We consider a class of partial-information portfolio optimization problems in which the drift of a risky asset is driven by two latent stochastic factors evolving at distinct time scales. We show that the filtered estimate of the latent mean-reversion level is driven by the difference between fast and slow exponential moving average (EMA)-type processes of the trailing price history, yielding a Moving Average Convergence Divergence (MACD)-type signal, along with a deterministic Volterra correction. Under logarithmic, power, and exponential utility, we derive candidate optimal strategies in explicit feedback form and establish admissibility and verification results. In particular, the results provide a mathematical foundation for the endogenous emergence of MACD-type trading signals as estimators of latent drift information contained in observed price paths.
Research
Broadly, I work in stochastic analysis and control, mean-field game theory, and their applications to mathematical finance. Current directions include stochastic control under partial observability and partially observable mean-field games.
Work in Progress
PhD Topic Proposal
Stochastic Filtering and Control in Partially Observable Diffusion Models
Optimal control theory studies the selection of admissible control policies that optimize a prescribed value functional subject to given system dynamics. In the stochastic setting, the state evolution is described by a stochastic differential equation, and admissible controls are required to be adapted to the filtration generated by the available information, ensuring that control actions depend only on past and present observations. In this proposal, we are particularly interested in systematic methods for reducing partially observed stochastic control problems to fully observable ones, using tools from stochastic filtering theory. Such problems arise when the controller has only partial information about the underlying system state and must act on the basis of indirect or noisy observations.
Undergraduate Research
C*-Algebras Generated by Weakly Quasi-Lattice Ordered Groups
In 1992 Alexandru Nica published a highly influential paper examining the C*-algebras generated by a semigroup he calls a quasi-lattice ordered group. Of particular interest to Nica were the C*-algebras generated by the Toeplitz representation of a quasi-lattice order, and a universally defined C*-algebra he calls C*(G, P). Due to the concreteness of the first C*-algebra and the universal properties of the second, Nica was interested in finding sufficient conditions to determine when these two algebras were isomorphic. He called quasi-lattice orders that satisfied this isomorphism condition amenable. Finding techniques that establish amenability is now a topic at the cutting edge of research in the study of C*-algebras of semigroups. In this dissertation, we follow the outline set out by Nica’s paper to study the C*-algebras generated by weakly quasi-lattice ordered groups. Most of the proofs throughout this dissertation required a substantial amount of original work to fill in details omitted by Nica, as he often only offered a proof outline.
Talks
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Endogenous Emergence of MACD in Partial-Information Portfolio Optimization
2026 • Quantitative Finance Conference 2026 -
Itô Calculus and Option Pricing Theory
2025 • UChicago Mathematics Summer REU -
An Explicit Construction of the Universal Nica Covariant Representation2021 • New Zealand Mathematics and Statistics Postgraduate Conference
Upcoming Conferences
Past Conferences
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Quantitative Finance Conference 2026
Jun 10 - Jun 12, 2026 • National University of Singapore, Singapore
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New Zealand Mathematics and Statistics Postgraduate Conference
Nov 16 - Nov 17, 2021 • Virtual
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Character Varieties and Topological Quantum Field Theories
Dec 2018 • University of Auckland, New Zealand
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New Zealand Mathematical Society Colloquium
Dec 4 - Dec 6, 2018 • University of Otago, New Zealand