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Introduction to QuantLib training with Luigi Ballabio

19-21 October, London

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Title: Professor

Short Description: Current research interests: Volatility modeling, market impact, and optimal execution.

Institution: Baruch College

Department: Department of Mathematics

Special Academic Interests: , ,

Location: New York, USA

SSRN Author Page: link

Is this Member on the AGENDA team?: No

Joined: June 25th, 2011

Activity

Jim Gatheral wrote a new blog post titled REVISION: Implied Volatility from Local Volatility: A Path Integral Approach

Assuming local volatility, we derive an exact Brownian bridge representation for the transition density; an exact expression for the transition density in terms of a path integral then follows. By Taylor-expanding around a certain path, we obtain a generalization of the heat kernel expansion of the density which coincides with the classical one in the time-homogeneous case, but is more accurate and natural in the time inhomogeneous case. As a further application of our path integral representation, we obtain an improved most-likely-path approximation for implied volatility in terms of local...
(24 days ago)

Jim Gatheral wrote a new blog post titled New: Pricing Under Rough Volatility

From an analysis of the time series of volatility using recent high frequency data, Gatheral, Jaisson and Rosenbaum previously showed that log-volatility behaves essentially as a fractional Brownian motion with Hurst exponent H of order 0.1, at any reasonable time scale. The resulting Rough Fractional Stochastic Volatility (RFSV) model is remarkably consistent with financial time series data. We now show how the RFSV model can be used to price claims on both the underlying and integrated volatility. We analyze in detail a simple case of this model, the rBergomi model. In particular, we...
(24 days ago)

Jim Gatheral wrote a new blog post titled New: Volatility is Rough

Estimating volatility from recent high frequency data, we revisit the question of the smoothness of the volatility process. Our main result is that log-volatility behaves essentially as a fractional Brownian motion with Hurst exponent H of order 0.1, at any reasonable time scale. This leads us to model the log-volatility as a fractional Brownian motion with H
(118 days ago)

About me:

Jim Gatheral worked at Bank of America and Bankers Trust before heading the Equity Quantitative Analytics group at Merrill Lynch in 1996, where he was a managing director for 17 years. In 1998 he became a fellow of the Masters Program of Mathematics in Finance at the Courant Institute of Mathematical Sciences of New York University. In March 2010 Jim assumed a tenured full professor position at the Financial Engineering Masters Program at Baruch College where he is teaching volatility surface modeling and market microstructure.