A note on Kurzweil-Henstock's anticipating non-stochastic integral

Motivated by the study of anticipating stochastic integrals using Kurzweil-Henstock approach, we use anticipating interval-point pairs (with the tag as the right-end point of the interval) in studying non-stochastic integral, which we call the Kurzweil-Henstock anticipating non-stochastic integral. We prove the integration-by-parts and integration-by-substitution results, the convergence theorems using our new setting. Using the convergence theorems, we show that the Kurzweil-Henstock's anticipating non-stochastic integral is equivalent to the Lebesgue integral.

Authors

Publication Details

Journal
Mathematica Bohemica
Published
2024-12-04
DOI
https://doi.org/10.21136/mb.2024.0028-24
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A note on Kurzweil-Henstock's anticipating non-stochastic integral

Tin Lam Toh, Yu Xin Ng
Mathematica Bohemica
Stochastic processes and financial applications
article

A note on Kurzweil-Henstock's anticipating non-stochastic integral

Tin Lam Toh, Yu Xin Ng
article en

Abstract

Motivated by the study of anticipating stochastic integrals using Kurzweil-Henstock approach, we use anticipating interval-point pairs (with the tag as the right-end point of the interval) in studying non-stochastic integral, which we call the Kurzweil-Henstock anticipating non-stochastic integral. We prove the integration-by-parts and integration-by-substitution results, the convergence theorems using our new setting. Using the convergence theorems, we show that the Kurzweil-Henstock's anticipating non-stochastic integral is equivalent to the Lebesgue integral.

Mathematica BohemicaVol. 150(3)
Openalex Percentile: Top 70%
Stochastic processes and financial applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A note on Kurzweil-Henstock's anticipating non-stochastic integral — Tin Lam Toh, Yu Xin Ng · Mathematica Bohemica (2024) | TGRS Research Map | TGRS