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The alternative risk measures in Excel
The paper examines the alternative risk measures and portfolio selection with alternative risk measures. The paper follows from student's activities in the subject of financial modeling, precisely in the modern portfolio theory. As many weaknesses of Markowitz mean-variance model have been noti...
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creator | Aljinović, Zdravka Marasović, Branka Vidović, Jelena |
description | The paper examines the alternative risk measures and portfolio selection with alternative risk measures. The paper follows from student's activities in the subject of financial modeling, precisely in the modern portfolio theory. As many weaknesses of Markowitz mean-variance model have been noticed, primarily in the sense that variance isn't appropriate risk measure when distribution of stock returns isn't normal, the alternative risk measures have to be introduced. The problem is how to present relatively complex portfolio optimization models with alternative risk measures to students' population and to teach them how to realize those models using Excel. In this paper, the alternative risk measures which attracted significant attention of financial managers last years together with Excel's formulations of analytical expressions are introduced. The presented risk measures are lower-semi variance, lower semi-absolute deviation, Value at Risk (VaR) and Conditional Value at Risk (CVaR). That is followed by construction of models for portfolio selection based on different risk measures together with Excel solutions. All theoretical settings are accompanied with illustrative examples. |
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The paper follows from student's activities in the subject of financial modeling, precisely in the modern portfolio theory. As many weaknesses of Markowitz mean-variance model have been noticed, primarily in the sense that variance isn't appropriate risk measure when distribution of stock returns isn't normal, the alternative risk measures have to be introduced. The problem is how to present relatively complex portfolio optimization models with alternative risk measures to students' population and to teach them how to realize those models using Excel. In this paper, the alternative risk measures which attracted significant attention of financial managers last years together with Excel's formulations of analytical expressions are introduced. The presented risk measures are lower-semi variance, lower semi-absolute deviation, Value at Risk (VaR) and Conditional Value at Risk (CVaR). That is followed by construction of models for portfolio selection based on different risk measures together with Excel solutions. All theoretical settings are accompanied with illustrative examples.</description><identifier>ISBN: 9781424477630</identifier><identifier>ISBN: 1424477638</identifier><identifier>EISBN: 9532330585</identifier><identifier>EISBN: 9789532330588</identifier><identifier>EISBN: 953233050X</identifier><identifier>EISBN: 9789532330502</identifier><language>eng</language><publisher>IEEE</publisher><subject>Application software ; Concrete ; Finance ; Financial management ; Mathematical model ; Portfolios ; Reactive power ; Risk analysis ; Risk management ; Student activities</subject><ispartof>The 33rd International Convention MIPRO, 2010, p.908-913</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5533558$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5533558$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Aljinović, Zdravka</creatorcontrib><creatorcontrib>Marasović, Branka</creatorcontrib><creatorcontrib>Vidović, Jelena</creatorcontrib><title>The alternative risk measures in Excel</title><title>The 33rd International Convention MIPRO</title><addtitle>MIPRO</addtitle><description>The paper examines the alternative risk measures and portfolio selection with alternative risk measures. The paper follows from student's activities in the subject of financial modeling, precisely in the modern portfolio theory. As many weaknesses of Markowitz mean-variance model have been noticed, primarily in the sense that variance isn't appropriate risk measure when distribution of stock returns isn't normal, the alternative risk measures have to be introduced. The problem is how to present relatively complex portfolio optimization models with alternative risk measures to students' population and to teach them how to realize those models using Excel. In this paper, the alternative risk measures which attracted significant attention of financial managers last years together with Excel's formulations of analytical expressions are introduced. The presented risk measures are lower-semi variance, lower semi-absolute deviation, Value at Risk (VaR) and Conditional Value at Risk (CVaR). That is followed by construction of models for portfolio selection based on different risk measures together with Excel solutions. All theoretical settings are accompanied with illustrative examples.</description><subject>Application software</subject><subject>Concrete</subject><subject>Finance</subject><subject>Financial management</subject><subject>Mathematical model</subject><subject>Portfolios</subject><subject>Reactive power</subject><subject>Risk analysis</subject><subject>Risk management</subject><subject>Student activities</subject><isbn>9781424477630</isbn><isbn>1424477638</isbn><isbn>9532330585</isbn><isbn>9789532330588</isbn><isbn>953233050X</isbn><isbn>9789532330502</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNpjZOCyNDU2MjY2MLUwZWbgtTS3MDQxMjExNzczNuBg4C0uzjIAAhNTIzMDC04GtZCMVIXEnJLUorzEksyyVIWizOJshdzUxOLSotRihcw8BdeK5NQcHgbWtMSc4lReKM3NIO3mGuLsoZuZmpoaX1CUmZtYVBlvampsbGpqYYxfFgD6qSxZ</recordid><startdate>201005</startdate><enddate>201005</enddate><creator>Aljinović, Zdravka</creator><creator>Marasović, Branka</creator><creator>Vidović, Jelena</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201005</creationdate><title>The alternative risk measures in Excel</title><author>Aljinović, Zdravka ; Marasović, Branka ; Vidović, Jelena</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-ieee_primary_55335583</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Application software</topic><topic>Concrete</topic><topic>Finance</topic><topic>Financial management</topic><topic>Mathematical model</topic><topic>Portfolios</topic><topic>Reactive power</topic><topic>Risk analysis</topic><topic>Risk management</topic><topic>Student activities</topic><toplevel>online_resources</toplevel><creatorcontrib>Aljinović, Zdravka</creatorcontrib><creatorcontrib>Marasović, Branka</creatorcontrib><creatorcontrib>Vidović, Jelena</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Aljinović, Zdravka</au><au>Marasović, Branka</au><au>Vidović, Jelena</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>The alternative risk measures in Excel</atitle><btitle>The 33rd International Convention MIPRO</btitle><stitle>MIPRO</stitle><date>2010-05</date><risdate>2010</risdate><spage>908</spage><epage>913</epage><pages>908-913</pages><isbn>9781424477630</isbn><isbn>1424477638</isbn><eisbn>9532330585</eisbn><eisbn>9789532330588</eisbn><eisbn>953233050X</eisbn><eisbn>9789532330502</eisbn><abstract>The paper examines the alternative risk measures and portfolio selection with alternative risk measures. The paper follows from student's activities in the subject of financial modeling, precisely in the modern portfolio theory. As many weaknesses of Markowitz mean-variance model have been noticed, primarily in the sense that variance isn't appropriate risk measure when distribution of stock returns isn't normal, the alternative risk measures have to be introduced. The problem is how to present relatively complex portfolio optimization models with alternative risk measures to students' population and to teach them how to realize those models using Excel. In this paper, the alternative risk measures which attracted significant attention of financial managers last years together with Excel's formulations of analytical expressions are introduced. The presented risk measures are lower-semi variance, lower semi-absolute deviation, Value at Risk (VaR) and Conditional Value at Risk (CVaR). That is followed by construction of models for portfolio selection based on different risk measures together with Excel solutions. All theoretical settings are accompanied with illustrative examples.</abstract><pub>IEEE</pub></addata></record> |
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ispartof | The 33rd International Convention MIPRO, 2010, p.908-913 |
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language | eng |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Application software Concrete Finance Financial management Mathematical model Portfolios Reactive power Risk analysis Risk management Student activities |
title | The alternative risk measures in Excel |
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