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Relationship of Cryptocurrencies with Gambling and Addiction

Year 2023, Volume 15, Issue 2, 1 - 1, 30.06.2023

Abstract

Cryptocurrencies has been considered as both an investment tool and a great invention that will replace money and change the world order. Although crypto currency trading has been investigated in many aspects, the psychological dimension that directly affects investors has often been ignored. Control of cryptocurrency trading is in the hands of investors rather than a central authority or institution. Thus, the value of cryptocurrencies changes with the reactions of investors. This situation suggests that psychological factors may be more prominent in cryptocurrency trading. Cryptocurrency trading has many similarities with gambling and betting, such as risk taking, getting quick returns, extreme gains or losses. Some significant components of behavioral addiction are also seen in individuals who spend so much time with cryptocurrency trading. The purpose of this article is to provide a better understanding of the psychological effects of cryptocurrency trading, which has entered our lives over a relatively brief period of time and reached millions of investors.

References

  • Ajaz T, Kumar AS (2018) Herding in crypto-currency markets. Ann Fin Econ, 13:1-15.
  • Amerikan Psikiyatri Birliği (1994) Mental Bozuklukların Tanısal ve Sayımsal El Kitabı, Dördüncü Baskı (DSM-IV) (Çev. Köroğlu, E.) Hekimler Yayın Birliği, Ankara, 1995.
  • Amerikan Psikiyatri Birliği (2013) Ruhsal Bozuklukların Tanısal ve Sayımsal El Kitabı, Beşinci Baskı (DSM-V) (Çev. Köroğlu, E.) Hekimler Yayın Birliği, Ankara, 2013.
  • Androulakis-Korakakis P, Michalopoulos N, Steele J (2021) Are different types of trading a potential form of gambling? https://web-cdn.gamban.com/Public_Report_Is_trading_a_form_of_gambling.pdf
  • Arthur J, Delfabbro P, Williams R (2016) Is there A relationship between participation in gambling activities and participation in high-risk stock trading? J Gambl Bus Econ, 9:34–53.
  • Arthur JN, Delfabbro P (2017) Day traders in South Australia: Similarities and differences with traditional gamblers. J Gambl Stud, 33:855–866.
  • Arthur JN, Williams RJ, Delfabbro P (2016) The conceptual and empirical relationship between gambling, investing, and speculation. J Behav Addict, 5:580–591.
  • Baddeley M (2010) Herding, social influence and economic decision-making: socio-psychological and neuroscientific analyses. Philos Trans R Soc Lond B Biol Sci, 365:281–290.
  • de Benoist A (1996) Confronting Globalization. Telos, 108:117–137.
  • Bouri E, Gupta R, Roubaud D (2019) Herding behaviour in cryptocurrencies. Fin Res Lett, 29:216–221.
  • Bracha A, Brown DJ (2012) Affective decision making: A theory of optimism bias. Games Econ Behav, 75:67–80.
  • Casale S, Rugai L, Fioravanti G (2018) Exploring the role of positive metacognitions in explaining the association between the fear of missing out and social media addiction. Addict Behav, 85:83-87
  • Chohan UW (2021) Cryptocurrencies and Inequality. In: Cryptofinance:49-62. World Scientific.
  • Ciaian P, Rajcaniova M, Kancs D (2016) The economics of BitCoin price formation. Appl Econ, 48:1799–1815.
  • Civitarese J, Mendes L (2018) Bad News, Technical Development and Cryptocurrencies Stability. Technical Development and Cryptocurrencies Stability. Available at SSRN: https://ssrn.com/abstract=3154124 or http://dx.doi.org/10.2139/ssrn.3154124 Coinmarketcap.com (2021). (Accessed September 1, 2021).
  • Comings DE, Blum K (2000) Reward deficiency syndrome: genetic aspects of behavioral disorders. Prog Brain Res, 126:325-341.
  • Delfabbro P, King D, Gainsbury SM (2020) Understanding gambling and gaming skill and its implications for the convergence of gaming with electronic gaming machines. Int Gambl Stud, 20:171–183.
  • Delfabbro P, King D, Williams J, Georgiou N (2021) Cryptocurrency trading, gambling and problem gambling. Addict Behav, 122:107021.
  • Delfabbro P, King D (2021) Is there a continuum of behavioural dependence in problem gambling? Evidence from 15 years of Australian prevalence research. Int J Ment Health Addict, 8:1-3.
  • Delfabbro P, King DL, Williams J (2021) The psychology of cryptocurrency trading: Risk and protective factors. J Behav Addict, 10:201–207.
  • Dixon MR, Giroux I, Jacques C, Grégoire P (2018) What characterizes excessive online stock trading? A qualitative study. J Gambl Issu, 38:8-26.
  • Gagarina M, Nestik T, Drobysheva T (2019) Social and psychological predictors of youths’ attitudes to cryptocurrency. Behav Sci (Basel), 9:118.
  • Gainsbury SM, Blaszczynski A (2017) How blockchain and cryptocurrency technology could revolutionize online gambling. Gaming Law Rev, 21:482–492.
  • Gao X, Lin T-C (2015) Do individual investors treat trading as a fun and exciting gambling activity? Evidence from repeated natural experiments. Rev Financ Stud, 28:2128–2166.
  • Goudriaan AE, Oosterlaan J, De Beurs E, Van Den Brink W (2006) Neurocognitive functions in pathological gambling: a comparison with alcohol dependence, Tourette syndrome and normal controls. Addiction, 101:534-547.
  • Grall-Bronnec M, Sauvaget A, Boutin C, Bulteau S, Jiménez-Murcia S, Fernández-Aranda F et al (2017) Excessive trading, a gambling disorder in its own right? A case study on a French disordered gamblers cohort. Addict Behav, 64:340–348.
  • Griffiths M (2005) A ‘components’ model of addiction within a biopsychosocial framework. J Subst Use, 10:191–197.
  • Griffiths M (2018) Hot topics in gambling: Gambling blocking apps, loot boxes, and crypto-trading addiction. Online Gambling Lawyer, 17:9-11.
  • Guglielmo R, Ioime L, Janiri L (2016) Is Pathological Trading an Overlooked Form of Addiction?. Addict Health, 8:207-209.
  • Ising A, Pompian M (2006) Behavioral Finance and Wealth Management-How to Build Optimal Portfolios That Account for Investor Biases. Financial Markets and Portfolio Management, 21:491.
  • Ito TA, Larsen JT, Smith NK, Cacioppo JT (1998) Negative information weighs more heavily on the brain: the negativity bias in evaluative categorizations. J Pers Soc Psychol, 75:887–900.
  • Kahneman D, Tversky A (1979) Prospect theory: An analysis of decision under risk. Econometrica, 47:263.
  • Kartini K, Nahda K (2021) Behavioral biases on investment decision: A case study in Indonesia. The Journal of Asian Finance, Economics and Business, 8:1231-1240.
  • Kim HJ, Hong JS, Hwang HC, Kim SM, Han DH (2020) Comparison of psychological status and investment style between Bitcoin investors and share investors. Front Psychol, 11:502295.
  • Kinari Y (2016) Properties of expectation biases: Optimism and overconfidence. J Behav Exp Finance, 10:32–49.
  • Kumar A (2009) Who gambles in the stock market? J Finance, 64:1889–1933.
  • Kumar S, Goyal N (2015) Behavioural biases in investment decision making – a systematic literature review. Qual Res Fin Mark, 7:88–108.
  • Marks I (1990) Behavioural (non‐chemical) addictions. Br J Addict, 85:1389-1394.
  • McClure SM, Bickel WK (2014) A dual-systems perspective on addiction: Contributions from neuroimaging and cognitive training. Ann N Y Acad Sci, 13:62-78.
  • Meng J, Fu F (2020) Understanding gambling behaviour and risk attitudes using cryptocurrency-based casino blockchain data. R Soc Open Sci, 7:201446.
  • Mills DJ, Nower L (2019) Preliminary findings on cryptocurrency trading among regular gamblers: A new risk for problem gambling? Addict Behav, 92:136–140.
  • Mosenhauer M, Newall PWS, Walasek L (2021) The stock market as a casino: Associations between stock market trading frequency and problem gambling. J Behav Addict, 10:683–689.
  • Naim-Fell J, Zangen A (2013) Addiction. Handb Clin Neurol, 116:613-630.
  • Nestler EJ (2005) Is there a common molecular pathway for addiction?. Nat Neurosci, 8:1445-1449.
  • Othman AHA, Musa Alhabshi S, Kassim S, Abdullah A, Haron R (2020) The impact of monetary systems on income inequity and wealth distribution: A case study of cryptocurrencies, fiat money and gold standard. Int J Emerg Mark, 15:1161–1183.
  • Pezzani F (2018) Bitcoin: the bewildering illusion of easy wealth. Acad Sci J, 3:1109–1113.
  • Pfaffenberger B (2000) The rhetoric of dread: Fear, uncertainty, and doubt (FUD) in information technology marketing. Knowl Technol Policy, 13:78–92.
  • Piper ME (2015). Withdrawal: Expanding a key addiction construct. Nicotine Tob Res, 17:1405-1415.
  • Przybylski AK, Murayama K, DeHaan CR, Gladwell V (2013) Motivational, emotional, and behavioral correlates of fear of missing out. Comput Human Behav, 29:1841–1848.
  • Scholten OJ, Zendle D, Walker JA (2020) Inside the decentralised casino: A longitudinal study of actual cryptocurrency gambling transactions. PLoS One, 15:e0240693.
  • Senarathne CW (2021) Gambling behaviour in the cryptocurrency market. In: Research Anthology on Blockchain Technology in Business, Healthcare, Education, and Government:1536–1552, IGI Global.
  • Spyrou S (2013) Herding in financial markets: a review of the literature. Rev Behav Fin, 5:175–194.
  • Steinmetz F, von Meduna M, Ante L, Fiedler I (2021) Ownership, uses and perceptions of cryptocurrency: Results from a population survey. Technol Forecast Soc Change, 173:121073.
  • Sudzina F, Dobeš M, Pavlíček A (2021) Towards the psychological profile of cryptocurrency early adopters: Overconfidence and self-control as predictors of cryptocurrency use. Current Psychology, 1-5.
  • Tversky A, Kahneman D (1974) Judgment under uncertainty: Heuristics and biases: Biases in judgments reveal some heuristics of thinking under uncertainty. Science, 185:1124–1131.
  • Vidal-Tomás D, Ibáñez AM, Farinós JE (2019) Herding in the cryptocurrency market: CSSD and CSAD approaches. Fin Res Lett, 30:181–186.
  • Youn H, Choi J-S, Kim D-J, Choi S-W (2016) Development and validation of a stock addiction inventory (SAI). Ann Gen Psychiatry, 15:1-7.

Kripto Paraların Kumar ve Bağımlılık ile İlişkisi

Year 2023, Volume 15, Issue 2, 1 - 1, 30.06.2023

Abstract

Kripto paralar, hem bir yatırım aracı hem de paranın yerini alacak ve dünya düzenini değiştirecek büyük bir icat olarak görülmektedir. Pek çok yönüyle araştırılan kripto para ticaretinin, yatırımcıları doğrudan etkileyen psikolojik boyutu genellikle göz ardı edilmiştir. Kripto para ticaretinin kontrolü, merkezi bir otorite ya da kurumdan ziyade yatırımcıların elindedir. Böylece kripto paraların değerleri, yatırımcıların hareketleriyle değişiklik göstermektedir. Bu durum, kripto para ticaretinde psikolojik faktörlerin daha ön planda olabileceğini düşündürmektedir. Risk alma, hızlı sonuç elde etme, tutarsız kazanç ya da kayıp gibi özellikleriyle kripto para ticareti, kumar ve bahis ile birçok benzerliğe sahiptir. Kripto para ticareti ile yoğun şekilde uğraşan bireylerde davranışsal bağımlılığın bazı önemli bileşenleri de görülmektedir. Bu makalenin amacı, hayatımıza kısa sürede girerek milyonlarca yatırımcıya ulaşan kripto para ticaretinin psikolojik yansımalarının daha net biçimde anlaşılmasını sağlamaktır.

References

  • Ajaz T, Kumar AS (2018) Herding in crypto-currency markets. Ann Fin Econ, 13:1-15.
  • Amerikan Psikiyatri Birliği (1994) Mental Bozuklukların Tanısal ve Sayımsal El Kitabı, Dördüncü Baskı (DSM-IV) (Çev. Köroğlu, E.) Hekimler Yayın Birliği, Ankara, 1995.
  • Amerikan Psikiyatri Birliği (2013) Ruhsal Bozuklukların Tanısal ve Sayımsal El Kitabı, Beşinci Baskı (DSM-V) (Çev. Köroğlu, E.) Hekimler Yayın Birliği, Ankara, 2013.
  • Androulakis-Korakakis P, Michalopoulos N, Steele J (2021) Are different types of trading a potential form of gambling? https://web-cdn.gamban.com/Public_Report_Is_trading_a_form_of_gambling.pdf
  • Arthur J, Delfabbro P, Williams R (2016) Is there A relationship between participation in gambling activities and participation in high-risk stock trading? J Gambl Bus Econ, 9:34–53.
  • Arthur JN, Delfabbro P (2017) Day traders in South Australia: Similarities and differences with traditional gamblers. J Gambl Stud, 33:855–866.
  • Arthur JN, Williams RJ, Delfabbro P (2016) The conceptual and empirical relationship between gambling, investing, and speculation. J Behav Addict, 5:580–591.
  • Baddeley M (2010) Herding, social influence and economic decision-making: socio-psychological and neuroscientific analyses. Philos Trans R Soc Lond B Biol Sci, 365:281–290.
  • de Benoist A (1996) Confronting Globalization. Telos, 108:117–137.
  • Bouri E, Gupta R, Roubaud D (2019) Herding behaviour in cryptocurrencies. Fin Res Lett, 29:216–221.
  • Bracha A, Brown DJ (2012) Affective decision making: A theory of optimism bias. Games Econ Behav, 75:67–80.
  • Casale S, Rugai L, Fioravanti G (2018) Exploring the role of positive metacognitions in explaining the association between the fear of missing out and social media addiction. Addict Behav, 85:83-87
  • Chohan UW (2021) Cryptocurrencies and Inequality. In: Cryptofinance:49-62. World Scientific.
  • Ciaian P, Rajcaniova M, Kancs D (2016) The economics of BitCoin price formation. Appl Econ, 48:1799–1815.
  • Civitarese J, Mendes L (2018) Bad News, Technical Development and Cryptocurrencies Stability. Technical Development and Cryptocurrencies Stability. Available at SSRN: https://ssrn.com/abstract=3154124 or http://dx.doi.org/10.2139/ssrn.3154124 Coinmarketcap.com (2021). (Accessed September 1, 2021).
  • Comings DE, Blum K (2000) Reward deficiency syndrome: genetic aspects of behavioral disorders. Prog Brain Res, 126:325-341.
  • Delfabbro P, King D, Gainsbury SM (2020) Understanding gambling and gaming skill and its implications for the convergence of gaming with electronic gaming machines. Int Gambl Stud, 20:171–183.
  • Delfabbro P, King D, Williams J, Georgiou N (2021) Cryptocurrency trading, gambling and problem gambling. Addict Behav, 122:107021.
  • Delfabbro P, King D (2021) Is there a continuum of behavioural dependence in problem gambling? Evidence from 15 years of Australian prevalence research. Int J Ment Health Addict, 8:1-3.
  • Delfabbro P, King DL, Williams J (2021) The psychology of cryptocurrency trading: Risk and protective factors. J Behav Addict, 10:201–207.
  • Dixon MR, Giroux I, Jacques C, Grégoire P (2018) What characterizes excessive online stock trading? A qualitative study. J Gambl Issu, 38:8-26.
  • Gagarina M, Nestik T, Drobysheva T (2019) Social and psychological predictors of youths’ attitudes to cryptocurrency. Behav Sci (Basel), 9:118.
  • Gainsbury SM, Blaszczynski A (2017) How blockchain and cryptocurrency technology could revolutionize online gambling. Gaming Law Rev, 21:482–492.
  • Gao X, Lin T-C (2015) Do individual investors treat trading as a fun and exciting gambling activity? Evidence from repeated natural experiments. Rev Financ Stud, 28:2128–2166.
  • Goudriaan AE, Oosterlaan J, De Beurs E, Van Den Brink W (2006) Neurocognitive functions in pathological gambling: a comparison with alcohol dependence, Tourette syndrome and normal controls. Addiction, 101:534-547.
  • Grall-Bronnec M, Sauvaget A, Boutin C, Bulteau S, Jiménez-Murcia S, Fernández-Aranda F et al (2017) Excessive trading, a gambling disorder in its own right? A case study on a French disordered gamblers cohort. Addict Behav, 64:340–348.
  • Griffiths M (2005) A ‘components’ model of addiction within a biopsychosocial framework. J Subst Use, 10:191–197.
  • Griffiths M (2018) Hot topics in gambling: Gambling blocking apps, loot boxes, and crypto-trading addiction. Online Gambling Lawyer, 17:9-11.
  • Guglielmo R, Ioime L, Janiri L (2016) Is Pathological Trading an Overlooked Form of Addiction?. Addict Health, 8:207-209.
  • Ising A, Pompian M (2006) Behavioral Finance and Wealth Management-How to Build Optimal Portfolios That Account for Investor Biases. Financial Markets and Portfolio Management, 21:491.
  • Ito TA, Larsen JT, Smith NK, Cacioppo JT (1998) Negative information weighs more heavily on the brain: the negativity bias in evaluative categorizations. J Pers Soc Psychol, 75:887–900.
  • Kahneman D, Tversky A (1979) Prospect theory: An analysis of decision under risk. Econometrica, 47:263.
  • Kartini K, Nahda K (2021) Behavioral biases on investment decision: A case study in Indonesia. The Journal of Asian Finance, Economics and Business, 8:1231-1240.
  • Kim HJ, Hong JS, Hwang HC, Kim SM, Han DH (2020) Comparison of psychological status and investment style between Bitcoin investors and share investors. Front Psychol, 11:502295.
  • Kinari Y (2016) Properties of expectation biases: Optimism and overconfidence. J Behav Exp Finance, 10:32–49.
  • Kumar A (2009) Who gambles in the stock market? J Finance, 64:1889–1933.
  • Kumar S, Goyal N (2015) Behavioural biases in investment decision making – a systematic literature review. Qual Res Fin Mark, 7:88–108.
  • Marks I (1990) Behavioural (non‐chemical) addictions. Br J Addict, 85:1389-1394.
  • McClure SM, Bickel WK (2014) A dual-systems perspective on addiction: Contributions from neuroimaging and cognitive training. Ann N Y Acad Sci, 13:62-78.
  • Meng J, Fu F (2020) Understanding gambling behaviour and risk attitudes using cryptocurrency-based casino blockchain data. R Soc Open Sci, 7:201446.
  • Mills DJ, Nower L (2019) Preliminary findings on cryptocurrency trading among regular gamblers: A new risk for problem gambling? Addict Behav, 92:136–140.
  • Mosenhauer M, Newall PWS, Walasek L (2021) The stock market as a casino: Associations between stock market trading frequency and problem gambling. J Behav Addict, 10:683–689.
  • Naim-Fell J, Zangen A (2013) Addiction. Handb Clin Neurol, 116:613-630.
  • Nestler EJ (2005) Is there a common molecular pathway for addiction?. Nat Neurosci, 8:1445-1449.
  • Othman AHA, Musa Alhabshi S, Kassim S, Abdullah A, Haron R (2020) The impact of monetary systems on income inequity and wealth distribution: A case study of cryptocurrencies, fiat money and gold standard. Int J Emerg Mark, 15:1161–1183.
  • Pezzani F (2018) Bitcoin: the bewildering illusion of easy wealth. Acad Sci J, 3:1109–1113.
  • Pfaffenberger B (2000) The rhetoric of dread: Fear, uncertainty, and doubt (FUD) in information technology marketing. Knowl Technol Policy, 13:78–92.
  • Piper ME (2015). Withdrawal: Expanding a key addiction construct. Nicotine Tob Res, 17:1405-1415.
  • Przybylski AK, Murayama K, DeHaan CR, Gladwell V (2013) Motivational, emotional, and behavioral correlates of fear of missing out. Comput Human Behav, 29:1841–1848.
  • Scholten OJ, Zendle D, Walker JA (2020) Inside the decentralised casino: A longitudinal study of actual cryptocurrency gambling transactions. PLoS One, 15:e0240693.
  • Senarathne CW (2021) Gambling behaviour in the cryptocurrency market. In: Research Anthology on Blockchain Technology in Business, Healthcare, Education, and Government:1536–1552, IGI Global.
  • Spyrou S (2013) Herding in financial markets: a review of the literature. Rev Behav Fin, 5:175–194.
  • Steinmetz F, von Meduna M, Ante L, Fiedler I (2021) Ownership, uses and perceptions of cryptocurrency: Results from a population survey. Technol Forecast Soc Change, 173:121073.
  • Sudzina F, Dobeš M, Pavlíček A (2021) Towards the psychological profile of cryptocurrency early adopters: Overconfidence and self-control as predictors of cryptocurrency use. Current Psychology, 1-5.
  • Tversky A, Kahneman D (1974) Judgment under uncertainty: Heuristics and biases: Biases in judgments reveal some heuristics of thinking under uncertainty. Science, 185:1124–1131.
  • Vidal-Tomás D, Ibáñez AM, Farinós JE (2019) Herding in the cryptocurrency market: CSSD and CSAD approaches. Fin Res Lett, 30:181–186.
  • Youn H, Choi J-S, Kim D-J, Choi S-W (2016) Development and validation of a stock addiction inventory (SAI). Ann Gen Psychiatry, 15:1-7.

Details

Primary Language Turkish
Subjects Psychiatry, Behavioral Sciences
Journal Section Review
Authors

Erman ŞENTÜRK> (Primary Author)
ÜSKÜDAR ÜNİVERSİTESİ NP FENERYOLU TIP MERKEZİ
0000-0001-9208-7905
Türkiye


Behçet COŞAR>
GAZİ ÜNİVERSİTESİ, TIP FAKÜLTESİ
0000-0002-6422-499X
Türkiye


Zehra ARIKAN>
LOKMAN HEKİM ÜNİVERSİTESİ, TIP FAKÜLTESİ
0000-0003-3138-2315
Türkiye

Early Pub Date June 30, 2023
Publication Date June 30, 2023
Acceptance Date October 12, 2022
Published in Issue Year 2023, Volume 15, Issue 2

Cite

AMA Şentürk E. , Coşar B. , Arıkan Z. Kripto Paraların Kumar ve Bağımlılık ile İlişkisi. Psikiyatride Güncel Yaklaşımlar - Current Approaches in Psychiatry. 2023; 15(2): 1-1.

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Psikiyatride Güncel Yaklaşımlar - Current Approaches in Psychiatry is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.