IPO mechanism selection by using Classification and Regression Trees

Küçükkocaoğlu, Güray; Sezgin, Özge

doi:10.1007/s11135-011-9430-4

Cited by 5 publications

(6 citation statements)

References 43 publications

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“…The classification tree is used when there is a need to classify the data. The regression tree is used when the dependent variable is continuous [33].…”

Section: Methodsmentioning

confidence: 99%

“…However, there are numerous other examples in this area [45,46]. In economics, CART has been applied to decide the best way to manage business plans [47], or for example, to predict the Initial Public Offering (IPO) method [33]. For water purposes related to environmental applications, this algorithm can help predict rainfall and groundwater level [48] and also, in groundwater potential for sustainable planning, irrigation, and town water supply purposes to achieve water demand goals [49].…”

Section: Methodsmentioning

confidence: 99%

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Water Consumption Range Prediction in Huelva’s Households using Classification and Regression Trees

Bermejo-Martín¹,

Rodríguez‐Monroy²,

Guerrero³

2020

Preprint

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This paper uses the numerical results of surveys sent to Huelva’s (Andalusia, Spain) households to determine the degree of knowledge they have about the urban water cycle, needs, values, and attitudes regarding water in an intermediary city with low water stress. In previous research, we achieved three different households’ clusters. The first one grouped households with high knowledge of the integral water cycle and a positive attitude to smart devices at home. The second cluster described households with low knowledge of the integral water cycle and high sensitivity to price. The third one showed average knowledge and predisposition to have a closer relationship with the water company. This paper continues with this research line, applying Classification and Regression Trees (CART) to determine which hierarchy of variables/factors/ independent components obtained from the surveys are the decisive ones to predict the range of household water consumption in Huelva. Positive attitudes towards improved cleaning habits for personal or household purposes are the highest hierarchy component to predict the water consumption range. Second in the hierarchy, the variable Knowledge Global Score about the integral urban water cycle, associated with water literacy, also contributes to predicting the water consumption range. Together with the three clusters obtained previously, these results will allow us to design water demand management strategies (WDM) fit for purpose that enable Huelva’s households to use water more efficiently.

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“…The classification tree is used when there is a need to classify the data. The regression tree is used when the dependent variable is continuous [33].…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Water Consumption Range Prediction in Huelva’s Households using Classification and Regression Trees

Bermejo-Martín¹,

Rodríguez‐Monroy²,

Guerrero³

2020

Preprint

View full text Add to dashboard Cite

show abstract

“…IPO underpricing has been reported for almost all countries and is usually referred as one of the financial theory related unsolved "puzzles" (see, for instance, Loughran et al, 1994;Loughran and Ritter, 1995;Jenkinson, 2001;Ritter and Welch, 2002;and Ritter, 2003). Several research hypotheses have been developed to examine the determinants of the allocation mechanism choice and the association between underpricing and the usage of specific IPO allocation mechanisms (see, among others, Benveniste and Busada, 1997;Wu, 2004;Ma and Faff, 2007;and Kucukkocaoglu and Alp, 2012).…”

Section: Introductionmentioning

confidence: 99%

An Empirical Analysis of IPOs and SEOs: Evidence from the Chinese Stock Markets

2014

SSRN Journal

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“…The classification tree is used when there is a need to classify the data. The regression tree is used when the dependent variable is continuous [45].…”

mentioning

confidence: 99%

“…This best separate point is checked by the Gini index [46]: "Gini is a measure of impurity computed by counting the frequency of events that how often a randomly chosen data instance is wrongly labeled, given that that instance is to be randomly labeled based on the distribution of class labels [45]".…”

mentioning

confidence: 99%

Water Consumption Range Prediction in Huelva’s Households Using Classification and Regression Trees

Bermejo-Martín

Rodríguez‐Monroy

Guerrero

2021

Water

View full text Add to dashboard Cite

This paper uses the numerical results of surveys sent to Huelva’s (Andalusia, Spain) households to determine the degree of knowledge they have about the urban water cycle, needs, values, and attitudes regarding water in an intermediary city with low water stress. In previous research, we achieved three different households’ clusters. The first one grouped households with high knowledge of the integral water cycle and a positive attitude to smart devices at home. The second cluster described households with low knowledge of the integral water cycle and high sensitivity to price. The third one showed average knowledge and predisposition to have a closer relationship with the water company. This paper continues with this research line, applying Classification and Regression Trees (CART) to determine which hierarchy of variables/factors/independent components obtained from the surveys are the decisive ones to predict the range of household water consumption in Huelva. Positive attitudes towards improved cleaning habits for personal or household purposes are the highest hierarchy component to predict the water consumption range. Second in the hierarchy, the variable Knowledge Global Score about the integral urban water cycle, associated with water literacy, also contributes to predicting the water consumption range. Together with the three clusters obtained previously, these results will allow us to design water demand management strategies (WDM) fit for purpose that enable Huelva’s households to use water more efficiently.

show abstract

IPO mechanism selection by using Classification and Regression Trees

Cited by 5 publications

References 43 publications

Water Consumption Range Prediction in Huelva’s Households using Classification and Regression Trees

Water Consumption Range Prediction in Huelva’s Households using Classification and Regression Trees

An Empirical Analysis of IPOs and SEOs: Evidence from the Chinese Stock Markets

Water Consumption Range Prediction in Huelva’s Households Using Classification and Regression Trees

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