Breast cancer is one of the most common cancers among women worldwide, representing the majority of new cancer cases and cancer-related deaths according to global statistics, making it a significant public health problem in today’s society. Thus, the correct diagnosis of breast cancer and...

This study examines the relationship between several factors such as firm value, agency costs and profitability and a firms’ use of financial derivatives. The analysis differentiates between derivative assets and derivative liabilities and utilize a annual panel data set of nonfinancial firms...

Blockchain is one of the primary digital technologies utilised in the finance industry with huge future potential. This study conducts a systematic literature review of a final sample of 407 prior literature from an initial set of 1979 records for the sample period of 2013–2020 with regard to...

There is considerable hype about blockchain in almost every industry, including finance, with significant investments globally. We conduct a systematic review of 851 records and construct a final article sample of 183 for the sample period 2012 to 2020 to identify relevant factors for blockchain...

This paper applies machine learning algorithms to the modeling of realized betas for the purposes of forecasting stock systematic risk. Forecast horizons range from 1 week up to 1 month. The machine learning algorithms employed are ridge regression, decision tree learning, adaptive boosting,...

This study surveys prior literature on mergers and acquisitions (M&A) with a special focus on factors affecting M&A outcomes and valuation. In addition, this study analyses one of the largest and most controversial mergers from the Philippine Banking sector: The merger of the fifth largest bank...

The business model of monolines/bond insurers is to guarantee payments of debt issues in case of defaults by the issuer. Thus, effectively providing their high credit rating to lesser rated debt issuers for a fee. Monoline insurance provide protection for debt issues and secondary guarantees for...

This paper develops several efficient machine learning models and compare their performance in forecasting the value and direction of stock prices and indices from the ASEAN countries. Although all models adequately forecast the stock indices ranging from 40% to 95% accuracy and outperform...

We study the rise of digital footprint (DF) users in the U.S. residential mortgage market. The proportion of lenders that use a borrower's DF has witnessed remarkable growth from 6% in 2013 to 34% in 2018 in a short span – according to our analysis. We show that the use of DFs can...