Black Swan Global Market: Analysis of the Effect of the Covid-19 Death Rate on the Volatility of European Football Club Stock Prices  (Case Study of Juventus F.C., Manchester United, Ajax Amsterdam and Borussia Dortmund)

Limba, Franco Benony; Rijoly, Jacobus Cliff Diky; Tarangi, Margreath I

doi:10.35794/jmbi.v7i3.32690

Cited by 8 publications

(6 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This financial background influence highlights that, in a turbulent period, investors will dump these assets for more liquid ones. Such a scenario is in line with the ‘flight to quality’ response in periods of crisis (Limba et al, 2020). Gimet and Montchaud (2016) emphasise the significant impact of the financial context, illustrating the vulnerability of football stocks to systematic risk.…”

Section: Introductionsupporting

confidence: 60%

Neural networks for estimating Macro Asset Pricing model in football clubs

Alaminos

Esteban

Salas

2023

Intell Sys Acc Fin Mgmt

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionsupporting

confidence: 60%

Neural networks for estimating Macro Asset Pricing model in football clubs

Alaminos

Esteban

Salas

2023

Intell Sys Acc Fin Mgmt

View full text Add to dashboard Cite

show abstract

“…But for patients who have congenital diseases, respiratory problems as well Elderly is very dangerous because it can lead to death. Until early March 2022 with variant omicron, confirmed count Covid-19 in whole world reach 440,928,482 people (Limba et al, 2020) . Whereas which die world as much 5,995,139 people, and 60,792,451 active positive people (still sick), and 374,140,892 patients declared cured based on data from WHO, ECDC, CDC-US, Worldometer.…”

Section: Impact Healthmentioning

confidence: 98%

Policy Strategy for Resolving the Post Pandemi Covid-19 Economic Crisis in Sri Lanka

Wijaretne

2023

ijief

View full text Add to dashboard Cite

This study provides an overview of the condition of the declining economy faced by cleavage world with exists plague pandemic Covid-19 as well as shape policies taken by Sri Lanka in responding to the threat of the economic crisis in future. It can be concluded that the existence of the Covid-19 pandemic has had an impact which is quite large and influential throughout the world. A number of sector affected industry even went bankrupt. With there policies taken by some countries to disconnect the spread of this virus is like barring out entry of foreign nationals into a country, self-quarantine or regional quarantine or restrictions on individual activities that have various impacts sector like sector tourism, economy etc. Individual activity restrictions and the economy has an impact for sectors such as decreased income, decreased purchasing power up to massive increase in layoffs and rising unemployment. This condition if no handled with good and serious in period long worried could raises the threat of a prolonged economic crisis, this will disrupt stability country. Policy fiscal nor monetary is effort which conducted in framework recovery economy national or could prevent happening crisis monetary which deep. The conclusion from this research is that the economy will recover in 2023 after the pandemic COVID-19 needs attention and must be resolved seriously and thoroughly with exists virus this could causing crisis in period long in field economy as well as health.

show abstract

“…Dunia kini sedang menghadapi fenomena Black Swan atau peristiwa yang terjadi secara tak terduga dan menyebabkan kehebohan di pasar keuangan (Limba, Rijoly, & Tarangi, 2020)(Taleb,2007. Peristiwa ini dimulai ketika adanya virus menular yang menyebabkan gangguan pada sistem pernafasan, dan menimbulkan gejala seperti : batuk, sesak napas, demam, nyeri otot, sakit kepala, kehilangan rasa dan penciuman, sakit tenggorokan, pilek/hidung tersumbat, mual (Pusat Informasi & Koordinasi COVID-19 JABAR, 2020).…”

Section: Pendahuluanunclassified

Analisis Prediksi Finansial Distress dengan Metode Altman Z-Score dan Springate Sebelum dan Selama Covid- 19

Rahman

2022

JEHSS

View full text Add to dashboard Cite

This research aims to predict financial distress in property and real estate sector companies, before and during the pandemic of Covid-19 using the Altman Z'-Score and Sprigate S-Score ratio analysis. The population of this research is all property and real estate companies listed on the Indonesian Stock Exchange for the period 2018 to 2020, so the population of this study is 66 companies. The sample was selected based on predetermined purposive sampling criteria. Those selected according to the specified sample criteria were 44 companies. The data analysis technique used the Altman Z-Score and Springate S-Score discriminant analysis techniques. The results of this study indicate an increase in the number of companies in the distressed category (red zone) during the COVID-19 pandemic (in 2020) by 16%, which was twice as high as before the Covid-19 pandemic, which was 7%. This indicates that there are difficulties both financially and in liquidity as well as a decrease in the company's ability to grow, which may lead to bankruptcy.

show abstract

Black Swan Global Market: Analysis of the Effect of the Covid-19 Death Rate on the Volatility of European Football Club Stock Prices (Case Study of Juventus F.C., Manchester United, Ajax Amsterdam and Borussia Dortmund)

Cited by 8 publications

References 6 publications

Neural networks for estimating Macro Asset Pricing model in football clubs

Neural networks for estimating Macro Asset Pricing model in football clubs

Policy Strategy for Resolving the Post Pandemi Covid-19 Economic Crisis in Sri Lanka

Analisis Prediksi Finansial Distress dengan Metode Altman Z-Score dan Springate Sebelum dan Selama Covid- 19

Contact Info

Product

Resources

About