Date of Publication

8-2022

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

Thomas S. Tiu

Defense Panel Chair

Edwin Valeroso

Defense Panel Member

Ricarte Pinlac
Kashmirr Camacho

Abstract/Summary

Actively managed ETFs continuously underperformed their passive counterparts. In fact, according to a recent study conducted by Johnson of Morningstar in 2022, 74% of all active funds underperformed the average passive peers based on his 10-year period of study ending in December 2021. Coinciding with the study of Johnson of Morningstar and the previous literatures, the common denominator in the underperformance of actively managed ETFs is the lack of proper market timing. Henceforth, the author initiated a dynamic mathematical approach to properly address the timing of the market. The approach is primarily established to reduce human behavioral error and become objective rather than subjective. The theories behind the approach are the Markovian Switching Model and Mean-Variance Optimization.

Throughout the application of the two theories, the result of the study proved a significant success and showed an increased portfolio return by; (1) perfectly timing the entry and exit in the market; and (2) properly navigating the allocation of assets as the market environment changes.

Abstract Format

html

Language

English

Format

Electronic

Keywords

Exchange traded funds

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Embargo Period

10-25-2022

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