papers

Publications (14)

q-fin.MF2024

Estimation of VaR with jump process: application in corn and soybean markets

Minglian Lin, Indranil SenGupta, William Wilson

Value at Risk (VaR) is a quantitative measure used to evaluate the risk linked to the potential loss of investment or capital. Estimation of the VaR entails the quantification of p…

q-fin.PR2024

Some asymptotics for short maturity Asian options

Humayra Shoshi, Indranil SenGupta

Most of the existing methods for pricing Asian options are less efficient in the limit of small maturities and small volatilities. In this paper, we use the large deviations theory…

q-fin.MF2022

Analysis of stock index with a generalized BN-S model: an approach based on machine learning and fuzzy parameters

Xianfei Hui, Baiqing Sun, Hui Jiang +1

In this paper we implement a combination of data-science and fuzzy theory to improve the classical Barndorff-Nielsen and Shephard model, and implement this to analyze the S&P 500 i…

q-fin.ST2020

Refinements of Barndorff-Nielsen and Shephard model: an analysis of crude oil price with machine learning

Indranil SenGupta, William Nganje, Erik Hanson

A commonly used stochastic model for derivative and commodity market analysis is the Barndorff-Nielsen and Shephard (BN-S) model. Though this model is very efficient and analytical…

q-fin.ST2023

Stochastic volatility modeling of high-frequency CSI 300 index and dynamic jump prediction driven by machine learning

Xianfei Hui, Baiqing Sun, Indranil SenGupta +2

This paper models stochastic process of price time series of CSI 300 index in Chinese financial market, analyzes volatility characteristics of intraday high-frequency price data. I…

q-fin.MF2021

Fractional Barndorff-Nielsen and Shephard model: applications in variance and volatility swaps, and hedging

Nicholas Salmon, Indranil SenGupta

In this paper, we introduce and analyze the fractional Barndorff-Nielsen and Shephard (BN-S) stochastic volatility model. The proposed model is based upon two desirable properties…