Abstract
The seminal work of Mandelbrot and Fama, carried out in the 1960s, suggested the class of α-stable laws as a probabilistic model of financial assets returns. Stable distributions possess several properties which make plausible their application in the field of finance — heavy tails, excess kurtosis, domains of attraction. Unfortunately working with stable laws is very much obstructed by the lack of closed-form expressions for probability density functions and cumulative distribution functions. In the current paper we review statistical and numerical techniques which make feasible the application of stable laws in practice.
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Stoyanov, S., Racheva-Jotova, B. (2004). Numerical Methods for Stable Modeling in Financial Risk Management. In: Rachev, S.T. (eds) Handbook of Computational and Numerical Methods in Finance. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-0-8176-8180-7_8
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DOI: https://doi.org/10.1007/978-0-8176-8180-7_8
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