Application of Markovian switching model and mean-variance analysis in dynamic allocation strategy for exchange traded funds
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ID: 286251
2022
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Abstract
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.
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| Authors | Palino, Justin Alfred Vigo |
| Journal | Malay Journal |
| Year | 2022 |
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| Keywords | Keywords not found |
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