Excel to Cloud: Migrating Legacy Trader Tools to Scalable Java & Python Applications

Many trading desks across the financial industry still rely heavily on Excel-based tools for pricing, risk assessment, and reporting workflows. While these spreadsheets offer flexibility and familiarity, they present challenges in scalability, collaboration, version control, and integration with modern trading infrastructure. This paper presents a cloud-native migration framework that transforms trader-centric Excel tools into robust, scalable applications using Java and Python. The framework incorporates modular microservices, RESTful APIs, AWS services, and real-time data processing. It also addresses migration challenges such as formula translation, data validation, and end-user adoption. The resulting system improves performance, auditability, and maintainability while retaining the usability traders expect.

Institutions

Publication Details

Journal
International Journal of Multidisciplinary Research in Science, Engineering and Technology.
Published
2025-03-30
DOI
https://doi.org/10.15680/ijmrset.2025.0803341
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Excel to Cloud: Migrating Legacy Trader Tools to Scalable Java & Python Applications

International Journal of Multidisciplinary Research in Science, Engineering and Technology.
FinTech, Crowdfunding, Digital Finance
article

Excel to Cloud: Migrating Legacy Trader Tools to Scalable Java & Python Applications

article en

Abstract

Many trading desks across the financial industry still rely heavily on Excel-based tools for pricing, risk assessment, and reporting workflows. While these spreadsheets offer flexibility and familiarity, they present challenges in scalability, collaboration, version control, and integration with modern trading infrastructure. This paper presents a cloud-native migration framework that transforms trader-centric Excel tools into robust, scalable applications using Java and Python. The framework incorporates modular microservices, RESTful APIs, AWS services, and real-time data processing. It also addresses migration challenges such as formula translation, data validation, and end-user adoption. The resulting system improves performance, auditability, and maintainability while retaining the usability traders expect.

International Journal of Multidisciplinary Research in Science, Engineering and Technology.Vol. 08(03)
Macquarie University (AU)
Openalex Percentile: Top 88%
FinTech, Crowdfunding, Digital Finance
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.