Financial optimization modeling on asset liability management with weighted goal programming
Asset Liability Management (ALM) can be overseen using financial ratios derived from financial statements. These statements provide a comprehensive picture of a company's status and necessitate analysis to evaluate performance. This research aims to analyze financial ratios to describe the fina...
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2024
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2-s2.0-85205767951 Wijayanti H.; Supian S.; Chaerani D.; Shuib A. Financial optimization modeling on asset liability management with weighted goal programming 2024 Decision Science Letters 13 4 10.5267/j.dsl.2024.7.004 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205767951&doi=10.5267%2fj.dsl.2024.7.004&partnerID=40&md5=52760bafb390c493d6c6f2fa18cc1f48 Asset Liability Management (ALM) can be overseen using financial ratios derived from financial statements. These statements provide a comprehensive picture of a company's status and necessitate analysis to evaluate performance. This research aims to analyze financial ratios to describe the financial condition, measure business development over time, and evaluate the achievement of the company's objectives. An optimization analysis of financial ratios is performed using the Weighted Goal Programming (WGP) model, which addresses multiple objectives by applying weights based on their priorities. The Best-Worst Method (BWM) was used to determine the priority weights of deviation variables from each financial ratio target. Financial ratios were selected based on their impact on profit using factor analysis. The constructed WGP model aims to minimize deviations in Return on Assets, Operating Ratios, Operating Income Ratio, Total Assets Turnover, and Current Ratio. Computational calculations to solve the WGP model are performed using Python, with pseudocode provided. A case study on a company in the garment and textile sector was conducted and found that the Operating Ratio, Return on Assets, Operating Income Ratio, and Current Ratio still need improvement by developing strategies to achieve the targets. Sensitivity analysis was also employed to assess the resilience of the model in response to alterations in data. © 2024 by the authors; licensee Growing Science, Canada. Growing Science 19295804 English Article All Open Access; Gold Open Access |
author |
Wijayanti H.; Supian S.; Chaerani D.; Shuib A. |
spellingShingle |
Wijayanti H.; Supian S.; Chaerani D.; Shuib A. Financial optimization modeling on asset liability management with weighted goal programming |
author_facet |
Wijayanti H.; Supian S.; Chaerani D.; Shuib A. |
author_sort |
Wijayanti H.; Supian S.; Chaerani D.; Shuib A. |
title |
Financial optimization modeling on asset liability management with weighted goal programming |
title_short |
Financial optimization modeling on asset liability management with weighted goal programming |
title_full |
Financial optimization modeling on asset liability management with weighted goal programming |
title_fullStr |
Financial optimization modeling on asset liability management with weighted goal programming |
title_full_unstemmed |
Financial optimization modeling on asset liability management with weighted goal programming |
title_sort |
Financial optimization modeling on asset liability management with weighted goal programming |
publishDate |
2024 |
container_title |
Decision Science Letters |
container_volume |
13 |
container_issue |
4 |
doi_str_mv |
10.5267/j.dsl.2024.7.004 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205767951&doi=10.5267%2fj.dsl.2024.7.004&partnerID=40&md5=52760bafb390c493d6c6f2fa18cc1f48 |
description |
Asset Liability Management (ALM) can be overseen using financial ratios derived from financial statements. These statements provide a comprehensive picture of a company's status and necessitate analysis to evaluate performance. This research aims to analyze financial ratios to describe the financial condition, measure business development over time, and evaluate the achievement of the company's objectives. An optimization analysis of financial ratios is performed using the Weighted Goal Programming (WGP) model, which addresses multiple objectives by applying weights based on their priorities. The Best-Worst Method (BWM) was used to determine the priority weights of deviation variables from each financial ratio target. Financial ratios were selected based on their impact on profit using factor analysis. The constructed WGP model aims to minimize deviations in Return on Assets, Operating Ratios, Operating Income Ratio, Total Assets Turnover, and Current Ratio. Computational calculations to solve the WGP model are performed using Python, with pseudocode provided. A case study on a company in the garment and textile sector was conducted and found that the Operating Ratio, Return on Assets, Operating Income Ratio, and Current Ratio still need improvement by developing strategies to achieve the targets. Sensitivity analysis was also employed to assess the resilience of the model in response to alterations in data. © 2024 by the authors; licensee Growing Science, Canada. |
publisher |
Growing Science |
issn |
19295804 |
language |
English |
format |
Article |
accesstype |
All Open Access; Gold Open Access |
record_format |
scopus |
collection |
Scopus |
_version_ |
1814778498633433088 |