The Resampled Method To Improve The Efficient Frontier In Minimizing Estimation Error: The Case Of Malaysia Equity Portfolios
Since the work of Markowitz (1952), Mean-Variance (MV) analysis has been a central focus of financial economics. MV theory is still used as a foundation of the modern finance for asset management. Problems involving quadratic objective functions or loss functions generally incorporate a MV analys...
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my.usm.eprints.31211 http://eprints.usm.my/31211/ The Resampled Method To Improve The Efficient Frontier In Minimizing Estimation Error: The Case Of Malaysia Equity Portfolios Abu Mansor, Siti Nurleena QA1 Mathematics (General) Since the work of Markowitz (1952), Mean-Variance (MV) analysis has been a central focus of financial economics. MV theory is still used as a foundation of the modern finance for asset management. Problems involving quadratic objective functions or loss functions generally incorporate a MV analysis. However, estimation error is known to have huge impact on MV optimized portfolios, which is one of the primary reasons to make standard Markowitz optimization unfeasible in practice. Therefore, in this study we improved the efficient frontier using a relatively new approach introduced by Michaud (1998), i.e., the resampled efficient. Michaud argues that the limitations of MV effiCiency in practice generally derive from a lack of statistical understanding of MV optimization. We support his statistical view of MV optimization that leads to new procedures which can reduce estimation error. Bermula dengan hasil kerja Markowitz (1952), analisis "Mean-Variance" (MV) telah menjadi fokus utama dalam analisis ekonomi kewangan. Kini, teori MV digunakan sebagai asas dalam bidang kewangan moden bagi pengurusan asset. Permasalahan yang melibatkan fungsi objektif kuadratik atau fungsi menyusut, secara amnya turut menggabungkan penggunaan ailalisis MV. Namun, ralat penganggaran memberi impak yang besar terhadap potfo!io yang telah dioptimumkan oleh analisis MV, di mana ia merupakan salah satu sebab utama menjadikan piawai pengoptimuman Markowitz tidak lagi dapat digunakan secara praktikal. Oleh itu, kajian ini memperbalki sempadan cekap menggunakan pendekatan baru yang diperkenalkan oleh Michaud (1998) iaitu pensampelan-semula cekap. Michaud membantah penggunaan kaedah MV kerana secara praktikal batasan "MV efficiency" wujud disebabkan oleh kurangnya pemahaman statistik daripada proses pengoptimuman MV. Kita turut menyokong pandangannya yang seterusnya menjurus ke arah satu kaedah baru yang boleh mengurangkan kesan ralat penganggaran. 2006-08 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/31211/1/SITI__NURLEENA_BINTI_ABU_MANSOR.pdf Abu Mansor, Siti Nurleena (2006) The Resampled Method To Improve The Efficient Frontier In Minimizing Estimation Error: The Case Of Malaysia Equity Portfolios. Masters thesis, Universiti Sains Malaysia. |
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QA1 Mathematics (General) Abu Mansor, Siti Nurleena The Resampled Method To Improve The Efficient Frontier In Minimizing Estimation Error: The Case Of Malaysia Equity Portfolios |
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Since the work of Markowitz (1952), Mean-Variance (MV) analysis has been a
central focus of financial economics. MV theory is still used as a foundation of the
modern finance for asset management. Problems involving quadratic objective
functions or loss functions generally incorporate a MV analysis.
However, estimation error is known to have huge impact on MV optimized
portfolios, which is one of the primary reasons to make standard Markowitz
optimization unfeasible in practice. Therefore, in this study we improved the efficient
frontier using a relatively new approach introduced by Michaud (1998), i.e., the
resampled efficient. Michaud argues that the limitations of MV effiCiency in practice
generally derive from a lack of statistical understanding of MV optimization. We support
his statistical view of MV optimization that leads to new procedures which can reduce
estimation error.
Bermula dengan hasil kerja Markowitz (1952), analisis "Mean-Variance" (MV)
telah menjadi fokus utama dalam analisis ekonomi kewangan. Kini, teori MV digunakan
sebagai asas dalam bidang kewangan moden bagi pengurusan asset. Permasalahan
yang melibatkan fungsi objektif kuadratik atau fungsi menyusut, secara amnya turut
menggabungkan penggunaan ailalisis MV.
Namun, ralat penganggaran memberi impak yang besar terhadap potfo!io yang
telah dioptimumkan oleh analisis MV, di mana ia merupakan salah satu sebab utama
menjadikan piawai pengoptimuman Markowitz tidak lagi dapat digunakan secara
praktikal. Oleh itu, kajian ini memperbalki sempadan cekap menggunakan pendekatan
baru yang diperkenalkan oleh Michaud (1998) iaitu pensampelan-semula cekap.
Michaud membantah penggunaan kaedah MV kerana secara praktikal batasan "MV
efficiency" wujud disebabkan oleh kurangnya pemahaman statistik daripada proses
pengoptimuman MV. Kita turut menyokong pandangannya yang seterusnya menjurus
ke arah satu kaedah baru yang boleh mengurangkan kesan ralat penganggaran. |
format |
Thesis |
author |
Abu Mansor, Siti Nurleena |
author_facet |
Abu Mansor, Siti Nurleena |
author_sort |
Abu Mansor, Siti Nurleena |
title |
The Resampled Method To Improve The Efficient Frontier In
Minimizing Estimation Error: The Case Of Malaysia Equity
Portfolios
|
title_short |
The Resampled Method To Improve The Efficient Frontier In
Minimizing Estimation Error: The Case Of Malaysia Equity
Portfolios
|
title_full |
The Resampled Method To Improve The Efficient Frontier In
Minimizing Estimation Error: The Case Of Malaysia Equity
Portfolios
|
title_fullStr |
The Resampled Method To Improve The Efficient Frontier In
Minimizing Estimation Error: The Case Of Malaysia Equity
Portfolios
|
title_full_unstemmed |
The Resampled Method To Improve The Efficient Frontier In
Minimizing Estimation Error: The Case Of Malaysia Equity
Portfolios
|
title_sort |
resampled method to improve the efficient frontier in
minimizing estimation error: the case of malaysia equity
portfolios |
publishDate |
2006 |
url |
http://eprints.usm.my/31211/1/SITI__NURLEENA_BINTI_ABU_MANSOR.pdf http://eprints.usm.my/31211/ |
_version_ |
1643707331619323904 |
score |
13.211869 |