1 citations · 1 across the 7 of their papers we have counts for
7 papers
Forecasting High Frequency Order Flow Imbalance
Aditya Nittur Anantha, Shashi Jain
Market information events are generated intermittently and disseminated at high speeds in real-time. Market participants consume this high-frequency data to build limit order books…
Neural Networks for Portfolio-Level Risk Management: Portfolio Compression, Static Hedging, Counterparty Credit Risk Exposures and Impact on Capital Requirement
Vikranth Lokeshwar Dhandapani, Shashi Jain
In this paper, we present an artificial neural network framework for portfolio compression of a large portfolio of European options with varying maturities (target portfolio) by a…
Optimizing Neural Networks for Bermudan Option Pricing: Convergence Acceleration, Future Exposure Evaluation and Interpolation in Counterparty Credit Risk
Vikranth Lokeshwar Dhandapani, Shashi Jain
This paper presents a Monte-Carlo-based artificial neural network framework for pricing Bermudan options, offering several notable advantages. These advantages encompass the effici…
Non-Parametric Estimation of Multi-dimensional Marked Hawkes Processes
Sobin Joseph, Shashi Jain
An extension of the Hawkes process, the Marked Hawkes process distinguishes itself by featuring variable jump size across each event, in contrast to the constant jump size observed…
Precision versus Shrinkage: A Comparative Analysis of Covariance Estimation Methods for Portfolio Allocation
Sumanjay Dutta, Shashi Jain
In this paper, we perform a comprehensive study of different covariance and precision matrix estimation methods in the context of minimum variance portfolio allocation. The set of…
A neural network based model for multi-dimensional nonlinear Hawkes processes
Sobin Joseph, Shashi Jain
This paper introduces the Neural Network for Nonlinear Hawkes processes (NNNH), a non-parametric method based on neural networks to fit nonlinear Hawkes processes. Our method is su…