Author: Drew Donald Saunders
Publisher:
ISBN:
Category : Default (Finance)
Languages : en
Pages :
Book Description
Three Essays on Financial Macroeconomics
Author: Drew Donald Saunders
Publisher:
ISBN:
Category : Default (Finance)
Languages : en
Pages :
Book Description
Publisher:
ISBN:
Category : Default (Finance)
Languages : en
Pages :
Book Description
Three Essays in Applied Macroeconomics and Financial Economics
Author: Amir Tayebi
Publisher:
ISBN:
Category : Consumer credit
Languages : en
Pages : 0
Book Description
Publisher:
ISBN:
Category : Consumer credit
Languages : en
Pages : 0
Book Description
Three Essays in International Macroeconomics and Finance
Author: Enrique Martinez-Garcia
Publisher:
ISBN:
Category :
Languages : en
Pages : 198
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 198
Book Description
Three Essays in Applied Financial Economics and Macroeconomics
Three Essays in Financial Economics
Three Essays on Macroeconomics and Finance
Three Essays in Financial Economics
Author: Jose Vicente Martinez
Publisher:
ISBN:
Category :
Languages : en
Pages : 294
Book Description
Publisher:
ISBN:
Category :
Languages : en
Pages : 294
Book Description
Three Essays in Financial Economics
Three Essays in Financial Economics
Three Essays in Financial Economics
Author: Adrien Alvero
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
In the third chapter, "Fuzzy Bunching", we introduce a new fuzzy bunching approach that is robust to noise. The existing bunching approach identifies the extent of bunching from a sharp spike in the probability density function. In many finance settings, however, the sharp spike could be diffused by data noise. The key idea behind our fuzzy bunching estimator is to identify bunching from the area of a bulge in the cumulative distribution function. The fuzzy bunching approach also avoids density estimation, which makes it easy to implement in sparse data. We provide the theoretical foundation of this approach and illustrate the advantages by using simulated and real data.
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
In the third chapter, "Fuzzy Bunching", we introduce a new fuzzy bunching approach that is robust to noise. The existing bunching approach identifies the extent of bunching from a sharp spike in the probability density function. In many finance settings, however, the sharp spike could be diffused by data noise. The key idea behind our fuzzy bunching estimator is to identify bunching from the area of a bulge in the cumulative distribution function. The fuzzy bunching approach also avoids density estimation, which makes it easy to implement in sparse data. We provide the theoretical foundation of this approach and illustrate the advantages by using simulated and real data.