Fuzzy Model Applied in Risk Perception and Price Forecasts
This study applies a fuzzy model to simulate an evolution of price forecasts among market investors based on their own risk perception and other multiple criteria decision. According to this imitation, we design a capital market laboratory experiment on the basis of Smith et al. (Econometrica 56:111...
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| Veröffentlicht in: | International journal of fuzzy systems 2019-09, Vol.21 (6), p.1906-1918 |
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| container_end_page | 1918 |
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| container_issue | 6 |
| container_start_page | 1906 |
| container_title | International journal of fuzzy systems |
| container_volume | 21 |
| creator | Yang, Que Wang, Zongrun |
| description | This study applies a fuzzy model to simulate an evolution of price forecasts among market investors based on their own risk perception and other multiple criteria decision. According to this imitation, we design a capital market laboratory experiment on the basis of Smith et al. (Econometrica 56:1119–1151,
1988
). The experiment sets two groups of experiments to test the investor’s market behaviour under the influence of risk perception. The results show that there is no significant difference in changing prices under the influence of perceived systemic risks and non-systemic risks. However, when market returns become more uncertain, investors’ perceptions of risk significantly affect their trading behaviour. Furthermore, we divide the investors’ investment behaviour into different investment strategies and observe the trading behaviours of the investors with risk perception. In addition, extended analysis shows that under a risk environment, a decline in asset price is related to the amount of cash and assets held by the investors, and the assets purchased in the previous period has no substantial relationship with the asset price in the last period and the forecast accuracy of the investment asset price in the last period. |
| doi_str_mv | 10.1007/s40815-019-00651-9 |
| format | Article |
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1988
). The experiment sets two groups of experiments to test the investor’s market behaviour under the influence of risk perception. The results show that there is no significant difference in changing prices under the influence of perceived systemic risks and non-systemic risks. However, when market returns become more uncertain, investors’ perceptions of risk significantly affect their trading behaviour. Furthermore, we divide the investors’ investment behaviour into different investment strategies and observe the trading behaviours of the investors with risk perception. In addition, extended analysis shows that under a risk environment, a decline in asset price is related to the amount of cash and assets held by the investors, and the assets purchased in the previous period has no substantial relationship with the asset price in the last period and the forecast accuracy of the investment asset price in the last period.</description><identifier>ISSN: 1562-2479</identifier><identifier>EISSN: 2199-3211</identifier><identifier>DOI: 10.1007/s40815-019-00651-9</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Algorithms ; Artificial Intelligence ; Behavior ; Capital markets ; Computational Intelligence ; Decision making ; Economic theory ; Engineering ; Experiments ; Information management ; Investment strategy ; Investors ; Laboratories ; Management Science ; Markov analysis ; Mathematical models ; Multiple criterion ; Operations Research ; Perception ; Portfolio investments ; Prices ; Research methodology ; Risk perception ; Variables</subject><ispartof>International journal of fuzzy systems, 2019-09, Vol.21 (6), p.1906-1918</ispartof><rights>Taiwan Fuzzy Systems Association 2019</rights><rights>Taiwan Fuzzy Systems Association 2019.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c362t-1d940f1b1e1acffa074e88199cdf8908b451f759d3ef6ad15905fe36ce4ef0fd3</citedby><cites>FETCH-LOGICAL-c362t-1d940f1b1e1acffa074e88199cdf8908b451f759d3ef6ad15905fe36ce4ef0fd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s40815-019-00651-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2932728197?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21388,27924,27925,33744,41488,42557,43805,51319,64385,64389,72469</link.rule.ids></links><search><creatorcontrib>Yang, Que</creatorcontrib><creatorcontrib>Wang, Zongrun</creatorcontrib><title>Fuzzy Model Applied in Risk Perception and Price Forecasts</title><title>International journal of fuzzy systems</title><addtitle>Int. J. Fuzzy Syst</addtitle><description>This study applies a fuzzy model to simulate an evolution of price forecasts among market investors based on their own risk perception and other multiple criteria decision. According to this imitation, we design a capital market laboratory experiment on the basis of Smith et al. (Econometrica 56:1119–1151,
1988
). The experiment sets two groups of experiments to test the investor’s market behaviour under the influence of risk perception. The results show that there is no significant difference in changing prices under the influence of perceived systemic risks and non-systemic risks. However, when market returns become more uncertain, investors’ perceptions of risk significantly affect their trading behaviour. Furthermore, we divide the investors’ investment behaviour into different investment strategies and observe the trading behaviours of the investors with risk perception. In addition, extended analysis shows that under a risk environment, a decline in asset price is related to the amount of cash and assets held by the investors, and the assets purchased in the previous period has no substantial relationship with the asset price in the last period and the forecast accuracy of the investment asset price in the last period.</description><subject>Algorithms</subject><subject>Artificial Intelligence</subject><subject>Behavior</subject><subject>Capital markets</subject><subject>Computational Intelligence</subject><subject>Decision making</subject><subject>Economic theory</subject><subject>Engineering</subject><subject>Experiments</subject><subject>Information management</subject><subject>Investment strategy</subject><subject>Investors</subject><subject>Laboratories</subject><subject>Management Science</subject><subject>Markov analysis</subject><subject>Mathematical models</subject><subject>Multiple criterion</subject><subject>Operations Research</subject><subject>Perception</subject><subject>Portfolio investments</subject><subject>Prices</subject><subject>Research methodology</subject><subject>Risk perception</subject><subject>Variables</subject><issn>1562-2479</issn><issn>2199-3211</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kMFKAzEURYMoWGp_wFXAdTQvmWQm7kqxKlQsouuQJi8yWmfGZLpov97REdy5ept7z30cQs6BXwLn5VUueAWKcTCMc62AmSMyEWAMkwLgmExAacFEUZpTMsu53nAJQkul5YRcL3eHw54-tAG3dN512xoDrRv6VOd3usbksevrtqGuCXSdao902Sb0Lvf5jJxEt804-71T8rK8eV7csdXj7f1ivmJeatEzCKbgETaA4HyMjpcFVtXwnQ-xMrzaFApiqUyQGLULoAxXEaX2WGDkMcgpuRi5XWo_d5h7-9buUjNMWmGkKMUAK4eUGFM-tTknjLZL9YdLewvcfmuyoyY7aLI_mqwZSnIs5SHcvGL6Q__T-gK8Omm_</recordid><startdate>20190901</startdate><enddate>20190901</enddate><creator>Yang, Que</creator><creator>Wang, Zongrun</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20190901</creationdate><title>Fuzzy Model Applied in Risk Perception and Price Forecasts</title><author>Yang, Que ; Wang, Zongrun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c362t-1d940f1b1e1acffa074e88199cdf8908b451f759d3ef6ad15905fe36ce4ef0fd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Artificial Intelligence</topic><topic>Behavior</topic><topic>Capital markets</topic><topic>Computational Intelligence</topic><topic>Decision making</topic><topic>Economic theory</topic><topic>Engineering</topic><topic>Experiments</topic><topic>Information management</topic><topic>Investment strategy</topic><topic>Investors</topic><topic>Laboratories</topic><topic>Management Science</topic><topic>Markov analysis</topic><topic>Mathematical models</topic><topic>Multiple criterion</topic><topic>Operations Research</topic><topic>Perception</topic><topic>Portfolio investments</topic><topic>Prices</topic><topic>Research methodology</topic><topic>Risk perception</topic><topic>Variables</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Que</creatorcontrib><creatorcontrib>Wang, Zongrun</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>International journal of fuzzy systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Que</au><au>Wang, Zongrun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Fuzzy Model Applied in Risk Perception and Price Forecasts</atitle><jtitle>International journal of fuzzy systems</jtitle><stitle>Int. J. Fuzzy Syst</stitle><date>2019-09-01</date><risdate>2019</risdate><volume>21</volume><issue>6</issue><spage>1906</spage><epage>1918</epage><pages>1906-1918</pages><issn>1562-2479</issn><eissn>2199-3211</eissn><abstract>This study applies a fuzzy model to simulate an evolution of price forecasts among market investors based on their own risk perception and other multiple criteria decision. According to this imitation, we design a capital market laboratory experiment on the basis of Smith et al. (Econometrica 56:1119–1151,
1988
). The experiment sets two groups of experiments to test the investor’s market behaviour under the influence of risk perception. The results show that there is no significant difference in changing prices under the influence of perceived systemic risks and non-systemic risks. However, when market returns become more uncertain, investors’ perceptions of risk significantly affect their trading behaviour. Furthermore, we divide the investors’ investment behaviour into different investment strategies and observe the trading behaviours of the investors with risk perception. In addition, extended analysis shows that under a risk environment, a decline in asset price is related to the amount of cash and assets held by the investors, and the assets purchased in the previous period has no substantial relationship with the asset price in the last period and the forecast accuracy of the investment asset price in the last period.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s40815-019-00651-9</doi><tpages>13</tpages></addata></record> |
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| subjects | Algorithms Artificial Intelligence Behavior Capital markets Computational Intelligence Decision making Economic theory Engineering Experiments Information management Investment strategy Investors Laboratories Management Science Markov analysis Mathematical models Multiple criterion Operations Research Perception Portfolio investments Prices Research methodology Risk perception Variables |
| title | Fuzzy Model Applied in Risk Perception and Price Forecasts |
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