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On sparsity of eigenportfolios to reduce transaction cost
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| Zeitschriftentitel: | Journal of Capital Markets Studies |
|---|---|
| Personen und Körperschaften: | , |
| In: | Journal of Capital Markets Studies, 3, 2019, 1, S. 82-90 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Emerald
|
| author_facet |
Xiong, Anqi Akansu, Ali N. Xiong, Anqi Akansu, Ali N. |
|---|---|
| author |
Xiong, Anqi Akansu, Ali N. |
| spellingShingle |
Xiong, Anqi Akansu, Ali N. Journal of Capital Markets Studies On sparsity of eigenportfolios to reduce transaction cost |
| author_sort |
xiong, anqi |
| spelling |
Xiong, Anqi Akansu, Ali N. 2514-4774 Emerald http://dx.doi.org/10.1108/jcms-06-2018-0024 <jats:sec> <jats:title content-type="abstract-subheading">Purpose</jats:title> <jats:p>Transaction cost becomes significant when one holds many securities in a large portfolio where capital allocations are frequently rebalanced due to variations in non-stationary statistical characteristics of the asset returns. The purpose of this paper is to employ a sparsing method to sparse the eigenportfolios, so that the transaction cost can be reduced and without any loss of its performance.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title> <jats:p>In this paper, the authors have designed pdf-optimized mid-tread Lloyd-Max quantizers based on the distribution of each eigenportfolio, and then employed them to sparse the eigenportfolios, so those small size orders may usually be ignored (sparsed), as the result, the trading costs have been reduced.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Findings</jats:title> <jats:p>The authors find that the sparsing technique addressed in this paper is methodic, easy to implement for large size portfolios and it offers significant reduction in transaction cost without any loss of performance.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Originality/value</jats:title> <jats:p>In this paper, the authors investigated the performance the sparsed eigenportfolios of stock returns in S&P500 Index. It is shown that the sparsing method is simple to implement and it provides high levels of sparsity without causing PNL loss. Therefore, transaction cost of managing a large size portfolio is reduced by employing such an efficient sparsity method.</jats:p> </jats:sec> On sparsity of eigenportfolios to reduce transaction cost Journal of Capital Markets Studies |
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Journal of Capital Markets Studies |
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| title |
On sparsity of eigenportfolios to reduce transaction cost |
| title_unstemmed |
On sparsity of eigenportfolios to reduce transaction cost |
| title_full |
On sparsity of eigenportfolios to reduce transaction cost |
| title_fullStr |
On sparsity of eigenportfolios to reduce transaction cost |
| title_full_unstemmed |
On sparsity of eigenportfolios to reduce transaction cost |
| title_short |
On sparsity of eigenportfolios to reduce transaction cost |
| title_sort |
on sparsity of eigenportfolios to reduce transaction cost |
| url |
http://dx.doi.org/10.1108/jcms-06-2018-0024 |
| publishDate |
2019 |
| physical |
82-90 |
| description |
<jats:sec>
<jats:title content-type="abstract-subheading">Purpose</jats:title>
<jats:p>Transaction cost becomes significant when one holds many securities in a large portfolio where capital allocations are frequently rebalanced due to variations in non-stationary statistical characteristics of the asset returns. The purpose of this paper is to employ a sparsing method to sparse the eigenportfolios, so that the transaction cost can be reduced and without any loss of its performance.</jats:p>
</jats:sec>
<jats:sec>
<jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title>
<jats:p>In this paper, the authors have designed pdf-optimized mid-tread Lloyd-Max quantizers based on the distribution of each eigenportfolio, and then employed them to sparse the eigenportfolios, so those small size orders may usually be ignored (sparsed), as the result, the trading costs have been reduced.</jats:p>
</jats:sec>
<jats:sec>
<jats:title content-type="abstract-subheading">Findings</jats:title>
<jats:p>The authors find that the sparsing technique addressed in this paper is methodic, easy to implement for large size portfolios and it offers significant reduction in transaction cost without any loss of performance.</jats:p>
</jats:sec>
<jats:sec>
<jats:title content-type="abstract-subheading">Originality/value</jats:title>
<jats:p>In this paper, the authors investigated the performance the sparsed eigenportfolios of stock returns in S&P500 Index. It is shown that the sparsing method is simple to implement and it provides high levels of sparsity without causing PNL loss. Therefore, transaction cost of managing a large size portfolio is reduced by employing such an efficient sparsity method.</jats:p>
</jats:sec> |
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| author | Xiong, Anqi, Akansu, Ali N. |
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| description | <jats:sec> <jats:title content-type="abstract-subheading">Purpose</jats:title> <jats:p>Transaction cost becomes significant when one holds many securities in a large portfolio where capital allocations are frequently rebalanced due to variations in non-stationary statistical characteristics of the asset returns. The purpose of this paper is to employ a sparsing method to sparse the eigenportfolios, so that the transaction cost can be reduced and without any loss of its performance.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title> <jats:p>In this paper, the authors have designed pdf-optimized mid-tread Lloyd-Max quantizers based on the distribution of each eigenportfolio, and then employed them to sparse the eigenportfolios, so those small size orders may usually be ignored (sparsed), as the result, the trading costs have been reduced.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Findings</jats:title> <jats:p>The authors find that the sparsing technique addressed in this paper is methodic, easy to implement for large size portfolios and it offers significant reduction in transaction cost without any loss of performance.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Originality/value</jats:title> <jats:p>In this paper, the authors investigated the performance the sparsed eigenportfolios of stock returns in S&P500 Index. It is shown that the sparsing method is simple to implement and it provides high levels of sparsity without causing PNL loss. Therefore, transaction cost of managing a large size portfolio is reduced by employing such an efficient sparsity method.</jats:p> </jats:sec> |
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| spelling | Xiong, Anqi Akansu, Ali N. 2514-4774 Emerald http://dx.doi.org/10.1108/jcms-06-2018-0024 <jats:sec> <jats:title content-type="abstract-subheading">Purpose</jats:title> <jats:p>Transaction cost becomes significant when one holds many securities in a large portfolio where capital allocations are frequently rebalanced due to variations in non-stationary statistical characteristics of the asset returns. The purpose of this paper is to employ a sparsing method to sparse the eigenportfolios, so that the transaction cost can be reduced and without any loss of its performance.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title> <jats:p>In this paper, the authors have designed pdf-optimized mid-tread Lloyd-Max quantizers based on the distribution of each eigenportfolio, and then employed them to sparse the eigenportfolios, so those small size orders may usually be ignored (sparsed), as the result, the trading costs have been reduced.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Findings</jats:title> <jats:p>The authors find that the sparsing technique addressed in this paper is methodic, easy to implement for large size portfolios and it offers significant reduction in transaction cost without any loss of performance.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Originality/value</jats:title> <jats:p>In this paper, the authors investigated the performance the sparsed eigenportfolios of stock returns in S&P500 Index. It is shown that the sparsing method is simple to implement and it provides high levels of sparsity without causing PNL loss. Therefore, transaction cost of managing a large size portfolio is reduced by employing such an efficient sparsity method.</jats:p> </jats:sec> On sparsity of eigenportfolios to reduce transaction cost Journal of Capital Markets Studies |
| spellingShingle | Xiong, Anqi, Akansu, Ali N., Journal of Capital Markets Studies, On sparsity of eigenportfolios to reduce transaction cost |
| title | On sparsity of eigenportfolios to reduce transaction cost |
| title_full | On sparsity of eigenportfolios to reduce transaction cost |
| title_fullStr | On sparsity of eigenportfolios to reduce transaction cost |
| title_full_unstemmed | On sparsity of eigenportfolios to reduce transaction cost |
| title_short | On sparsity of eigenportfolios to reduce transaction cost |
| title_sort | on sparsity of eigenportfolios to reduce transaction cost |
| title_unstemmed | On sparsity of eigenportfolios to reduce transaction cost |
| url | http://dx.doi.org/10.1108/jcms-06-2018-0024 |