Human resources turnover as an asset acquisition and divestiture process: Evidence from the <scp>U.K.</scp> football industry

Fotaki, Maria; Kourtis, Apostolos; Markellos, Raphael N.

doi:10.1002/ijfe.2558

Cited by 7 publications

(2 citation statements)

References 93 publications

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“…Consequently, the perception of instant spending and the raising of wages and social security payments is dominant, rather than the capital-enhancing role of the players' capital. Fotaki et al (2007) examined football player transfers in the UK from the viewpoint of human resource management. Their findings show that transfers of players and managers impact significantly share prices around the time of the event, although this effect varies.…”

Section: Literature Reviewmentioning

confidence: 99%

Neural networks for estimating Macro Asset Pricing model in football clubs

Alaminos

Esteban

Salas

2023

Intell Sys Acc Fin Mgmt

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Summary The recent crisis caused by COVID‐19 directly affected consumption habits and the stability sof financial markets. In particular, the football industry has been hit hard by this pandemic and therefore has more volatile stock prices. Given this new scenario, further research is needed to accurately estimate the value of the shares of football clubs. In this paper, we estimate an asset pricing model in football clubs with different compositions of risk nature using non‐linear techniques of artificial neural networks. Usually, asset pricing models have been estimated with linear methods such as ordinary least squares. Our results show a precision higher than 90% for all the estimated models, which far exceeds those shown by linear methods in the previous literature. We find that the residual represents about 40% of the variance of the price‐dividend ratio. Long‐term risks follow in importance, and above all, the habit component and its behaviour in the face of changes. The importance of the residual component exists due to a low correlation between the asset price and consumer behaviour, but to a much lesser extent than that shown in previous studies. The estimation carried out with artificial neural networks, both the Deep Learning methods and especially the Quantum Neural Network, opens up new possibilities to estimate more efficiently the pricing of financial assets in the football industry.

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Section: Literature Reviewmentioning

confidence: 99%

Neural networks for estimating Macro Asset Pricing model in football clubs

Alaminos

Esteban

Salas

2023

Intell Sys Acc Fin Mgmt

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“…And generally low cultural quality of students [7][8]. The reason for this is the contradictory relationship between supply and demand in the youth soccer player reserve talent cultivation system, which has resulted in low investment in the cultivation of youth talent and low success rate, while on the demand side of the cultivated soccer players have low contribution rate to the clubs, and there are great problems with the students in the issues of further education and employment [9][10]. To analyze the problem of supply and demand contradiction in the youth soccer talent training system, the main system innovation to realize the effective supply of the system, to strengthen the innovation league system as an effective demand, hope to amend and improve the existing training system on the basis of the existing training system, in order to focus on solving the problem of the reserve talent training system of China's youth soccer players in the contradiction between the supply and demand [11].…”

Section: Introductionmentioning

confidence: 99%

Construction of Chinese Youth Football Players Cultivation System Based on Discrete Regression Algorithm

2024

Applied Mathematics and Nonlinear Sciences

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In the course of the development of Chinese soccer, the development of youth soccer plays a very important role, so it is very important to build a scientific training system for youth soccer. In this paper, Bootstrap resampling technique is used to train the multidimensional logistic regression algorithm, and the genetic algorithm is used to optimize the parameters, which in turn improves the logistic regression algorithm. The HBase discrete regression algorithm model is constructed by combining the improved logistic regression algorithm with the HBase database system. Experiments were conducted on the running ability, performance prediction, and mental health disorder detection of Chinese youth soccer players, and finally the clubs in five places that improved the training system of youth soccer players through the HBase discrete regression algorithm were evaluated. The experimental results show that the maximum instantaneous explosive power of the athletes is close to 80 m/s2. In the performance prediction experiment, the error between the performance of the youth soccer players predicted based on the HBase discrete regression algorithm and the real value is less than 0.5. In the five clubs that have improved the cultivation system of the youth soccer athletes based on the HBase discrete regression algorithm, the overall average score of the evaluation of the cultivation system is more than 83 points.. This study has the potential to help improve the development of youth soccer in China.

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Does CSR governance matters for corporate value creation: exploring the nexus between corporate sustainability governance and investment efficiency of acquirers in Pakistan

Rustam

Geng

2022

Environ Sci Pollut Res

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Human resources turnover as an asset acquisition and divestiture process: Evidence from the U.K. football industry

Cited by 7 publications

References 93 publications

Neural networks for estimating Macro Asset Pricing model in football clubs

Neural networks for estimating Macro Asset Pricing model in football clubs

Construction of Chinese Youth Football Players Cultivation System Based on Discrete Regression Algorithm

Does CSR governance matters for corporate value creation: exploring the nexus between corporate sustainability governance and investment efficiency of acquirers in Pakistan

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