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BEGIN:VEVENT
DTSTAMP:20260729T153112
DTSTART;TZID=America/Detroit:20260902T160000
DTEND;TZID=America/Detroit:20260902T170000
SUMMARY:Workshop / Seminar:A New Approach for the Continuous Time Kyle-Back Strategic Insider Equilibrium Problem
DESCRIPTION:In this talk\, we consider a continuous-time Kyle-Back model which is a game between an insider and a market maker. The existing literature typically focuses on constructing equilibria with a PDE approach\, which requires certain Markovian structures. We characterize all equilibria through a coupled system of forward-backward SDEs. In particular\, when the time duration is small\, we show that the FBSDE is well-posed\, and therefore the game has a unique equilibrium. Moreover\, this unique equilibrium may be non-Markovian and thus not attainable via the PDE approach. We next study the set value of the game\, which roughly speaking is the set of insider's values over all equilibria and thus is by nature unique. Finally\, we characterize the set value through a level set of a certain standard HJB equation.\nIn the second part of the talk\, we apply the new approach to the Kyle-Back model with dynamic legal risk and large numbers of noise traders. In this setting\, the insider chooses a strategy that conceals his identity within a large volume of surrounding trades and concentrates on medium-sized trades.  We establish an intensity-based mathematical framework for explaining the interconnections between insider trading and stealth trading. When the number of noise traders becomes large\, the price impact of the insider asymptotically vanishes\, and consequently the stochastic game becomes deterministic optimizations\, which also carry implications for regulatory investigations and sanctions.\n\nThe results above include the joint work with Weixuan Xia and with Jianfeng Zhang.
UID:149579-21906721@events.umich.edu
URL:https://events.umich.edu/event/149579
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:East Hall - 1360
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260727T105626
DTSTART;TZID=America/Detroit:20260909T160000
DTEND;TZID=America/Detroit:20260909T170000
SUMMARY:Workshop / Seminar:TBA
DESCRIPTION:TBA
UID:149581-21906722@events.umich.edu
URL:https://events.umich.edu/event/149581
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:East Hall - 1360
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260727T110442
DTSTART;TZID=America/Detroit:20260916T160000
DTEND;TZID=America/Detroit:20260916T170000
SUMMARY:Workshop / Seminar:TBA
DESCRIPTION:TBA
UID:149582-21906724@events.umich.edu
URL:https://events.umich.edu/event/149582
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:East Hall - 1360
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260727T104702
DTSTART;TZID=America/Detroit:20260923T160000
DTEND;TZID=America/Detroit:20260923T170000
SUMMARY:Workshop / Seminar:Buying Time: Optimal Service Purchase and Retirement Timing in Defined Benefit Plans
DESCRIPTION:We study retirement timing decisions in a defined benefit (DB) pension plan with a service-purchase\noption. An employee who would otherwise retire at a fixed time T may elect to purchase L additional\nyears of service and retire early. Earlier retirement provides additional leisure but requires an upfront\npayment and typically results in a reduced post-retirement income stream. We model this trade-off in\na continuous-time retirement framework by allowing the employee to choose L to maximize the value\nof wealth and leisure at retirement in both deterministic and life-contingent settings. Our model\ncaptures a common feature of public pension systems: early retirement is often accompanied by both\nan upfront cost and a permanent reduction in benefits. We show that this structure yields tractable\nand intuitive results in several benchmark cases\, including settings without mortality risk and settings\nwith mortality risk under simplifying assumptions. In more general cases\, we characterize optimal\nbehavior through comparative statics and numerical examples. A key insight is that the interaction\nbetween the finite-horizon value of leisure and the lifetime cost embedded in pension pricing can\ngenerate a range of behaviors\, including monotone strategies and interior optima. While many results\nalign with economic intuition\, others require more careful interpretation. We also extend the model to\nallow for dynamic decision-making via a multi-period service-purchase option\, solved by backward\ninduction. The results provide insight into optimal retirement timing and the role of plan design in\nshaping participant behavior. This is joint work with David Kausch and Virginia Young.
UID:149578-21906720@events.umich.edu
URL:https://events.umich.edu/event/149578
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:East Hall - 1360
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260729T153011
DTSTART;TZID=America/Detroit:20260930T160000
DTEND;TZID=America/Detroit:20260930T170000
SUMMARY:Workshop / Seminar:Quantitative propagation of chaos and universality for asymmetric Langevin spin glass dynamics
DESCRIPTION:We obtain quantitative estimates on quenched propagation of chaos for Langevin spin glass dynamics with i.i.d. disorder. Prior work in the case of Gaussian disorder established the qualitative convergence of the law of a single spin to a deterministic McKean--Vlasov limit. We prove convergence rates in expected Wasserstein distance and quantitative concentration rates for Lipschitz observables under the assumption that the disorder satisfies the T_2 inequality. The proof uses a coupling argument\, together with techniques from concentration of measure\, filtering theory\, and Malliavin calculus.
UID:149663-21906910@events.umich.edu
URL:https://events.umich.edu/event/149663
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:East Hall - 1360
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260407T124520
DTSTART;TZID=America/Detroit:20261007T160000
DTEND;TZID=America/Detroit:20261007T170000
SUMMARY:Workshop / Seminar:Robust and Risk-Sensitive Acceleration in Gradient Methods
DESCRIPTION:First-order methods such as gradient descent (GD) are foundational in optimization. In unconstrained problems with exact gradients\, momentum-based methods—most notably Nesterov’s accelerated gradient descent (AGD) and Polyak’s heavy-ball (HB) method—achieve faster convergence by improving dependence on the condition number. However\, this acceleration comes at a cost: momentum amplifies gradient noise\, making these methods less robust than GD under standard parameter choices and requiring more accurate gradient estimates to attain comparable accuracy. Similar challenges arise in convex and nonconvex min–max optimization.\nMotivated by applications in machine learning\, this talk studies unconstrained and min–max optimization under deterministic\, unbiased stochastic\, and biased stochastic gradient noise. I will present new algorithms that achieve optimal robustness against different noise types\, using control-theoretic tools such as the H_2​ norm\, the H_∞​ norm\, and the risk-sensitivity index\, together with coherent risk measures. I will also discuss worst-case noise constructions and high-probability convergence guarantees. This perspective builds a bridge between optimization and robust control theory and enables the design of noise-robust and risk-sensitive accelerated methods.\nRepresentative Publications:\nM. Gürbüzbalaban\, Y. Syed\, N. S. Aybat\, Accelerated gradient methods with biased gradient estimates: Risk sensitivity\, high-probability guarantees\, and large deviation bounds\, Journal of Nonlinear and Variational Analysis\, 2026 (Special Issue). https://jnva.biemdas.com/archives/2927\nM. Gürbüzbalaban\, Robustly Stable Accelerated Momentum Methods with a Near-Optimal L_2​ Gain and H_∞​ Performance\, Mathematics of Operations Research\, 2025.\nhttps://pubsonline.informs.org/doi/abs/10.1287/moor.2023.0321\nB. Can and M. Gürbüzbalaban\, Entropic risk-averse generalized momentum methods\, Optimization Methods and Software\, 2025. https://www.tandfonline.com/doi/abs/10.1080/10556788.2025.2549356
UID:141373-21888712@events.umich.edu
URL:https://events.umich.edu/event/141373
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:East Hall - 1360
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260608T221120
DTSTART;TZID=America/Detroit:20261028T160000
DTEND;TZID=America/Detroit:20261028T170000
SUMMARY:Workshop / Seminar:TBA
DESCRIPTION:TBA
UID:148617-21904532@events.umich.edu
URL:https://events.umich.edu/event/148617
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:East Hall - 1360
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260727T104513
DTSTART;TZID=America/Detroit:20261202T160000
DTEND;TZID=America/Detroit:20261202T170000
SUMMARY:Workshop / Seminar:TBA
DESCRIPTION:TBA
UID:149576-21906718@events.umich.edu
URL:https://events.umich.edu/event/149576
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:East Hall - 1360
CONTACT:
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260727T104405
DTSTART;TZID=America/Detroit:20261209T160000
DTEND;TZID=America/Detroit:20261209T170000
SUMMARY:Workshop / Seminar:THE HEREDITARY LAWS OF LARGE NUMBERS
DESCRIPTION:The celebrated theorem of Komlos (1967) establishes L^1-boundedness as a sufficient condition for a sequence of measurable functions on a probability space to contain a subsequence along which\, and along whose every further subsequence (“hereditarily”)\, the Cesaro averages converge to a “randomized mean” in the spirit of the Strong law of Large Numbers. We provide conditions not only sufficient\, but also necessary\, for this result\, as well as for the hereditary analogues of the Weak Law of Large Numbers\, of the Hsu-Robbins-Erdos Law of Large Numbers\, and of the Law of the Iterated Logarithm. \n\nJoint work with I. Berkes (Budapest) and W. Schachermayer (Vienna).
UID:149577-21906719@events.umich.edu
URL:https://events.umich.edu/event/149577
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics,Statistics
LOCATION:East Hall - 1360
CONTACT:
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