Financial Modeling and Prediction as a Service

Victor Chang*, Muthu Ramachandran

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


This paper describes our proposal for Quality of Service (QoS) for Financial Modeling and Prediction as a Service (FMPaaS), since a majority of papers does not focus on SaaS level. We focus on two factors for delivering successful QoS, which are performance and accuracy for FMPaaS. The design process, theories and models behind the FMPaaS service have been explained. To support our FMPaaS service, two APIs have been developed to improve on performance and accuracy. Two major experiments have been illustrated and results show that each API processing can be completed in 2.12 seconds and 100,000 simulations can be completed in an acceptable period of time. Accuracy tests have been performed while using Facebook as an example. Three points of comparisons between actual and predicted prices have been undertaken. Results support accuracy since results are between 93.72 % and 99.63 % for Facebook. Three case studies have been used and results can support the accuracy and validity of the high level of accuracy offered by FMPaaS.

Original languageEnglish
Pages (from-to)177-195
Number of pages19
JournalJournal of Grid Computing
Issue number2
Publication statusPublished - 1 Jun 2017


  • Financial Modeling and Prediction as a Service (FMPaaS) QoS
  • Performance and accuracy test for FMPaaS QoS
  • Quality of Service (QoS) for SaaS


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