This paper contributes to the existing literature on the analysis of spatial time series
presenting a new clustering algorithm called COFUST, ie COpula-based FUzzy clustering …

This paper proposes a classification method for financial time series that addresses the
significant issue of noise. The proposed method combines improved complete ensemble …

We define a new distance measure for ranking data using a mixture of copula functions. Our
distance measure evaluates the dissimilarity of subjects' ranking preferences to segment …

This dissertation examines novel applications of network and discrete optimization models
in three settings: 1) a social network analysis of stock prices; 2) personnel planning for large …

It is very important to find some new distance measurement methods to estimate the
correlation of the return of stocks because that the traditional distance measurement …

This thesis is about the concept of diversification and its measurement in portfolio theory.
Diversification is one of the major components of portfolio theory. It helps to reduce or …

The overarching theme of this thesis revolves around employing methodologies typically
beyond the scope of portfolio optimization and their integration with portfolio strategies. The …

In this thesis, we delve into two key financial aspects. First, we analyze the stability of stock
clusters using the S&P 500 and Nikkei 225 constituents, employing various clustering …

The thesis focuses on applying F-transform theory to analyse the relations among multiple
time series and provide a predictive linguistic description for them. This objective is …