papers

Publications (8)

q-fin.CP2026

One Other Option Pricing Scheme

Jimin Lin

We present a distinctive approach to parameterizing the risk neutral distribution. Using parsimonious and interpretable parameters, the model provides direct and localized control…

q-fin.CP2024

Neural Term Structure of Additive Process for Option Pricing

Jimin Lin, Guixin Liu

The additive process generalizes the Lévy process by relaxing its assumption of time-homogeneous increments and hence covers a larger family of stochastic processes. Recent resear…

math.OC2023

Reinforcement Learning Algorithm for Mixed Mean Field Control Games

Andrea Angiuli, Nils Detering, Jean-Pierre Fouque +2

We present a new combined \textit{mean field control game} (MFCG) problem which can be interpreted as a competitive game between collaborating groups and its solution as a Nash equ…

math.PR2026

Bootstrap Percolation in Random Graphs of Unbounded Rank

Nils Detering, Jimin Lin

Bootstrap percolation in (random) graphs is a contagion dynamic among a set of vertices with certain threshold levels. The process is started by a set of initially infected vertice…

q-fin.CP2026

Shallow Representation of Option Implied Information

Jimin Lin

Option prices encode the market's collective outlook through implied density and implied volatility. An explicit link between implied density and implied volatility translates the…

math.OC2022

Reinforcement Learning for Intra-and-Inter-Bank Borrowing and Lending Mean Field Control Game

Andrea Angiuli, Nils Detering, Jean-Pierre Fouque +2

We propose a mean field control game model for the intra-and-inter-bank borrowing and lending problem. This framework allows to study the competitive game arising between groups of…

q-fin.MF2019

On Carr and Lee's correlation immunization strategy

Jimin Lin, Matthew Lorig

In their seminal work Carr and Lee (2008) show how to robustly price and replicate a variety of claims written on the quadratic variation of a risky asset under the assumption that…

q-fin.ST2024

NeuralBeta: Estimating Beta Using Deep Learning

Yuxin Liu, Jimin Lin, Achintya Gopal

Traditional approaches to estimating beta in finance often involve rigid assumptions and fail to adequately capture beta dynamics, limiting their effectiveness in use cases like he…