Information leakage in the football transfer market

Fűrész, Diána Ivett; Rappai, Gábor

doi:10.1080/16184742.2020.1797847

Cited by 13 publications

(12 citation statements)

References 49 publications

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“…Based on the types of investors considering the additional benefits in their bidding behaviour is also consistent with the argument that the football sector is only loosely connected to the general economic cycle and plays under its own rules. Fűrész and Rappai (2022) confirm the premise that the great majority of sports investors respond to the news before the formal announcement. Moreover, they indicate that these investors are predominantly optimistic and therefore assume that, for example, the arrival of a new player will translate into improved sporting returns.…”

Section: Why Football?supporting

confidence: 71%

“…Fűrész and Rappai (2022) confirm the premise that the great majority of sports investors respond to the news before the formal announcement. Moreover, they indicate that these investors are predominantly optimistic and therefore assume that, for example, the arrival of a new player will translate into improved sporting returns.…”

Section: Introductionmentioning

confidence: 83%

“…According to these authors, sporting performance means more to the investor than economic performance (Benkraiem et al, 2011;Fűrész & Rappai, 2022).…”

Section: Stock Market Models and Footballmentioning

confidence: 99%

“…This outcome is not unexpected and the reason for the poor performance and high volatility concerning the clubs' shares, is that many of them experience important and regular deficits. However, some studies suggest a discrepancy in stock market behaviour between rational investors and fans (Edmans et al, 2007; Fűrész & Rappai, 2022; Huth, 2019). According to these authors, sporting performance means more to the investor than economic performance (Benkraiem et al, 2011; Fűrész & Rappai, 2022).…”

Section: Introductionmentioning

confidence: 99%

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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: Why Football?supporting

confidence: 71%

Section: Introductionmentioning

confidence: 83%

“…According to these authors, sporting performance means more to the investor than economic performance (Benkraiem et al, 2011;Fűrész & Rappai, 2022).…”

Section: Stock Market Models and Footballmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Neural networks for estimating Macro Asset Pricing model in football clubs

Alaminos

Esteban

Salas

2023

Intell Sys Acc Fin Mgmt

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“…The transfer market for football players takes place in an extremely speculative context where fake information is often leaked by clubs, intermediaries and the various media involved (Fürész and Rappai 2020). Market actors thus prefer to rely on objective valuations before starting any transfer negotiation.…”

Section: Negotiating Player Transfersmentioning

confidence: 99%

Econometric Approach to Assessing the Transfer Fees and Values of Professional Football Players

2021

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Billions of euros are invested every year by professional football clubs for the recruitment of players. How do market actors decide prices? This paper presents an econometric model unveiling the key factors coming into play in determining fees on the transfer market for professional football (soccer) players. The statistical technique used to build the model is multiple linear regression (MLR), with fees paid by clubs as an independent variable. The sample comprises over 2000 transactions of players transferred for money from clubs in the five major European leagues during the period stretching from July 2012 to November 2021. This paper notably highlights the importance of taking into consideration the remaining duration of contracts binding players with the club to which they belong, a factor often neglected in the existing literature. It also shows that a statistical model can explain over 80% of the differences in the transfer fees paid for players. This paper reveals various applications of the approach developed for the football industry to both assess and predict football players’ transfer fees and values: transfer negotiations, club sales or purchases, bank credit, fund raising, financial planning and communication, legal disputes, etc.

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Football players in light of economic value theory: Critical review and conceptualisation

Franceschi,

Brocard,

Follert

et al. 2023

Manage Decis Econ

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Football players represent the key assets of football clubs, and their value determination is therefore at the heart of clubs' investment and decision‐making processes. Unsurprisingly, the topic of player value has attracted the attention of scholars from various disciplines for decades. Despite this, there is a corpus of academic literature, which, although it works empirically with the relevant data, does not discuss any of the concepts related to the terms ‘value’ and ‘price’ in depth. Conversely, there are studies that do so but do not present a unified and coherent concept of the terminologies used. Consequently, no comprehensive definition of the value of football players seems to emerge from the literature. The central aim of this paper is to fill this gap. Based on a critical review of existing literature, we propose a unified framework embedded in subjective value theory, particularly as formulated by the Austrian school of economics. As a result, this work presents a theoretical basis for defining the use value and market value of football players, the comparison of which can improve clubs' decision‐making. In this context, we also discuss the conceptual validity of Transfermarkt values, a widely used crowd‐sourced valuation tool. Overall, we seek to strengthen the link between economic theory and practical management problems in the football industry. Furthermore, our results are not solely limited to football but are also applicable to athlete valuation in other sports.

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Information leakage in the football transfer market

Cited by 13 publications

References 49 publications

Neural networks for estimating Macro Asset Pricing model in football clubs

Neural networks for estimating Macro Asset Pricing model in football clubs

Econometric Approach to Assessing the Transfer Fees and Values of Professional Football Players

Football players in light of economic value theory: Critical review and conceptualisation

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