Financial Mathematics III

Dear Colleagues,

In recent years, financial mathematics has become an important field for mathematicians. On the one hand, the development of mathematical and probabilistic models for finance has allowed us to make progress in the classical fields of financial mathematics. Among these, we may refer to the criteria of choice for the best alternatives among investment or financing projects, as well as models for studying, for example, the dynamics of interest rates, the evaluation of bonds, portfolio theory and dynamic asset allocation, the dynamics of stock prices, and the pricing and risk assessment of many derivatives (options, futures, swaps, and a variety of other derivatives).

On the other hand, other important issues require the formulation of mathematical models for studying novel issues that have become relevant, oftentimes hot topics in financial markets. Especially the evaluation and management of the risks to which financial markets are exposed have become crucial factors. Thus, we have discovered innovative models for the evaluation of credit risks for bonds and of bank loans, and models for the assessment of sovereign risks.

In addition, new models to assess the performance of mutual funds make use of different approaches drawn from different fields—among these data envelopment analysis—and enable the study of socially responsible investments. Moreover, the application of several machine learning algorithms to different financial mathematics problems has enabled improvements in financial valuations and pricing.

The purpose of the current Special Issue is to establish a collection of articles that reflect the latest mathematical methods and models in the field of financial mathematics, creating a bridge between mathematical theory and its application to finance.

This Special Issue is a continuation of the previous, successful Special Issue “Financial Mathematics”.

Prof. Dr. Antonella Basso
Guest Editor

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• financial mathematics
• bonds and interest rates dynamics
• asset allocation and portfolio theory
• derivatives and option pricing
• credit and sovereign risks
• socially responsible investments
• performance evaluation of mutual funds
• data envelopment analysis
• machine learning algorithms
• neural networks