Implied Hurst Exponent And Fractional Implied Volatility
Download Implied Hurst Exponent And Fractional Implied Volatility PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Implied Hurst Exponent And Fractional Implied Volatility book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Implied Hurst Exponent and Fractional Implied Volatility
Two methods to derive Hurst exponent from option prices are proposed in this paper. They are based on fractional Brownian market setting. The first method is to use fractional Black-Scholes model inversely to derive implied Hurst exponent. The second one depends on no specific option pricing model. It is a model-free approach which is applicable as long as asset price evolves with on jumps. The difficulty in deriving implied information from fractional Brownian market is due to the fact that both Hurst exponent and volatility are unobservable. So they can be derived as a whole from single-period option prices, but can hardly be separated from each other. In this paper, a method that integrates option prices of different maturities is suggested to solve this problem. We also make a comparison between volatility in classical Brownian market and that in fractional Brownian market, which reveals that variance term structures are fitted differently in two settings. Based on this result, we suggest two potential applications of implied Hurst exponent in this paper.
Mathematical and Statistical Methods for Actuarial Sciences and Finance
The cooperation and contamination among mathematicians, statisticians and econometricians working in actuarial sciences and finance are improving the research on these topics and producing numerous meaningful scientific results. This volume presents new ideas in the form of four- to six-page papers presented at the International Conference MAF2022 – Mathematical and Statistical Methods for Actuarial Sciences and Finance. Due to the COVID-19 pandemic, the conference, to which this book is related, was organized in a hybrid form by the Department of Economics and Statistics of the University of Salerno, with the partnership of the Department of Economics of Cà Foscari University of Venice, and was held from 20 to 22 April 2022 in Salerno (Italy) MAF2022 is the tenth edition of an international biennial series of scientific meetings, started in 2004 on the initiative of the Department of Economics and Statistics of the University of Salerno. It has established itself internationally with gradual and continuous growth and scientific enrichment. The effectiveness of this idea has been proven by the wide participation in all the editions, which have been held in Salerno (2004, 2006, 2010, 2014, 2022), Venice (2008, 2012 and 2020 online), Paris (2016) and Madrid (2018). This book covers a wide variety of subjects: artificial intelligence and machine learning in finance and insurance, behavioural finance, credit risk methods and models, dynamic optimization in finance, financial data analytics, forecasting dynamics of actuarial and financial phenomena, foreign exchange markets, insurance models, interest rate models, longevity risk, models and methods for financial time series analysis, multivariate techniques for financial markets analysis, pension systems, portfolio selection and management, real-world finance, risk analysis and management, trading systems, and others. This volume is a valuable resource for academics, PhD students, practitioners, professionals and researchers. Moreover, it is also of interest to other readers with quantitative background knowledge.
Fractional Calculus and Fractional Processes with Applications to Financial Economics
Fractional Calculus and Fractional Processes with Applications to Financial Economics presents the theory and application of fractional calculus and fractional processes to financial data. Fractional calculus dates back to 1695 when Gottfried Wilhelm Leibniz first suggested the possibility of fractional derivatives. Research on fractional calculus started in full earnest in the second half of the twentieth century. The fractional paradigm applies not only to calculus, but also to stochastic processes, used in many applications in financial economics such as modelling volatility, interest rates, and modelling high-frequency data. The key features of fractional processes that make them interesting are long-range memory, path-dependence, non-Markovian properties, self-similarity, fractal paths, and anomalous diffusion behaviour. In this book, the authors discuss how fractional calculus and fractional processes are used in financial modelling and finance economic theory. It provides a practical guide that can be useful for students, researchers, and quantitative asset and risk managers interested in applying fractional calculus and fractional processes to asset pricing, financial time-series analysis, stochastic volatility modelling, and portfolio optimization. - Provides the necessary background for the book's content as applied to financial economics - Analyzes the application of fractional calculus and fractional processes from deterministic and stochastic perspectives