Portfolio selection and risk management are very actively studied topics in quantitative finance and applied statistics. They are closely related to the dependency structure of portfolio assets or risk factors. The correlation structure across assets and opposite tail movements are essential to...

We analyse a sample of funds and other securities each assigned a total rating score by an unknown expert entity. The scores are based on a number of risk and complexity factors, each assigned a category (factor score) of Low, Medium, or High by the expert entity. A principal component analysis...

Classical asset allocation methods have assumed that the distribution of asset returns is smooth, well behaved with stable statistical moments over time. The distribution is assumed to have constant moments with e.g., Gaussian distribution that can be conveniently parameterised by the first two...

In this study, we develop a two-step asset allocation strategy that identifies the tail risk of a benchmark asset and uses multi-moment dynamic portfolio selection to account for possible conditional non-normality of portfolio returns. The TEDAS - Tail Event Asset Allocation strategy is based on...

We analyse a sample of funds and other securities each assigned a total rating score by an unknown expert entity. The scores are based on a number of risk and complexity factors, each assigned a category (factor score) of Low, Medium, or High by the expert entity. A principal component analysis...

"This book is the first part of Applications and Trends in Fintech, which serves as a comprehensive guide to the advanced topics in fintech, including the deep learning and natural language processing algorithms, blockchain design thinking, token economics, cybersecurity, cloud computing and...