Advanced Methods, Modeling and Optimization for Financial Engineering and Risk Management

Dear Colleagues,

In portfolio management theory, the principle of separation postulates that all investors will achieve an identical optimal risk portfolio if given the same inputs. However, the realization of true optimality depends on the accuracy of technical analysis, conducted by financial engineers in predicting the rate of return of the financial assets, encompassed in the portfolio. Statistical methods for working with quantitative information, particularly about volatility and risks, are essential to achieving high accuracy in the technical analysis. Some applications of statistical methods and modeling in financial engineering include the use of Bayesian Statistics, (S)AR(F)IMA and (G)ARCH Modeling, Black–Scholes Models and Levy Models.

This Special Issue aims to collect high-quality and interesting papers considering the recent advancements in statistical and numerical methods, modeling and optimization for financial engineering and risk management.

Manuscripts providing pioneering results and achievements, solving complex problems or suggesting novel and advanced methods and techniques are warmly welcome for submission. Estimating and modeling risk and crafting an optimal portfolio are in the scope of this Special Issue. Models for establishing the relationship between the return and risk of financial instruments like the Capital Asset Pricing Model (CAPM) and the Fama and French model are attractive aspects of the research as well.

Dr. Vesela Mihova
Dr. Slavi Georgiev
Guest Editors

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