp. 314
Author(s):  
José Manuel Cueto ◽  
Aurea Grané ◽  
Ignacio Cascos
Keyword(s):  
Time Series ◽  
Coefficient Of Variation ◽  
Stock Prices ◽  
Bootstrap Method ◽  
Block Bootstrap ◽  
Time Series Regression ◽  
Cross Sectional ◽  
Multifactor Models ◽  
Two Factors ◽  
Resampling Procedure

In this paper, we propose multifactor models for the pan-European Equity Market using a block-bootstrap method and compare the results with those of traditional inferential techniques. The new factors are built from statistical measurements on stock prices—in particular, coefficient of variation, skewness, and kurtosis. Data come from Reuters, correspond to nearly 2000 EU companies, and span from January 2008 to February 2018. Regarding methodology, we propose a non-parametric resampling procedure that accounts for time dependency in order to test the validity of the model and the significance of the parameters involved. We compare our bootstrap-based inferential results with classical proposals (based on F-statistics). Methods under assessment are time-series regression, cross-sectional regression, and the Fama–MacBeth procedure. The main findings indicate that the two factors that better improve the Capital Asset Pricing Model with regard to the adjusted R2 in the time-series regressions are the skewness and the coefficient of variation. For this reason, a model including those two factors together with the market is thoroughly studied. We also observe that our block-bootstrap methodology seems to be more conservative with the null of the GRS test than classical procedures.

On the bootstrap and the moving block bootstrap for the maximum of a stationary process

1999 ◽  
Vol 76 (1-2) ◽  
pp. 1-17 ◽  
Author(s):  
Krishna B. Athreya ◽  
Jun-ichiro Fukuchi ◽  
Soumendra N. Lahiri
Keyword(s):  
Stationary Process ◽  
Block Bootstrap ◽  
Moving Block Bootstrap

scholarly journals Investigating Mortality Uncertainty Using the Block Bootstrap

2010 ◽  
Vol 2010 ◽  
pp. 1-15 ◽  
Author(s):  
Xiaoming Liu ◽  
W. John Braun
Keyword(s):  
Life Expectancy ◽  
Mortality Risk ◽  
Spatial Dependence ◽  
Bootstrap Method ◽  
Prediction Intervals ◽  
Block Bootstrap ◽  
Model Framework ◽  
Model Risk ◽  
Process Risk ◽  
Carter Model

This paper proposes a block bootstrap method for measuring mortality risk under the Lee-Carter model framework. In order to take account of all sources of risk (the process risk, the parameter risk, and the model risk) properly, a block bootstrap is needed to cope with the spatial dependence found in the residuals. As a result, the prediction intervals we obtain for life expectancy are more accurate than the ones obtained from other similar methods.

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