most citedModeling Inverse Demand Function with Explainable Dual Neural Networks

1 citations · 1 across the 6 of their papers we have counts for

collaborators

8 papers

q-fin.TR2026

Oracle-Parametrized Constant Function Market Makers: From Price Feeds to Pricing Rules

Hamed Amini, Zachary Feinstein

This paper introduces oracle-parametrized automated market makers (OP-AMMs), i.e., automated market makers whose quoted price depends jointly on the pool reserves and an external o…

math.OC2026

Extended Graphon Mean-Field Games in Discrete Time

Hamed Amini, Zhongyuan Cao, Gökçe Dayanıklı +3

In this paper, we study games involving a continuum of heterogeneous players in the discrete-time setting with finite state spaces and continuous action spaces. We introduce a new…

math.PR2023

Ruin-dependent bivariate stochastic fluid processes

Hamed Amini, Andreea Minca, Oscar Peralta

This paper presents a novel model for bivariate stochastic fluid processes that incorporate a ruin-dependent behavioral switch. Unlike typical models that assume a shared underlyin…

q-fin.CP2023★ 1 cited

Modeling Inverse Demand Function with Explainable Dual Neural Networks

Zhiyu Cao, Zihan Chen, Prerna Mishra +2

Financial contagion has been widely recognized as a fundamental risk to the financial system. Particularly potent is price-mediated contagion, wherein forced liquidations by firms…

q-fin.MF2023

Decentralized Prediction Markets and Sports Books

Hamed Amini, Maxim Bichuch, Zachary Feinstein

Prediction markets allow traders to bet on potential future outcomes. These markets exist for weather, political, sports, and economic forecasting. Within this work we consider a d…

math.PR2023

Duration-dependent stochastic fluid processes and solar energy revenue modeling

Hamed Amini, Andreea Minca, Oscar Peralta

We endow the classical stochastic fluid process with a duration-dependent Markovian arrival process (DMArP). We show that this provides a flexible model for the revenue of a solar…

math.PR2023

Stochastic Graphon Games with Jumps and Approximate Nash Equilibria

Hamed Amini, Zhongyuan Cao, Agnès Sulem

We study continuous stochastic games with heterogeneous mean field interactions and jumps on large networks and explore their limit counterparts. We introduce the graphon game mode…

math.PR2023

Ruin Probabilities for Risk Processes in Stochastic Networks

Hamed Amini, Zhongyuan Cao, Andreea Minca +1

We study multidimensional Cramér-Lundberg risk processes where agents, located on a large sparse network, receive losses form their neighbors. To reduce the dimensionality of the p…