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Here the demand is increasing, as with [[Veblen good]]s or stock buyers with the [[Hot-hand fallacy#Consumers|"hot hand"]] fallacy preferring to buy more successful stocks and sell those that are less successful.<ref name="Johnson2005">{{cite journal|last=Johnson|first=Joseph|author2=Tellis, G.J. |author3=Macinnis, D.J. |s2cid=145211986|title=Losers, Winners, and Biased Trades|journal=Journal of Consumer Research|year=2005|volume=2|issue=32|pages=324–329|doi=10.1086/432241}}</ref>
 
Here the demand is increasing, as with [[Veblen good]]s or stock buyers with the [[Hot-hand fallacy#Consumers|"hot hand"]] fallacy preferring to buy more successful stocks and sell those that are less successful.<ref name="Johnson2005">{{cite journal|last=Johnson|first=Joseph|author2=Tellis, G.J. |author3=Macinnis, D.J. |s2cid=145211986|title=Losers, Winners, and Biased Trades|journal=Journal of Consumer Research|year=2005|volume=2|issue=32|pages=324–329|doi=10.1086/432241}}</ref>
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Here the demand is increasing, as with Veblen goods or stock buyers with the "hot hand" fallacy preferring to buy more successful stocks and sell those that are less successful.
 
Here the demand is increasing, as with Veblen goods or stock buyers with the "hot hand" fallacy preferring to buy more successful stocks and sell those that are less successful.
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Vernon L. Smith used these techniques to model sociability in economics. There, a model correctly predicts that agents are averse to resentment and punishment, and that there is an asymmetry between gratitude/reward and resentment/punishment.  The classical Nash equilibrium is shown to have no predictive power for that model, and the Gibbs equilibrium must be used to predict phenomena outlined in Humanomics.
 
Vernon L. Smith used these techniques to model sociability in economics. There, a model correctly predicts that agents are averse to resentment and punishment, and that there is an asymmetry between gratitude/reward and resentment/punishment.  The classical Nash equilibrium is shown to have no predictive power for that model, and the Gibbs equilibrium must be used to predict phenomena outlined in Humanomics.
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弗农 · l · 史密斯利用这些技巧为经济学中的社交性建立了模型。在这里,一个模型正确地预测了代理人厌恶怨恨和惩罚,以及感激/奖励和怨恨/惩罚之间的不对称。经典的纳什均衡点模型对这个模型没有预测能力,吉布斯平衡必须用来预测在 Humanomics 概述的现象。
      
[[Vernon L. Smith]] used these techniques to model sociability in economics.<ref name = "CaSm">
 
[[Vernon L. Smith]] used these techniques to model sociability in economics.<ref name = "CaSm">
    
{{cite journal|author1 = Michael J. Campbell | author2 = [[Vernon L. Smith]] | title = An elementary humanomics approach to boundedly rational quadratic models | journal = Physica A |year=2020| volume = 562 | page = 125309 |doi=10.1016/j.physa.2020.125309| url =https://www.researchgate.net/publication/343657559}}</ref> There, a model correctly predicts that agents are averse to resentment and punishment, and that there is an asymmetry between gratitude/reward and resentment/punishment.  The classical Nash equilibrium is shown to have ''no'' predictive power for that model, and the Gibbs equilibrium must be used to predict phenomena outlined in ''Humanomics''.<ref name = "SmWi">{{cite book|author = [[Vernon L. Smith]] and [[Bart J. Wilson]]|date=2019|title=Humanomics: Moral Sentiments and the Wealth of Nations for the Twenty-First Century|url=https://www.cambridge.org/core/books/humanomics/1B4064A206BD99DB36E794B53ADF8BB4|doi = 10.1017/9781108185561|publisher=Cambridge University Press|isbn=9781108185561}}</ref>
 
{{cite journal|author1 = Michael J. Campbell | author2 = [[Vernon L. Smith]] | title = An elementary humanomics approach to boundedly rational quadratic models | journal = Physica A |year=2020| volume = 562 | page = 125309 |doi=10.1016/j.physa.2020.125309| url =https://www.researchgate.net/publication/343657559}}</ref> There, a model correctly predicts that agents are averse to resentment and punishment, and that there is an asymmetry between gratitude/reward and resentment/punishment.  The classical Nash equilibrium is shown to have ''no'' predictive power for that model, and the Gibbs equilibrium must be used to predict phenomena outlined in ''Humanomics''.<ref name = "SmWi">{{cite book|author = [[Vernon L. Smith]] and [[Bart J. Wilson]]|date=2019|title=Humanomics: Moral Sentiments and the Wealth of Nations for the Twenty-First Century|url=https://www.cambridge.org/core/books/humanomics/1B4064A206BD99DB36E794B53ADF8BB4|doi = 10.1017/9781108185561|publisher=Cambridge University Press|isbn=9781108185561}}</ref>
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弗农 · l · 史密斯利用这些技巧为经济学中的社交性建立了模型。在这里,一个模型正确地预测了代理人厌恶怨恨和惩罚,以及感激/奖励和怨恨/惩罚之间的不对称。经典的纳什均衡点模型对这个模型没有预测能力,吉布斯平衡必须用来预测在 Humanomics 概述的现象。
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Quantifiers derived from [[information theory]] were used in several papers by econophysicist [http://www.aureliofernandez.net/ Aurelio F. Bariviera] and coauthors in order to assess the degree in the informational efficiency of stock markets.<ref>{{cite journal |author=Zunino, L., Bariviera, A.F., Guercio, M.B., Martinez, L.B. and Rosso, O.A.|title=On the efficiency of sovereign bond markets |journal=Physica A: Statistical Mechanics and Its Applications|volume= 391|pages= 4342–4349|year=2012 |doi=10.1016/j.physa.2012.04.009 | issue = 18|bibcode = 2012PhyA..391.4342Z |url=http://ri.conicet.gov.ar/bitstream/11336/59368/11/CONICET_Digital_Nro.2499931a-041e-4174-8911-3017a0595f19_J.pdf|hdl=11336/59368 |s2cid=122129979 }}</ref>
    
Quantifiers derived from information theory were used in several papers by econophysicist [http://www.aureliofernandez.net/ Aurelio F. Bariviera] and coauthors in order to assess the degree in the informational efficiency of stock markets.
 
Quantifiers derived from information theory were used in several papers by econophysicist [http://www.aureliofernandez.net/ Aurelio F. Bariviera] and coauthors in order to assess the degree in the informational efficiency of stock markets.
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Quantifiers derived from [[information theory]] were used in several papers by econophysicist [http://www.aureliofernandez.net/ Aurelio F. Bariviera] and coauthors in order to assess the degree in the informational efficiency of stock markets.<ref>{{cite journal |author=Zunino, L., Bariviera, A.F., Guercio, M.B., Martinez, L.B. and Rosso, O.A.|title=On the efficiency of sovereign bond markets |journal=Physica A: Statistical Mechanics and Its Applications|volume= 391|pages= 4342–4349|year=2012 |doi=10.1016/j.physa.2012.04.009 | issue = 18|bibcode = 2012PhyA..391.4342Z |url=http://ri.conicet.gov.ar/bitstream/11336/59368/11/CONICET_Digital_Nro.2499931a-041e-4174-8911-3017a0595f19_J.pdf|hdl=11336/59368 |s2cid=122129979 }}</ref>
      
Zunino et al. use an innovative statistical tool in the financial literature: the complexity-entropy causality plane. This Cartesian representation establish an efficiency ranking of different markets and distinguish different bond market dynamics. Moreover, the authors conclude that the classification derived from the complexity-entropy causality plane is consistent with the qualifications assigned by major rating companies to the sovereign instruments. A similar study developed by Bariviera et al. explore the relationship between credit ratings and informational efficiency of a sample of corporate bonds of US oil and energy companies using also the complexity–entropy causality plane. They find that this classification agrees with the credit ratings assigned by Moody's.
 
Zunino et al. use an innovative statistical tool in the financial literature: the complexity-entropy causality plane. This Cartesian representation establish an efficiency ranking of different markets and distinguish different bond market dynamics. Moreover, the authors conclude that the classification derived from the complexity-entropy causality plane is consistent with the qualifications assigned by major rating companies to the sovereign instruments. A similar study developed by Bariviera et al. explore the relationship between credit ratings and informational efficiency of a sample of corporate bonds of US oil and energy companies using also the complexity–entropy causality plane. They find that this classification agrees with the credit ratings assigned by Moody's.
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