activity
20242026
collaborators

7 papers

stat.AP2026

Spillover-Informed Network Architecture for Global Volatility Forecasting

Neha Gupta, Nishit Soni, Aditya Maheshwari

Spillover of volatility shocks across borders during turbulent periods makes accurate equity market volatility forecasts especially critical for risk management, derivatives pricin…

cs.LG2026

NeuroMem-FHP: A Likelihood-Free Deep Learning Framework for Parameter Estimation of Fractional Hawkes Process

Neha Gupta, Aditya Maheshwari

In this paper, we propose deep learning based NeuroMem-FHP framework for estimating the parameters of the fractional Hawkes process (FHP), a self-exciting point process that captur…

cs.LG2025

NeuroMemFPP: A recurrent neural approach for memory-aware parameter estimation in fractional Poisson process

Neha Gupta, Aditya Maheshwari

In this paper, we propose a recurrent neural network (RNN)-based framework for estimating the parameters of the fractional Poisson process (FPP), which models event arrivals with m…

math.PR2025

Noncentral moderate deviations for time-changed multivariate Lévy processes with linear combinations of inverse stable subordinators

Neha Gupta, Claudio Macci

The term noncentral moderate deviations is used in the literature to mean a class of large deviation principles that, in some sense, fills the gap between the convergence in probab…

math.PR2025

Geometrical subordinated Poisson processes and its extensions

Neha Gupta, Aditya Maheshwari, Dheeraj Goyal

In this paper, we study a generalized version of the Poisson-type process by time-changing it with the geometric counting process. Our work generalizes the work done by Meoli (2023…

math.PR2024

Hawkes process with tempered Mittag-Leffler kernel

Neha Gupta, Aditya Maheshwari

In this paper, we propose an extension of the Hawkes process by incorporating a kernel based on the tempered Mittag-Leffler distribution. This is the generalization of the work pre…

math.PR2024

Tempered Fractional Hawkes Process and Its Generalization

Neha Gupta, Aditya Maheshwari

Hawkes process (HP) is a point process with a conditionally dependent intensity function. This paper defines the tempered fractional Hawkes process (TFHP) by time-changing the HP w…