Information aggregation and computational intelligenceLimits to price discovery

被引:3
作者
Shu-Heng Chen
Ragupathy Venkatachalam
机构
[1] National Chengchi University,Department of Economics, AI
关键词
Web 2.0; Computational intelligence; Socialist calculation debate; Text mining; Sentiment analysis; Tacit knowledge; Evolutionary computation; C63; B25; D8; C55;
D O I
10.1007/s40844-016-0048-z
中图分类号
学科分类号
摘要
This study examines the possibility that the computational intelligence (CI) inspired tools can effectively aggregate the rich information generated from the Web 2.0 economy and, thereby, enhance the quality of decision-making. Despite many advancements and commendable applications of CI in recent years, this issue has not been well addressed. We argue that this question is intimately related to the central issue of the socialist calculation debate since the time of Friedrich Hayek. In terms of information aggregation, we examine whether there is a better engineering than the market mechanism. More precisely, we focus on whether the CI-driven sentiment analysis can generate signals like prices and whether CI can process unstructured text data better than the market. We argue that Web 2.0 economy may not be able to set us free from information overload problems that have long coexisted with the presence of markets. We attribute this to the tacitness and subjectivity of knowledge and the recursive (feedback) characteristic of the sentiments. In this sense, Hayek’s fundamental assertion that the effectiveness of the market mechanism may not be so much conditioned on the information and communication technology still applies.
引用
收藏
页码:231 / 252
页数:21
相关论文
共 88 条
[1]  
Aghion P(2011)Incomplete contracts and the theory of the firm: what have we learned over the past 25 years? J Econ Perspect 25 181-197
[2]  
Holden R(2013)A framework for evolutionary algorithms based on Charles Sanders Peirce’s evolutionary semiotics Inf Sci 236 93-108
[3]  
Akhtar J(2006)Undescribable events Rev Econ Stud 73 849-868
[4]  
Koshul B(2013)Sentiments Econometrica 81 739779-8
[5]  
Awais M(2011)100 years of the American economic review: the top 20 articles Am Econ Rev 101 1-348
[6]  
Al-Najjar N(1982)Accurate predictions and fixed point theorems Soc Sci Inf 21 323-622
[7]  
Anderlini L(1982)Accurate predictions and fixed point theorems: a reply to Simon Soc Sci Inf 21 612-8
[8]  
Felli L(1987)Fixed-point theorems and public prediction of social behavior Adv Appl Math 8 17-590
[9]  
Angeletos G-M(2011)Twitter mood predicts the stock market J Comput Sci 2 1-156
[10]  
La’O J(2014)Judgment aggregation in search for the truth Games Econ Behav 87 571-9