Human Resources Turnover as an Asset Acquisition, Accumulation and Divesture Process

Fotaki, Maria; Markellos, Raphael N.; Mania, Maria

doi:10.2139/ssrn.1325645

Cited by 9 publications

(10 citation statements)

References 42 publications

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Section: Literature Reviewmentioning

confidence: 99%

“…The existing literature has mainly focused on researching football clubs on the stock market in British clubs (Allouche & Soulez, 2005; Benkraiem et al, 2011; Fotaki et al, 2009; Gannon et al, 2006; Renneboog & Vanbrabant, 2000; Samaiogo, Aglietta et al, 2008). Others are interested in another specific national league, like Turkish clubs (Demir & Danis, 2011; Saraç & Zeren, 2013), German clubs (Stadtmann, 2006), Italian clubs (Boidoa & Fasanob, 2007; Boțoc et al, 2019), Portuguese clubs (Duque & Ferreira, 2005) and a set of European clubs (Baur & McKeating, 2011; Benkraiem et al, 2009; Bernille & Lyandres, 2011; Scholtens & Peenstra, 2009).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Quite a few studies (Allouche & Soulez, 2005; Fotaki et al, 2009; Fűrész & Rappai, 2022) have taken player transfers into account to explicate stock returns. They conclude that, on the one hand, markets consider the players' sale announcement as positive, implying the inflow of money and the reduced charges are better than the players' loss of capital.…”

Section: Literature Reviewmentioning

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: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Neural networks for estimating Macro Asset Pricing model in football clubs

Alaminos

Esteban

Salas

2023

Intell Sys Acc Fin Mgmt

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“…There is extensive existing literature on the link between match results and financial returns in associated football (e.g. Stadtmann, 2004Stadtmann, , 2006Allouche and Soulez, 2008;Benkraiem et al, 2009;Fotaki et al, 2009;Galoppo and Boido, 2020), and different studies vary greatly in terms of the sample composition, time span considered, competitions analyzed, covariates and econometric methodology employed for the estimations. Table 1 presents some of the previous main findings regarding the relationship between soccer teams' performance and stock market reactions.…”

Section: Financial Markets Pricementioning

confidence: 99%

Do financial markets price UEFA Champions League competition events?

Soana

Lippi

Rossi

2022

EMJB

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PurposeThis paper investigates the stock market reaction to three different events related to the UEFA Champions League – the announcements of draws, odds and match results. The aim of the paper is to test whether these events are informative for stock market operators, i.e. whether they produce abnormal returns.Design/methodology/approachApplying the event study methodology, the authors investigate the stock market reaction before (at two events: the draw date and on the release of betting odds) and after the matches of 11 listed soccer teams in the period 2003–2019. The authors also conduct OLS regression analyses in order to disentangle the impact of firm specific variables and match characteristics on cumulative abnormal returns.FindingsThis paper finds that match outcomes affect the stock market performance of listed teams, while the announcements of draws and odds do not. More specifically, the market does not consider match outcomes involving wins and ties as informative events, while it penalizes losing teams. Moreover, investor reactions to events related to the UCL competition depend more on match characteristics than on company specific variables.Originality/valueThe study enriches the ongoing debate about the impact of soccer team results on stock market performance in several ways: using the widest time span ever adopted in this area; focusing on UCL, which is the most important soccer competition played by private clubs; disentangling for the first time the effects of draws, odds release and sporting outcome on stock returns of listed soccer clubs.

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“…Corresponding market reaction to this public information was rarely considered as a research topic within the context of literature. One of the few studies regarding this subject belongs to Fotaki et al (2009). These researchers revealed a negative investor reaction to buying of players for United Kingdom Football Clubs, whereas player sales resulted in a positive investor reaction.…”

Section: Introductionmentioning

confidence: 99%

The Relationship Between Footballer and Head Coach Transfer News and Stock Prices of Sport Clubs

Dayı¹,

Gök²,

Ulusoy³

2018

Proceedings of the 39th International Academic Conference, Amsterdam

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Sportive performances of sports clubs are closely pursued by investors and the effect of match results on stock prices are widely investigated in the literature. On the other hand, whatever the results of the matches might be, the football players and head coaches affect the game by their physical performances, abilities, intelligence and strategic thinking characteristics. Football players and head coaches are the most important assets of the clubs that they work for. Nevertheless, the impact of transfer news of football players and head coaches on the clubs' stock prices have rarely been studied. We aimed to analyze the effects of transfer news of Trabzonspor (TSPOR: Istanbul), one of the four sports clubs traded in Borsa Istanbul, on stock prices within the scope of this study. The transfers exceeding a capital of 1 million Euros during the period of 2013-2017 were investigated by event study analysis. By analyzing 47 events related to football players and 15 events to head coaches, it was found that the contract news of head coaches had more prominent effects on returns than that of footballers'.

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Human Resources Turnover as an Asset Acquisition, Accumulation and Divesture Process

Abstract: . The usual disclaimer applies. The present paper supersedes an earlier version by the same authors entitled "Are Human Resources linked to Shareholder Wealth? An M&A perspective using data from the UK Football Industry".

Cited by 9 publications

References 42 publications

Neural networks for estimating Macro Asset Pricing model in football clubs

Neural networks for estimating Macro Asset Pricing model in football clubs

Do financial markets price UEFA Champions League competition events?

The Relationship Between Footballer and Head Coach Transfer News and Stock Prices of Sport Clubs

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