{"_buckets": {"deposit": "7604d6bb-aef7-4d9d-a9e8-5c3e0e8ca628"}, "_deposit": {"id": "3396", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "3396"}, "status": "published"}, "_oai": {"id": "oai:repository.dl.itc.u-tokyo.ac.jp:00003396"}, "item_7_alternative_title_1": {"attribute_name": "\u305d\u306e\u4ed6\u306e\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_alternative_title": "\u907a\u4f1d\u7684\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0\u3092\u7528\u3044\u305f\u591a\u76ee\u7684\u30dd\u30fc\u30c8\u30d5\u30a9\u30ea\u30aa\u6700\u9069\u5316\u3068\u30ea\u30d0\u30e9\u30f3\u30b7\u30f3\u30b0"}]}, "item_7_biblio_info_7": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2012-03-22", "bibliographicIssueDateType": "Issued"}, "bibliographic_titles": [{}]}]}, "item_7_date_granted_25": {"attribute_name": "\u5b66\u4f4d\u6388\u4e0e\u5e74\u6708\u65e5", "attribute_value_mlt": [{"subitem_dategranted": "2012-03-22"}]}, "item_7_degree_name_20": {"attribute_name": "\u5b66\u4f4d\u540d", "attribute_value_mlt": [{"subitem_degreename": "\u4fee\u58eb(\u5de5\u5b66)"}]}, "item_7_description_5": {"attribute_name": "\u6284\u9332", "attribute_value_mlt": [{"subitem_description": "An asset is any financial instrument like shares of companies, bonds, foreign exchange assets and a lot of others. A Portfolio is collection of these assets held by companies, financial and other institutions and rich individuals. People invest in Portfolios to invest their capital and make profits out of them. In this work, we discuss in depth the problem of Portfolio Optimization through the application of Evolutionary Algorithms, Genetic Algorithms in particular. Portfolio Optimization can be considered a resource allocation problem, where the capital to be invested is the resource and it is invested in various assets held the Portfolio. It is mainly based on the Modern Portfolio Theory (MPT) proposed by Harry Markowitz in 1952. The main idea is that by diversification, holding various kinds of assets, the total risk associated with the Portfolio can be reduced (the specific risk) while maintaining the target expected return. A lot of researchers have proposed various optimizing techniques to find an optimized Portfolio for different markets. The MPT was an extremely significant work in this field. However, it has a lot of restrictions and assumptions in it. If we can reduce/remove those restrictions that do not hold in real world, the problem becomes a very complicated one. At the same time, the optimized Portfolio evolved like this is much more realistic and can be practically used. There have been a number of researches proposing various numerical techniques to solve this problem. We are going to concentrate on Genetic Algorithms in this work, which are random search meta-heuristics. Genetic Algorithms have proved time and again, to work well with these kinds of problems. In this work, we have proposed some new points, which we believe will overcome the weak points of previous researches. The point of new mutation operator that optimizes each and every weight present in the Portfolio has been proposed, in addition to the concept of Traded Volumes which is basically an indirect way of incorporating the impact of news on the financial markets. The results achieved are motivating and the approach, we believe, will be used as a reference for future related works to develop Portfolios in real world.", "subitem_description_type": "Abstract"}]}, "item_7_full_name_3": {"attribute_name": "\u8457\u8005\u5225\u540d", "attribute_value_mlt": [{"nameIdentifiers": [{"nameIdentifier": "8167", "nameIdentifierScheme": "WEKO"}], "names": [{"name": "\u30bd\u30fc\u30e0, \u30f4\u30a3\u30b7\u30e3\u30eb"}]}]}, "item_7_select_21": {"attribute_name": "\u5b66\u4f4d", "attribute_value_mlt": [{"subitem_select_item": "master"}]}, "item_7_subject_13": {"attribute_name": "\u65e5\u672c\u5341\u9032\u5206\u985e\u6cd5", "attribute_value_mlt": [{"subitem_subject": "007", "subitem_subject_scheme": "NDC"}]}, "item_7_text_24": {"attribute_name": "\u7814\u7a76\u79d1\u30fb\u5c02\u653b", "attribute_value_mlt": [{"subitem_text_value": "\u5de5\u5b66\u7cfb\u7814\u7a76\u79d1\u96fb\u6c17\u7cfb\u5de5\u5b66\u5c02\u653b"}]}, "item_7_text_36": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7", "attribute_value_mlt": [{"subitem_text_value": "Thesis"}]}, "item_7_text_4": {"attribute_name": "\u8457\u8005\u6240\u5c5e", "attribute_value_mlt": [{"subitem_text_value": "\u6771\u4eac\u5927\u5b66\u5927\u5b66\u9662\u5de5\u5b66\u7cfb\u7814\u7a76\u79d1\u96fb\u6c17\u7cfb\u5de5\u5b66\u5c02\u653b"}, {"subitem_text_value": "Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo"}]}, "item_creator": {"attribute_name": "\u8457\u8005", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Soam, Vishal"}], "nameIdentifiers": [{"nameIdentifier": "8166", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "\u30d5\u30a1\u30a4\u30eb\u60c5\u5831", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2017-05-31"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "37106528.pdf", "filesize": [{"value": "2.2 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 2200000.0, "url": {"label": "37106528.pdf", "url": "https://repository.dl.itc.u-tokyo.ac.jp/record/3396/files/37106528.pdf"}, "version_id": "c7a6a70a-8e64-446a-81b6-d7f9e1ccb1de"}]}, "item_language": {"attribute_name": "\u8a00\u8a9e", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7", "attribute_value_mlt": [{"resourcetype": "thesis", "resourceuri": "http://purl.org/coar/resource_type/c_46ec"}]}, "item_title": "Multi-Objective Portfolio Optimization and Re-balancing using Genetic Algorithms", "item_titles": {"attribute_name": "\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_title": "Multi-Objective Portfolio Optimization and Re-balancing using Genetic Algorithms"}]}, "item_type_id": "7", "owner": "1", "path": ["9/233/234", "6/209/271"], "permalink_uri": "http://hdl.handle.net/2261/51628", "pubdate": {"attribute_name": "\u516c\u958b\u65e5", "attribute_value": "2012-05-18"}, "publish_date": "2012-05-18", "publish_status": "0", "recid": "3396", "relation": {}, "relation_version_is_last": true, "title": ["Multi-Objective Portfolio Optimization and Re-balancing using Genetic Algorithms"], "weko_shared_id": null}