To reduce risk, investors seek assets that have high expected return and are unlikely to move in tandem. Correlation measures are generally used to quantify the connections between equities. The 2008 financial crisis, and its aftermath, demonstrated the need for a better way to quantify these connections. We present a machine learning-based method to build a connectedness matrix to address the ...

Correlated binary data are common in biomedical studies. Such data can be analyzed using Liang and Zeger's generalized estimating equations (GEE) approach. An attractive point of the GEE approach is that one can use a misspecified working correlation matrix, such as the working independence model (i.e., the identity matrix), and draw (asymptotically) valid statistical inference by using the so-...

In this paper, we suggest an algorithm to enhance the accuracy of sensor measurements representing camera parameters. The process proposed is based solely on a pair of wide baseline (or sparse view) images. We use the so-called JUDOCA operator to extract junctions. This operator produces junctions in terms of locations as well as orientations. Such an information is used to estimate an affine t...

Introduction: Considering the increasing trend of the elderly population in Iran, attention paid to this critical phase, both socially and psychologically, is essential in improving their quality of life. The present study aimed to investigate prediction of quality of life - based on personality traits and spiritual intelligence in the elderly. Methods: This correlational study  carried out on...

agricultural activities are risky activities. in these activities, various natural, social and economic risks have created fragile and vulnerable situation for producers. price risk in agricultural products has caused financial problems for many producers and farmers. to deal with these price risks and price fluctuations, there are varieties of tools. this paper focused on futures markets instr...