Covariance versus correlation in capacitated vehicle routing problem-investment fund allocation problem

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Capacitated Vehicle Routing Problem-Investment Fund Allocation Problem (CVRP-IFAP) provides investors with a sequence of assets to allocate their funds into. To minimize total risks of investment in CVRP-IFAP covariance values measure the risks between two assets. Another measure of risks are correlation values between returns. The correlation values can be used to diversify the risk of investment loss in order to optimize expected return against a certain level of risk. This study compares the total risk obtained from CVRP-IFAP when using covariance values and correlation values. Results show that CVRP-IFAP with covariance values provides lesser total risks and a significantly better measure of risk.

Original languageEnglish
Title of host publication4th International Conference on Mathematical Sciences - Mathematical Sciences
Subtitle of host publicationChampioning the Way in a Problem Based and Data Driven Society, ICMS 2016
PublisherAmerican Institute of Physics Inc.
Volume1830
ISBN (Electronic)9780735414983
DOIs
Publication statusPublished - 27 Apr 2017
Event4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016 - Putrajaya, Malaysia
Duration: 15 Nov 201617 Nov 2016

Other

Other4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016
CountryMalaysia
CityPutrajaya
Period15/11/1617/11/16

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ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Mamat, N. J. Z., Jaaman @ Sharman, S. H., & Ahmad, R. . R. (2017). Covariance versus correlation in capacitated vehicle routing problem-investment fund allocation problem. In 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016 (Vol. 1830). [060003] American Institute of Physics Inc.. https://doi.org/10.1063/1.4980947

Covariance versus correlation in capacitated vehicle routing problem-investment fund allocation problem. / Mamat, Nur Jumaadzan Zaleha; Jaaman @ Sharman, Saiful Hafizah; Ahmad, Rokiah @ Rozita.

4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830 American Institute of Physics Inc., 2017. 060003.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mamat, NJZ, Jaaman @ Sharman, SH & Ahmad, RR 2017, Covariance versus correlation in capacitated vehicle routing problem-investment fund allocation problem. in 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. vol. 1830, 060003, American Institute of Physics Inc., 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016, Putrajaya, Malaysia, 15/11/16. https://doi.org/10.1063/1.4980947
Mamat NJZ, Jaaman @ Sharman SH, Ahmad RR. Covariance versus correlation in capacitated vehicle routing problem-investment fund allocation problem. In 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830. American Institute of Physics Inc. 2017. 060003 https://doi.org/10.1063/1.4980947
Mamat, Nur Jumaadzan Zaleha ; Jaaman @ Sharman, Saiful Hafizah ; Ahmad, Rokiah @ Rozita. / Covariance versus correlation in capacitated vehicle routing problem-investment fund allocation problem. 4th International Conference on Mathematical Sciences - Mathematical Sciences: Championing the Way in a Problem Based and Data Driven Society, ICMS 2016. Vol. 1830 American Institute of Physics Inc., 2017.
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