Research Seminar Series in Statistics and Mathematics

Wirtschaftsuniversität Wien, Departments 4 D4.4.00811:00 - 12:10

Art Vortrag/Diskussion
Vortragende/rChrista Cuchiero (Faculty of Mathematics, University of Vienna)
Veranstalter Institut für Statistik und Mathematik
Kontakt katrin.artner@wu.ac.at

Christa Cuchiero (Faculty of Mathe­ma­tics, Univer­sity of Vienna) about "Contem­porary stochastic vola­ti­lity mode­ling - theory and empi­rics"

The Insti­tute for Statis­tics and Mathe­ma­tics (Depart­ment of Finance, Accoun­ting and Statis­tics) cordi­ally invites ever­yone inte­rested to attend the talks in our Rese­arch Seminar Series, where inter­na­tio­nally renowned scho­lars from leading univer­si­ties present and discuss their (working) papers.

The list of talks for the winter term 2018/19 is avail­able via the follo­wing link: https://www.wu.ac.at/en/stat­math/resse­minar

Stochastic vola­ti­lity mode­ling has been in the center of finance and econo­metrics since the ground­brea­king results of Black & Scholes and Merton on their famous deter­mi­nistic vola­ti­lity model. It is a very natural approach to resolve the short­co­m­ings of the Black-­Scho­le­s-­Merton model and to match both time series and option data much more accu­ra­tely. In the last few years, the by now clas­sical conti­nuous time stochastic vola­ti­lity models based on low dimen­sional diffu­sions, e.g. the Heston or the SABR model, have been chal­lenged and might be fully replaced by two modern deve­lop­ments, namely rough vola­ti­lity and local stochastic vola­ti­lity.
The rough vola­ti­lity para­digm asserts that the trajec­to­ries of assets' vola­ti­lity are rougher than Brow­nian motion, a revo­lu­tio­nary perspec­tive that has radi­cally changed certain persis­tent para­digms. It considers vola­ti­lity as stochastic Volterra process and provides a universal approach to capture econo­metric and micro­struc­tural foun­da­tions of markets.
Rough vola­ti­lity is comple­mented by local stochastic vola­ti­lity which combines clas­sical stochastic vola­ti­lity with perfect cali­bra­tion to the implied vola­ti­lity smiles or skews, a theo­re­ti­cally and prac­tically still very intri­cate task. In this talk we provide a novel infi­nite dimen­sional point of view on both direc­tions. It allows to dissolve a generic non-­Mar­ko­va­nity of the at first sight natu­rally low dimen­sional vola­ti­lity process. This approach enables in parti­cular to treat the chal­len­ging problem of multi­va­riate rough cova­ri­ance models for more than one asset. We also consider (non-­pa­ra­metric) esti­ma­tion tech­ni­ques and tread new paths to cali­bra­tion by using machine learning methods.

Kindly note that on November 16 two talks are sche­duled at our insti­tute:
9:00 – 10:10  Clara Grazian (Univer­sity of Oxford)
11:00 – 12:10  Christa Cuchiero (Univer­sity of Vienna)

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