Date of Publication
10-25-2025
Document Type
Master's Thesis
Degree Name
Master of Science in Financial Engineering
Subject Categories
Finance and Financial Management
College
Ramon V. Del Rosario College of Business
Department/Unit
Financial Management Department
Thesis Advisor
Tomas S. Tiu
Defense Panel Chair
Ricarte Q. Pinlac
Defense Panel Member
Joseph James F. Lago
Julius O. Buendia
Abstract (English)
The study created an active equity fund using the Markov Chain Monte Carlo (MCMC) optimization model. This method can serve as an alternative investment strategy to improve portfolio returns and lower risk. The MCMC model was utilized as an asset allocation strategy in creating active equity portfolios using stock prices from different stock exchanges from January 2013 to December 2022. The study revealed a promising outcome of the MCMC model, in terms of average and cumulative returns, was highly effective in less volatile markets and even outperformed the majority of equity fund benchmarks and reference indices. The study further recommends investing in Thailand's KAEquity, Malaysia's MCMC portfolio, and Singapore's MCMC portfolio based on Roy's Safety-First Criterion, as they have generated low standard deviations, implying high resilience to systematic risks. The MCMC model could be a valuable instrument for investors and fund managers as it has been found to be effective in markets with lower volatility. Portfolio managers should consider utilizing the optimization method and the continuous updating of the algorithm to keep up with innovations in the financial ecosystem.
Abstract Format
html
Abstract (Filipino)
Ang pananaliksik na ito ay bumuo ng isang active equity fund gamit ang Markov Chain Monte Carlo (MCMC) optimization model. Ang metodolohiyang ito ay maaaring magsilbing alternatibong estratehiya sa pamumuhunan upang mapataas ang kita ng portfolio at mapababa ang panganib ng pagkalugi. Ginamit ang modelong MCMC bilang isang asset allocation strategy sa pagbuo ng mga active equity portfolio gamit ang mga presyo ng stocks mula sa iba’t ibang stock exchange sa timog-silangang asya simula Enero 2013 hanggang Disyembre 2022.
Ipinakita ng pag-aaral ang mga positibong resulta ng paggamit ng modelong MCMC sa usapin ng average at cumulative returns, na napatunayang lubhang epektibo sa mga merkadong hindi gaanong magalaw ang presyo (less volatile) at nalampasan pa nito ang karamihan sa mga benchmark ng equity funds at mga reference index.
Inirerekomenda rin ng pag-aaral ang pamumuhunan sa KAEquity ng Thailand, MCMC portfolio ng Malaysia, at MCMC portfolio ng Singapore batay sa Roy’s Safety-First Criterion, sapagkat nagpakita ang mga ito ng mababang standard deviation na nagpapahiwatig ng mataas na kakayahang makayanan ang mga panganib na dala ng systematic risks.
Maaaring maging mahalagang instrumento ang modelong MCMC para sa mga mamumuhunan at tagapamahala ng pondo, dahil napatunayan itong epektibo sa mga merkadong hindi gaanong magalaw ang presyo. Dapat isaalang-alang din ng mga portfolio manager ang paggamit ng nasabing optimization method at ang tuluy-tuloy na pag-a-update ng algorithm upang makasabay sa mga inobasyon sa sistema ng pananalapi.
Abstract Format
html
Language
English
Format
Electronic
Keywords
Portfolio management
Recommended Citation
Aguibiador, M. R. (2025). Development of an active equity fund portfolio using the Markov Chain Monte Carlo optimization model as a strategic allocation strategy. Retrieved from https://animorepository.dlsu.edu.ph/etdm_finman/21
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Embargo Period
10-25-2026
