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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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TZID:America/Chicago
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TZOFFSETFROM:-0600
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TZNAME:CDT
DTSTART:20260308T080000
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DTSTART:20261101T070000
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DTSTART;TZID=America/Chicago:20260417T140000
DTEND;TZID=America/Chicago:20260417T150000
DTSTAMP:20260405T062651
CREATED:20251210T203233Z
LAST-MODIFIED:20260109T214820Z
UID:2528-1776434400-1776438000@www.math.ttu.edu
SUMMARY:Corruption via Mean Field Games
DESCRIPTION:Speaker: Dr. Kirill Golubnichiy\, Department of Mathematics & Statistics\, Texas Tech University \nAbstract: A new mathematical model describing the evolution of a corrupted hierarchy is derived. This model is based on mean field games theory. We consider a retrospective (inverse) problem for this model. From an applied standpoint\, this problem amounts to reconstructing the past activity of the corrupted hierarchy using present-time data for this community. We derive three new Carleman estimates. These estimates yield Hölder stability and uniqueness results for both the retrospective problem and its generalized version. The Hölder stability estimates characterize how the error in the solution of the retrospective problem depends on the error in the input data.
URL:https://www.math.ttu.edu/mathematicalfinance/event/corruption-via-mean-field-games/
LOCATION:via Zoom
CATEGORIES:Spring 2026
ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/04/Golubnichiy.jpeg
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DTSTART;TZID=America/Chicago:20260424T090000
DTEND;TZID=America/Chicago:20260424T100000
DTSTAMP:20260405T062651
CREATED:20260311T203054Z
LAST-MODIFIED:20260323T173753Z
UID:2826-1777021200-1777024800@www.math.ttu.edu
SUMMARY:Dynamic asymmetric tail dependence structure among multi-asset classes for portfolio management: Dynamic skew- copula approach
DESCRIPTION:Speaker: Dr. Kakeru Ito \nAbstract:  This study proposes AC dynamic skew-𝑡 copula with cDCC model to capture the dynamic asymmetric tail dependence structure among multi-asset classes (government bonds\, corporate bonds\, equities\, and REITs). We provide new evidence that lower tail dependence coefficients increased compared to upper ones for all pairs in the COVID-19 crash and the recent high inflation period\, indicating that the diversification effect through multi-asset investment decreased. Our empirical analysis also shows that in terms of AIC and BIC\, dynamic AC skew-𝑡 copula fits data of multi-asset classes better than other dynamic elliptical copulas because it can consider the above dependence structure characteristics. Furthermore\, out-of-sample analysis reveals that considering an asymmetry of tail dependence structure at each point with an AC dynamic skew-𝑡 copula enhances expected shortfall (ES) estimation accuracy and the performance of a minimum ES portfolio. These results indicate that capturing dynamic asymmetric tail dependence is crucial for multi-asset portfolio management.
URL:https://www.math.ttu.edu/mathematicalfinance/event/dynamic-asymmetric-tail-dependence-structure-among-multi-asset-classes-for-portfolio-management-dynamic-skew-copula-approach/
LOCATION:via Zoom
CATEGORIES:Seminars,Spring 2026
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DTSTART;TZID=America/Chicago:20260501T140000
DTEND;TZID=America/Chicago:20260501T150000
DTSTAMP:20260405T062651
CREATED:20251229T180758Z
LAST-MODIFIED:20251229T180758Z
UID:2595-1777644000-1777647600@www.math.ttu.edu
SUMMARY:Differential Beliefs in Financial Markets Under Information Constraints: A Modeling Perspective
DESCRIPTION:Speaker: Prof. Karen Grigorian\, Department of Statistics and Applied Probability\, UC Santa Barbara \nAbstract: We apply the theory of McKean-Vlasov-type SDEs to study several problems related to market efficiency in the context of partial information and partially observable financial markets: (i) convergence of reduced-information market price processes to the true price process under an increasing information flow; (ii) a specific mechanism of shrinking biases under increasing information flows; (iii) optimal aggregation of expert opinions by a trader seeking a positive alpha. All these problems are studied by means of (conditional) McKean-Vlasov-type SDEs\, Wasserstein barycenters\, KL divergence and relevant tools from convex optimization\, optimal control and nonlinear filtering. We supply the theoretical results in (i)-(iii) with concrete simulations demonstrating how the proposed models can be applied in practice to model financial markets under information constraints and the arbitrage-seeking behavior of traders with differential beliefs.
URL:https://www.math.ttu.edu/mathematicalfinance/event/differential-beliefs-in-financial-markets-under-information-constraints-a-modeling-perspective/
LOCATION:via Zoom
CATEGORIES:Spring 2026
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