Targeting Predictors Via Partial Distance Correlation With Applications to Financial Forecasting

Author(s):  
Kashif Yousuf ◽  
Yang Feng
1991 ◽  
Author(s):  
WENDY BROCK ◽  
STEPHEN CASSIDY

2019 ◽  
Vol 118 (9) ◽  
pp. 28-34
Author(s):  
Dr P. Govindasamy ◽  
Dr.H. Premraj

Financial Planning and Forecasting is the estimation of value of a variable or set of variables at some future point. A Financial forecasting exercise is usually carried out in order to provide an aid to decision – making and planning of any line of business for future developments. This paper focuses insurance segments and tailored all the key areas of attention are such as assets, liabilities, marketing, human resources, expenditures, digitalization and technology inclusion, etc., all in one term called as wealth maximization. Financial planning and forecasting represents a blueprint of what a firm proposes to do in the future. So, naturally planning over such horizon tends to be fairly in aggregative terms. We need to focus on common elements which include economic assumptions, target forecast, proforma statements, asset requirements and the mode of financing the investments and so on. A financial plan can also be an investment plan, which allocates savings to various assets or projects expected to produce future income, such as a new business or product line, shares in an existing business. Financial forecast and financial plan can also refer to an annual projection of income and expenses for a company, division or department. This can also be an estimation of cash needs and a decision on how to raise the funds, such as through borrowing or issuing additional shares in a company. Forecasting is also used by outsiders to value companies and their securities. This is the aggregative perspective of the whole firm, rather than looking at individual projects. Growth is a key theme behind financial forecasting, so growth should not be the underlying goal of corporation – creating shareholder value is enabled through corporate growth.


2012 ◽  
Vol 10 (3) ◽  
pp. 192-201 ◽  
Author(s):  
Ricardo de A. Araújo ◽  
Adriano L. I. Oliveira ◽  
Sérgio Soares ◽  
Silvio Meira

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 208
Author(s):  
Javier Brugés Martelo ◽  
Jan Lundgren ◽  
Mattias Andersson

The manufacturing of high-quality extruded low-density polyethylene (PE) paperboard intended for the food packaging industry relies on manual, intrusive, and destructive off-line inspection by the process operators to assess the overall quality and functionality of the product. Defects such as cracks, pinholes, and local thickness variations in the coating can occur at any location in the reel, affecting the sealable property of the product. To detect these defects locally, imaging systems must discriminate between the substrate and the coating. We propose an active full-Stokes imaging polarimetry for the classification of the PE-coated paperboard and its substrate (before applying the PE coating) from industrially manufactured samples. The optical system is based on vertically polarized illumination and a novel full-Stokes imaging polarimetry camera system. From the various parameters obtained by polarimetry measurements, we propose implementing feature selection based on the distance correlation statistical method and, subsequently, the implementation of a support vector machine algorithm that uses a nonlinear Gaussian kernel function. Our implementation achieves 99.74% classification accuracy. An imaging polarimetry system with high spatial resolution and pixel-wise metrological characteristics to provide polarization information, capable of material classification, can be used for in-process control of manufacturing coated paperboard.


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