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X-WR-CALNAME:Mathematical Finance
X-ORIGINAL-URL:https://www.math.ttu.edu/mathematicalfinance
X-WR-CALDESC:Events for Mathematical Finance
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DTSTART:20250309T080000
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DTSTART:20251102T070000
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DTSTART;TZID=America/Chicago:20250905T120000
DTEND;TZID=America/Chicago:20250905T130000
DTSTAMP:20260520T204232
CREATED:20250702T153825Z
LAST-MODIFIED:20250703T171328Z
UID:2029-1757073600-1757077200@www.math.ttu.edu
SUMMARY:The Bachelier implied volatility: A Malliavin calculus approach.
DESCRIPTION:Speaker: Prof. Elisa Alos\, Dept. of Economics and Business\, University of Pompeu Fabra\, Barcelona \nAbstract: We introduce the main tools of Malliavin calculus and show how to use them to study the short-end behavior of skew and curvature of the implied volatility surface. This methodology allows us to obtain general formulas in terms of Malliavin derivatives that can be applied to a wide class of models including local\, stochastic and rough volatilities. Numerical examples are given.
URL:https://www.math.ttu.edu/mathematicalfinance/event/seminar-date-reserved-2/
LOCATION:via Zoom
CATEGORIES:Fall 2025
ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2025/07/Alos.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250912T140000
DTEND;TZID=America/Chicago:20250912T150000
DTSTAMP:20260520T204232
CREATED:20250704T194330Z
LAST-MODIFIED:20250729T162609Z
UID:2040-1757685600-1757689200@www.math.ttu.edu
SUMMARY:Rough Heston model as the scaling limit of bivariate cumulative heavy-tailed INAR( ∞) processes and applications
DESCRIPTION:Speaker: Prof. Zhenyu Cui\, School of Business\, Stevens Institute of Technology\, Hoboken NJ \nAbstract: We establish a novel link between nearly unstable cumulative heavy-tailed integer-valued autoregressive (INAR(∞)) processes and the rough Heston model via discrete scaling limits. We prove that a sequence of bivariate cumulative INAR(∞) processes converge in law to the rough Heston model under appropriate scaling conditions\, providing a rigorous mathematical foundation for understanding how microstructural order flow drives macroscopic prices following rough volatility dynamics. Our theoretical framework extends the scaling limit techniques from Hawkes processes to the INAR(∞) setting.\n     Hence\, we can carry out efficient Monte Carlo simulation of the rough Heston model through simulating the corresponding approximating INAR(∞) processes\, which provides an alternative discrete-time simulation method to the Euler-Maruyama method.  Extensive numerical experiments illustrate the improved accuracy and efficiency of the proposed simulation scheme as compared to the literature\, in the valuation of European options\, and also path-dependent options such as arithmetic Asian options\, lookback options and barrier options.
URL:https://www.math.ttu.edu/mathematicalfinance/event/seminar-date-reserved-4/
LOCATION:via Zoom
CATEGORIES:Fall 2025
ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2025/07/Cui.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250919T140000
DTEND;TZID=America/Chicago:20250919T150000
DTSTAMP:20260520T204232
CREATED:20250630T162129Z
LAST-MODIFIED:20250630T162129Z
UID:1993-1758290400-1758294000@www.math.ttu.edu
SUMMARY:Recent advances in stochastic volatility jump diffusions: Calibration and exotic option pricing
DESCRIPTION:Speaker: Dr. Jean-Phillipe Aguilar\, Head of Pricing Models Audit\, Societe Generale\, Paris La Defense \nAbstract:Stochastic Volatility Jump Diffusion (SVJ) models combine the advantages of both stochastic volatility and jump models\, while addressing some of their well-known limitations; moreover\, they often calibrate well in equity and FX markets. In this talk we will focus on a particular class of SVJ models\, namely the Heston Kou Double Exponential (HKDE) model\, that has recently been investigated in detail and shown to outperform challenger models possessing similar features. We will discuss the main properties of the HKDE model as well has its calibration to single stock and FX option data\, demonstrating a better fit of the volatility smile when compared to several challenger models; we will also discuss the smile sensitivity to the HKDE model parameters as well as their econometrics interpretations. Last\, we will provide application to the pricing and analysis of several generations of exotic contracts by means of advanced Fourier pricing (PROJ method in particular). \nJoint work with Gaetano Agazzotti\, Claudio Aglieri Rinella and Justin Lars Kirkby.
URL:https://www.math.ttu.edu/mathematicalfinance/event/recent-advances-in-stochastic-volatility-jump-diffusions-calibration-and-exotic-option-pricing/
LOCATION:via Zoom
CATEGORIES:Fall 2025
ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2025/06/Aquilar-e1751300432196.jpg
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BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20250926T120000
DTEND;TZID=America/Chicago:20250926T130000
DTSTAMP:20260520T204232
CREATED:20250707T130236Z
LAST-MODIFIED:20250707T184623Z
UID:2048-1758888000-1758891600@www.math.ttu.edu
SUMMARY:Risk-aware Trading Portfolio Optimization
DESCRIPTION:Speakers: Dr. Marco Bianchetti\, Head of Market and Counterparty Risk IMA Methodologies\, Intesa Sanpaolo\, Milan\, Italy\n               Dr Fabio Vitale\, Senior Researcher\, CENTAI Institute\, Turin\, Italy \nAbstract: We investigate portfolio optimization in financial markets from a trading and risk management perspective. We term this task Risk-Aware Trading Portfolio Optimization (RATPO)\, formulate the corresponding optimization problem\, and propose an efficient Risk-Aware Trading Swarm (RATS) algorithm to solve it. The key elements of RATPO are a generic initial portfolio P\, a specific set of Unique Eligible Instruments (UEIs)\, their combination into an Eligible Optimization Strategy (EOS)\, an objective function\, and a set of constraints. RATS searches for an optimal EOS that\, added to P\, improves the objective function respecting the constraints. RATS is a specialized Particle Swarm Optimization method that leverages the parameterization of P in terms of UEIs\, enables parallel computation with a large number of particles\, and is fully general with respect to specific choices of the key elements\, which can be customized to encode financial knowledge and needs of traders and risk managers. We showcase two RATPO applications involving a real trading portfolio made of hundreds of different financial instruments\, an objective function combining both market risk (VaR) and profit & loss measures\, constraints on market sensitivities and UEIs trading costs. In the case of small-sized EOS\, RATS successfully identifies the optimal solution and demonstrates robustness with respect to hyper-parameter tuning. In the case of large-sized EOS\, RATS markedly improves the portfolio objective value\, optimizing risk and capital charge while respecting risk limits and preserving expected profits. Our work bridges the gap between the implementation of effective trading strategies and compliance with stringent regulatory and economic capital requirements\, allowing a better alignment of business and risk management objectives.
URL:https://www.math.ttu.edu/mathematicalfinance/event/seminar-date-reserved-6/
LOCATION:via Zoom
CATEGORIES:Fall 2025
ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2025/07/Bianchetti_Vitale.jpg
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