This study utilizes machine learning techniques, notably classification and regression trees
(CART) and support vector regression (SVR), to predict corporate credit ratings. While SVR …

Prior studies indicate that rating agencies have adopted more stringent rating criteria over
time. In this paper, we hypothesize that improvements in rating accuracy can explain some …

This paper presents a regime-switching normal tempered stable (NTS) firm value model for
pricing default risk, based on an N-state continuous Markov chain process and an …

We extend a recent score-driven clustering model by considering the possibility of
unbalanced panels for the dependent variables. We apply the model to a random sample of …

In accord with international transfer pricing regulations, the borrower's creditworthiness is
the main factor to be reflected in valuation of cross-border loan transactions between …

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 …

In many retail organisations, transactional Net Promoter Score (tNPS) is used to quantify
customer satisfaction. It is also one of the alternative measures used in customer retention …

Corporate Rating is one of the tools of Signaling Theory, expected to provide clear and
standardized signals of a company's financial health and credit risk. However, according to …