Influence of Investors’ Loss-cut Behavior to Artificial Market
The aim of this study is to discuss the influence of investors’ loss-cut behavior to the market stock price and the investors’ asset distribution by using the artificial market simulation. The loss-cut behavior is strongly related to the anchoring effect, which is one of the investors’ cognitive bia...
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Veröffentlicht in: | Evolutionary and institutional economics review 2010-09, Vol.7 (1), p.133-153 |
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description | The aim of this study is to discuss the influence of investors’ loss-cut behavior to the market stock price and the investors’ asset distribution by using the artificial market simulation. The loss-cut behavior is strongly related to the anchoring effect, which is one of the investors’ cognitive biases. The anchoring effect is a psychological heuristic that influences the way people intuitively assess probabilities. The investor in the actual market is modeled as the agent in the artificial market. The agent has the prediction rule of the stock price and the anchoring coefficient related to the strength of the anchoring effect. Once the agent predicts the stock price by the prediction rule, he determines the order price and the order amount from the predicted stock price according to the strength of the anchoring effect. Agents’ orders are gathered to the market and the stock price is determined according to the Itayose method. In the numerical examples, two kinds of agents with different anchoring effects are modeled; Type A and Type B agents. Type A agents have stronger anchoring effect than the Type B agents. The simulation results reveal that the Type-A agents’ order price tends to uctuate more violently than the Type B agents, and that the Type A agents tend to lose more asset than the Type B. |
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The loss-cut behavior is strongly related to the anchoring effect, which is one of the investors’ cognitive biases. The anchoring effect is a psychological heuristic that influences the way people intuitively assess probabilities. The investor in the actual market is modeled as the agent in the artificial market. The agent has the prediction rule of the stock price and the anchoring coefficient related to the strength of the anchoring effect. Once the agent predicts the stock price by the prediction rule, he determines the order price and the order amount from the predicted stock price according to the strength of the anchoring effect. Agents’ orders are gathered to the market and the stock price is determined according to the Itayose method. In the numerical examples, two kinds of agents with different anchoring effects are modeled; Type A and Type B agents. Type A agents have stronger anchoring effect than the Type B agents. The simulation results reveal that the Type-A agents’ order price tends to uctuate more violently than the Type B agents, and that the Type A agents tend to lose more asset than the Type B.</description><identifier>ISSN: 1349-4961</identifier><identifier>EISSN: 2188-2096</identifier><identifier>DOI: 10.14441/eier.7.133</identifier><language>eng</language><publisher>Tokyo: Springer-Verlag</publisher><subject>Economic theory ; Economic Theory/Quantitative Economics/Mathematical Methods ; Economics ; Economics and Finance ; History of Economic Thought/Methodology ; Investments ; Investors ; Political Economy/Economic Systems ; Social Policy</subject><ispartof>Evolutionary and institutional economics review, 2010-09, Vol.7 (1), p.133-153</ispartof><rights>Japan Association for Evolutionary Economics 2010</rights><rights>Japan Association for Evolutionary Economics 2010.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c359t-efd5f51839f06382dd5b1a77a746417f540427e3af5a92d0a111f95f5e4959723</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.14441/eier.7.133$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.14441/eier.7.133$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Zhai, Fei</creatorcontrib><creatorcontrib>Takahashi, Kenji</creatorcontrib><creatorcontrib>Shinoki, Hiroto</creatorcontrib><creatorcontrib>Kita, Eisuke</creatorcontrib><title>Influence of Investors’ Loss-cut Behavior to Artificial Market</title><title>Evolutionary and institutional economics review</title><addtitle>Evolut Inst Econ Rev</addtitle><description>The aim of this study is to discuss the influence of investors’ loss-cut behavior to the market stock price and the investors’ asset distribution by using the artificial market simulation. The loss-cut behavior is strongly related to the anchoring effect, which is one of the investors’ cognitive biases. The anchoring effect is a psychological heuristic that influences the way people intuitively assess probabilities. The investor in the actual market is modeled as the agent in the artificial market. The agent has the prediction rule of the stock price and the anchoring coefficient related to the strength of the anchoring effect. Once the agent predicts the stock price by the prediction rule, he determines the order price and the order amount from the predicted stock price according to the strength of the anchoring effect. Agents’ orders are gathered to the market and the stock price is determined according to the Itayose method. In the numerical examples, two kinds of agents with different anchoring effects are modeled; Type A and Type B agents. Type A agents have stronger anchoring effect than the Type B agents. The simulation results reveal that the Type-A agents’ order price tends to uctuate more violently than the Type B agents, and that the Type A agents tend to lose more asset than the Type B.</description><subject>Economic theory</subject><subject>Economic Theory/Quantitative Economics/Mathematical Methods</subject><subject>Economics</subject><subject>Economics and Finance</subject><subject>History of Economic Thought/Methodology</subject><subject>Investments</subject><subject>Investors</subject><subject>Political Economy/Economic Systems</subject><subject>Social Policy</subject><issn>1349-4961</issn><issn>2188-2096</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNptkMtOwzAQRS0EEqWw4gcssYQEjx9xvKNUPCoFsYG1ZRIbUkJc7KQSO36D3-NLMBSxYjXS6Mydq4PQIZAcOOdwalsbcpkDY1toQqEsM0pUsY0mwLjKuCpgF-3FuCSEgyDFBJ0teteNtq8t9g4v-rWNgw_x8_0DVz7GrB4HfG6fzLr1AQ8ez8LQurZuTYdvTHi2wz7acaaL9uB3TtH95cXd_Dqrbq8W81mV1UyoIbOuEU5AyZQjBStp04gHMFIayQsO0glOOJWWGSeMog0xAOBUOrFcCSUpm6KjTe4q-NcxtdRLP4Y-vdRUMUplKVWZqOMNVYfUPlinV6F9MeFNA9E_ivS3Ii11UpTokw0dE9U_pv1f5n_4F2SQaCY</recordid><startdate>20100901</startdate><enddate>20100901</enddate><creator>Zhai, Fei</creator><creator>Takahashi, Kenji</creator><creator>Shinoki, Hiroto</creator><creator>Kita, Eisuke</creator><general>Springer-Verlag</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>PQBIZ</scope><scope>PQBZA</scope></search><sort><creationdate>20100901</creationdate><title>Influence of Investors’ Loss-cut Behavior to Artificial Market</title><author>Zhai, Fei ; Takahashi, Kenji ; Shinoki, Hiroto ; Kita, Eisuke</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-efd5f51839f06382dd5b1a77a746417f540427e3af5a92d0a111f95f5e4959723</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Economic theory</topic><topic>Economic Theory/Quantitative Economics/Mathematical Methods</topic><topic>Economics</topic><topic>Economics and Finance</topic><topic>History of Economic Thought/Methodology</topic><topic>Investments</topic><topic>Investors</topic><topic>Political Economy/Economic Systems</topic><topic>Social Policy</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhai, Fei</creatorcontrib><creatorcontrib>Takahashi, Kenji</creatorcontrib><creatorcontrib>Shinoki, Hiroto</creatorcontrib><creatorcontrib>Kita, Eisuke</creatorcontrib><collection>CrossRef</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><jtitle>Evolutionary and institutional economics review</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhai, Fei</au><au>Takahashi, Kenji</au><au>Shinoki, Hiroto</au><au>Kita, Eisuke</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Influence of Investors’ Loss-cut Behavior to Artificial Market</atitle><jtitle>Evolutionary and institutional economics review</jtitle><stitle>Evolut Inst Econ Rev</stitle><date>2010-09-01</date><risdate>2010</risdate><volume>7</volume><issue>1</issue><spage>133</spage><epage>153</epage><pages>133-153</pages><issn>1349-4961</issn><eissn>2188-2096</eissn><abstract>The aim of this study is to discuss the influence of investors’ loss-cut behavior to the market stock price and the investors’ asset distribution by using the artificial market simulation. The loss-cut behavior is strongly related to the anchoring effect, which is one of the investors’ cognitive biases. The anchoring effect is a psychological heuristic that influences the way people intuitively assess probabilities. The investor in the actual market is modeled as the agent in the artificial market. The agent has the prediction rule of the stock price and the anchoring coefficient related to the strength of the anchoring effect. Once the agent predicts the stock price by the prediction rule, he determines the order price and the order amount from the predicted stock price according to the strength of the anchoring effect. Agents’ orders are gathered to the market and the stock price is determined according to the Itayose method. In the numerical examples, two kinds of agents with different anchoring effects are modeled; Type A and Type B agents. Type A agents have stronger anchoring effect than the Type B agents. The simulation results reveal that the Type-A agents’ order price tends to uctuate more violently than the Type B agents, and that the Type A agents tend to lose more asset than the Type B.</abstract><cop>Tokyo</cop><pub>Springer-Verlag</pub><doi>10.14441/eier.7.133</doi><tpages>21</tpages></addata></record> |
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title | Influence of Investors’ Loss-cut Behavior to Artificial Market |
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