IPO underpricing algorithm: Difference between revisions

Revision as of 12:04, 7 January 2015

Revision as of 12:11, 10 July 2015

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In [[supervised learning]] models, there are tests that are needed to pass to reduce mistakes. Usually, when mistakes are encountered i.e. test output does not match test input, the algorithms use [[back propagation]] to fix mistakes. Whereas in [[unsupervised learning]] models, the input is classified based on which problems need to be resolved.

For example, Chou<ref>{{cite journal|last=Chou|first=Shi-Hao |coauthorsauthor2=Yen-Sen Ni and |author3=William T. Lin|title=Forecasting IPO price using GA and ANN simulation|journal=In&nbsp;Proceedings of the 10th WSEAS international conference on Signal processing, computational geometry and artificial vision&nbsp;(ISCGAV'10)|year=2010|pages=145–150|publisher=World Scientific and Engineering Academy and Society (WSEAS)}}</ref> discusses their algorithm for determining the IPO price of [[Baidu]]. They have a three layer algorithm which contains—input level, hidden level, and output level:

* Input level, the data is received unprocessed.

* Hidden level, the data is processed for analyses

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===Rule-based system===

For example, Quintana<ref>{{cite journal|last=Quintana|first=David |coauthorsauthor2=Cristóbal Luque and |author3=Pedro Isasi|title=Evolutionary rule-based system for IPO underpricing prediction|journal=In&nbsp;Proceedings of the 2005 conference on Genetic and evolutionary computation&nbsp;(GECCO '05)|year=2005|pages=983–989}}</ref> first abstracts a model with 7 major variables. The rules evolved from the Evolutionary Computation system developed at Michigan and Pittsburgh:

* Underwriter prestige – Is the underwriter prestigious in role of lead manager? 1 for true, 0 otherwise.

* Price range width – The width of the non-binding reference price range offered to potential customers during the roadshow. This width can be interpreted as a sign of uncertainty regarding the real value of the company and a therefore, as a factor that could influence the initial return.