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Abstract

Background and aims Crypto-currency trading is a rapidly growing form of behaviour characterised by investing in highly volatile digital assets based largely on blockchain technology. In this paper, we review the particular structural characteristics of this activity and its potential to give rise to excessive or harmful behaviour including over-spending and compulsive checking. We note that there are some similarities between online sports betting and day trading, but also several important differences. These include the continuous 24-hour availability of trading, the global nature of the market, and the strong role of social media, social influence and non-balance sheet related events as determinants of price movements. Methods We review the specific psychological mechanisms that we propose to be particular risk factors for excessive crypto trading, including: over-estimations of the role of knowledge or skill, the fear of missing out (FOMO), preoccupation, and anticipated regret. The paper examines potential protective and educational strategies that might be used to prevent harm to inexperienced investors when this new activity expands to attract a greater percentage of retail or community investors. Discussion and conclusions The paper suggests the need for more specific research into the psychological effects of regular trading, individual differences and the nature of decision-making that protects people from harm, while allowing them to benefit from developments in blockchain technology and crypto-currency.
The psychology of cryptocurrency trading: Risk
and protective factors
PAUL DELFABBRO
1
p, DANIEL L. KING
2
and
JENNIFER WILLIAMS
3
1
School of Psychology, University of Adelaide, South Australia, Australia
2
College of Education, Psychology and Social Work, Flinders University, South Australia, Australia
3
Department of Psychology, University of Lethbridge, Alberta, Canada
Received: March 15, 2021 Revised manuscript received: May 17, 2021 Accepted: May 22, 2021
ABSTRACT
Background and aims: Crypto-currency trading is a rapidly growing form of behaviour characterised by
investing in highly volatile digital assets based largely on blockchain technology. In this paper, we review
the particular structural characteristics of this activity and its potential to give rise to excessive or
harmful behaviour including over-spending and compulsive checking. We note that there are some
similarities between online sports betting and day trading, but also several important differences. These
include the continuous 24-hour availability of trading, the global nature of the market, and the strong
role of social media, social influence and non-balance sheet related events as determinants of price
movements. Methods: We review the specific psychological mechanisms that we propose to be particular
risk factors for excessive crypto trading, including: over-estimations of the role of knowledge or skill, the
fear of missing out (FOMO), preoccupation, and anticipated regret. The paper examines potential
protective and educational strategies that might be used to prevent harm to inexperienced investors when
this new activity expands to attract a greater percentage of retail or community investors. Discussion and
conclusions: The paper suggests the need for more specific research into the psychological effects of
regular trading, individual differences and the nature of decision-making that protects people from harm,
while allowing them to benefit from developments in blockchain technology and crypto-currency.
KEYWORDS
crypto-currency, trading, harm, risk factors, protective factors
INTRODUCTION: THE NATURE OF CRYPTOCURRENCY
Cryptocurrency trading appear to be one of the fastest growing markets in the world. Surveys
conducted by major exchanges (e.g., Crypto.com, 2021;Independent Reserve, 2020) suggest
that hundreds of thousands of people are signing up to exchange platforms each month. The
current global population of crypto-currency (crypto) buyers and sellers is now estimated to
be over 106 million (Crypto.com, 2021). So rapidly is this growth occurring that gures re-
ported as recently as three months ago are already signicant under-estimates. Growth in
retail investors (from the general population) is paralleled by growth in the cryptocurrency
market itself. Total market capitalisation (total coins x market price) has now reached 1.75
trillion $US in February 2021 after having been $550 billion in December 2020 and $275b in
June 2020. The price of Bitcoin (BTC), the leading currency, has increased in price from $9500
(June 2020) to a peak of $58,000 in February 2021, with similar exponential growth observed
in Ethereum (ETH) and numerous other altcoins(coins other than Bitcoin). This growth in
cryptocurrency value, increasing investor interest and media attention has raised some media
commentary about whether the general community might be fully aware of the risks or harms
that might be associated with this activity. This is particularly when media activity may focus
primarily on a small minority of early investors who have achieved nancial gains, largely due
Journal of Behavioral
Addictions
DOI:
10.1556/2006.2021.00037
© 2021 The Author(s)
REVIEW ARTICLE
pCorresponding author.
E-mail: paul.delfabbro@adelaide.edu.
au
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to historical factors (e.g., buying Bitcoin in 2013) or holding
coins well before the onset of periodic bull cycles.
The term cryptocurrency refers to digital coinsor assets
that are based on block-chain technology. Blockchains are
distributed ledger systems where each node of the system is
linked together in a peer-to-peer network. All transactions are
systematically validated by each component of the network.
Blocks, which form the basis for the coins, are created through
an initial coin release (or ICO), can be earned through activ-
ities (e.g., in gaming, transaction activity), or mined. Mining
usually occurs through proof-of-worksystems, whereby
cryptographic algorithms generate complex random numbers
of hashes which must be solved using the application of
computer power. The different parties that contribute to this
work (or mine the blocks) receive a fraction of the block (e.g.,
part of a Bitcoin). Such systems also use proofofstake
1
methods based on value-added contributions to the generation
of the coins. Coins are traded on exchanges, stored privately in
wallets using keysor identiers.
2
Increasingly, they can be
used in tokenised economies to pay for games, to gamble, to
pay for commodities, for producing work (e.g., Anytask and
Electroneum) or secure contracts (smart contracts, Chainlink)
and to coordinate supply chains (e.g., VeChain) or as currency
(Reserve Rights or BTC) (Gainsbury & Blaszczynki, 2017;
Scholten, Zendle, & Walker, 2020).
Cryptocurrency trading has much in common with
modern trading on the share-market (Granero et al., 2012;
Kim, Hong, Hwang, Kim, & Han, 2020). It attracts both
experienced and less experienced investors; both large
institutional investors as well as small retail investors; is
subject to market uctuations; and, trading is heavily auto-
mated, with buy and sell orders set by digital trading sys-
tems. However, there a number of clear differences. First,
trading can occur 24 hours of the day and every day of the
week. Second, crypto coins are harder to value. In contrast to
mining companies that can state potential earnings (e.g.,
based on gold deposits or barrels of oil), this more difcult
with cryptocurrencies which share many similarities with
stocks traded on venture exchanges. With such stocks, there
are often only ideas for projects and few tangible assets and
realisation of the business models. Crypto projects also often
lack statements of prot margins that might be used to es-
timate future dividend returns.
3
Instead, future value can
only be based on whether investors believe that the coin will
attract attention based on whether it has a good reputation
and prole,
4
or whether it has a genuine use case(i.e.,
utility beyond trading). Investors can only look at simple
ratios such as the maximum number of coins available vs
current supply or the current total market capitalisation as
the basis for hypothetical growth.
5
This is based on the
knowledge that some coins have a limited maximum and
greater likelihood of price growth, whereas others with an
innite supply (e.g., DOGE coin) are inationary and lose
value as more coins are produced. Like speculative stocks,
prices can shift rapidly overnight due to sentiment changes,
celebrity endorsements, or single comments and their
popularity on platforms such as Reddit. Although there is
evidence that price rises in crypto stocks correlate with
Twitter activity and have some predictability (see Kraaije-
veld & De Smedt, 2020), many of these other extraneous
factors are unpredictable and therefore (like an unexpected
run by a horse) has a strong element of randomness or
chance.
A third difference is that the crypto market is much more
volatile. Prices for single coins can increase over 100%
percent in a matter of hours and then drop back down again
soon after (Meng & Fu, 2020). Even Bitcoin, the dominant
coin, can vary substantially in price (e.g., in February 2021 it
lost 20% of its value in 2 days) (Dahham & Ibrahim, 2020).
Markets also move in rapid cycles of boom and bust that are
more severe than observed in the standard stock-market. For
example, even in well-documented bull-runs(e.g., in 2017),
the Bitcoin price suffered multiple corrections of between 30
and 40%. Meanwhile, altcoins often display even more
extreme price movements. This creates trading opportu-
nities, but also make them higher risk. In 2017, during the
so-called crypto-bubble, some well-documented coins
(e.g., the privacy coin Verge) rose over 100,000% such that
an investment of $US100 invested at the right time would
have become over $1m in under a year. The same coin,
along with many others, also fell over 80% in the bust cycle
in 20172018 such that many altcoin holders who failed to
sell at the peak lost much of their capital gains.
A fourth difference is that crypto trading has the po-
tential create some additional uncertainties that traditional
shares often do not create. Many thousands of coins have
been produced and many have been scams, whereby coin
values have been quickly pumped(i.e., articially inated
in value through means of spreading misinformation) only
for the founders to leave the market (Kamps & Kleinberg,
2018). Crypto can also be used in criminal activities; be the
basis of operations with spurious business propositions; and
often be subject to inconsistent or knee-jerkregulations
(e.g., countries might decide to delist certain coins or ban
crypto completely such as currently been suggested in India
and Nigeria). Crypto owners can also lose their assets (the
keys to their coins) through loss of hard wallets, hard-drives,
1
The term proof of stake is similar to the concept of money on the tablein
business, whereby parties to a transaction demonstrate commitment and
trust by staking something of value to the business proposition.
2
Coins can be stored on exchanges (soft wallet) or on special USB-style
external hard drives (hard wallets).
3
Some crypto projects do offer what are called air-dropswhich are rewards
for holding tokens or for activity on the host platform (e.g., gambling or
playing games on certain platform that use a particular token as a cur-
rency).
4
The number of Google searches and Twitter search hits for a coin has been
found to correlate with future price behaviour.
5
If the current supply of coins is very much below the total possible supply
which can be mined or produced, then this means that the coin value will
decrease. Low market cap values are also favoured because it gives a real-
istic sense of growth. For example, a top 10 market cap will be in the order
of $1020b, so that a current market cap of $100m has a more realistic
growth potential.
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hacks launched on exchanges, or incorrect use of the tech-
nology.
A final characteristic of crypto trading which makes it
risky is that it is very difficult to engage in portfolio
balancing to protect against risk on the downside. In con-
ventional share trading, investors in speculative or high risk
or speculative stocks can also purchase more stable blue
chipshares which tend to hold their value over a longer
period. By contrast, the value of altcoins is pegged to Bitcoin
such that they usually only go up or down when BTC
changes in price (Balakrishnan, 2020). In effect, this makes
them operate more like derivatives
6
of BTC than indepen-
dent stocks.
7
As a result, if BTC suffers a major correction,
altcoin value loss will usually be even greater, so that coin
holders will have little means of creating a a balanced
portfoliowhereby there may be some hope that some coin
move against the overall market trajectory.
Crypto-trading: a form of gambling?
These many characteristics of crypto trading has led some
commentators to suggest that this new activity shares much
in common with online gambling (Gainsbury & Blaszczyn-
ski, 2017;Millar, 2018;Mills & Nower, 2019). Indeed,
similar arguments have been raised in relation to the day-
trading of shares, which appears to entail a signicant
element of luck or chance, inconsistent returns, and a like-
lihood of poor returns for most investors (e.g., Arthur &
Delfabbro, 2016;Arthur, Delfabbro, & Williams, 2015;
Arthur, Williams, & Delfabbro, 2016;Barber, Lee, Liu, &
Odean, 2009;Dorn, Dorn, & Sengmueller, 2014;Gao & Lin,
2015;Jordan & Diltz, 2003). As Arthur et al. (2015) point
out, day-trading differs from conventional long-term share
investing in that the event frequency (time between purchase
and sale) is often short. Purchases and sales may also be
more based on technical analysisthan appreciation of the
intrinsic or long-term value of the stock. Rather like race and
sports bettors studying form guides or sporting statistics, day
traders study candles, patterns, or ratios and support
levels. While these indicators can often be useful guides to
price movements, they often involve ad hoc judgments (the
price has already moved up or down) and they are not
capable of anticipating sudden market changes. As a result,
it is estimated that the majority of coin and day traders do
not make returns higher than the market and many lose
money (Melker, 2019). Few day-traders of shares last for
very long in the market, with only 7% estimated to last ve
years in the business.
Research by Arthur and Delfabbro (2016) showed that
people who gamble are signicantly more likely to engage in
day-trading. Similar ndings have emerged in relation to
crypto trading, with Mills and Nower (2019) observing, using
a sample of gamblers, that those who engaged in sports
betting and high-risk stock trading were more likely to report
crypto-trading. All of these activities were associated with a
higher risk of problem gambling, with problem gambling
found to be an independent predictor of crypto-trading after
controlling for other associated variables. The authors argued
that crypto-trading may be appealing to people who enjoy
gambling and may attract similar demographic groups or
(often younger males with higher levels of income and ed-
ucation) and people with similar personality or tempera-
ments (Conlin et al., 2015;Dixon, Giroux, Jacques, &
Gregoire, 2018;Kim et al., 2020;Kumar, 2009). These include
greater impulsivity and novelty seeking.
These emerging findings and the structural characteris-
tics described above therefore raise important questions
about the potential risks inherent in crypto-trading.
Accordingly, in this paper we examine how some of the
specific structural characteristics of this new activity might
assist in understanding how the topic might need to be
approached in psychological research. In particular, we
examine the ways in which existing insights into online
sports betting and day trading can be applied to crypto
trading. A particular focus is on whether this activity could
potentially lead to excessive behaviour and harm in some
individuals, and what specific structural characteristics are
likely to be involved. Here we outline some of the most
important psychological principles that we believe to be
central to understanding the potentially addictive elements
of this new behaviour. We then conclude the paper with
discussion of some potential protective factors that could
mitigate against the primary risk factors.
Risk factors in crypto currency trading
The illusion of control. Crypto trading, as with day trading
and sports betting, is not entirely based on chance. Skill and
strategy can make a difference to outcomes. For example,
betting on Sheffield United to win the 202122 English
Premier League or buying a cheap altcoin after a þ30% daily
surge in price during a at period of the crypto market are
both likely to be ill-advised decisions. By contrast, betting on
Manchester City and buying altcoins when the price has
recently dropped appear to be better decisions. However, all
of these activities offer many opportunities for people to
over-estimate the role that applying specic types of
knowledge or skill might play in outcomes and, conversely,
the signicant role that luck and chance are likely to play.
The illusion of control, dened as a subjective over-esti-
mation of the objective ability to exert control (Langer,
1975) is known to be a common feature of gambling (Wohl
& Enzle, 2002;Wood & Clapham, 2005). People believe that
strategies, skills, or certain rituals can increase the proba-
bility of winning. Such beliefs are known to be present in
both chance and more skilled games and appear to be
stronger in people experiencing gambling problems (Jeffer-
son & Nicki, 2003;Joukhador & Blaszczynski, 2004;Lambos
& Delfabbro, 2007).
6
By this, we do not imply that altcoins are derivatives in the traditional
sense; only that upward and downward movement are strongly correlated
with Bitcoin.
7
Altcoins move in the direction of BTC, but the rate of change can often be
much higher (e.g., 10x or 100x value during a time when BTC might
change by 4x).
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The illusion of control is likely to be a strong feature of
crypto trading and this feature is also likely to be common to
sports betting and day trading. The effect is likely to be
bolstered by other heuristics and biases, including: biased or
self-serving attributions (outcomes due to personal action
rather than external factors); hindsight bias (the outcome is
seen as being hypothesised all along); and, the hot-hand
fallacy (perceptions of predictable momentum shifts or
winning periods (Lambos & Delfabbro, 2007;Toneatto &
Ladouceur, 2003). Many of these effects are likely to be
strong during favourable market conditions. If BTC is
trending upwards, then nearly all coins will experience
growth over time. As a result, traders will rarely be wrong in
their choices and most decisions will be positively rein-
forced. Traders will therefore, often falsely, infer continency
between their actions and positive outcomes, an effect which
is known to be stronger when the probability of reinforce-
ment is high (Blanco, Matute, & Vadillo, 2011;Matute,
1996). As a result, traders may gain a sense of invincibility or
perception that they cannot lose and this may contribute to
greater risk taking, for example: speculation of large
amounts in just one speculative coin; not planning for
strategies to exit the market at the right time; or, moving
money from a more balanced portfolio towards purchasing
riskier altcoins.
Social learning and reinforcement. Crypto trading has also
emerged during the era of social media. This has led to the
emergence of a strong social media culture of crypto advi-
sors, spruikers/influencers and more experienced advisors
on platforms such as Youtube. Searching online quickly
shows that it is possible to nd at least one positive
endorsement of at least one major coin. Some of these arise
from what appear to be more experienced and well-
informed sources (e.g., the Coin Bureau, Michael van der
Poppe), but there are many others that are entirely specu-
lative, ill-informed, and potentially misleading because they
leave out key information (a coin might have a low market
cap which suggests growth potential, but only 10% of the
total supply of coins has been produced). Although similar
promotional information has historically been available
concerning conventional shares, the volume of material, the
interactivity and supercial condentiality of the informa-
tion (i.e., the sense that one is in the know rst, or is getting
some special insights) is much stronger. Promoters of
particular coins can show evidence of how much money
they have already earned from buying in very low, and they
can use graphics with great effect to show the anticipated
growth. This can serve to create a sense of urgency and a
need for immediate action. It also encourages a culture of
mutual social reinforcement in which followers of channels
seek to promote their successes, while also reading about the
gains scored by others.
Preoccupation. Preoccupation or salience is a recognised
feature of most major conceptual models of addiction (e.g.,
Browne & Rockloff, 2019;Grifths, 2005). Those who
engage excessively in a particular activity often nd it
difcult to disengage from the activity. They may continu-
ously think about the activity (preoccupation) and prioritize
the activity ahead of other important responsibilities. Crypto
trading would appear to be an activity that has the potential
to be highly absorbing. Like day-trading, it involves regular
scrutiny of price movements, news and other online media
about coin-related developments (e.g., coin burns), the
need to make regular buy and sell decisions and research
into the different coins (their potential value, market cap,
number and reputation) (Dixon et al., 2018). However,
because crypto markets operate continuously, it is possible
for people to be engaged with the activity at any hour of the
day. By contrast, sports bettors (unless they bet on many
different activities) often have to wait for matches to occur.
Day-traders can only be actively engaged with the activity in
the sense of buying and selling during daylight hours. This
creates the potential for crypto trading to absorb a consid-
erable amount of time and potentially with greater risk of
disruptions to sleep and other daily commitments.
Fear of Missing Out (FOMO)
One of the strongest psychological factors that appears to
influence crypto-trading is the fear of missing out (FOMO).
This term is often used by some experienced traders and a
style of thinking to avoid (Przybylski, Murayama, DeHaan,
& Gladwell, 2013). Although FOMO is likely to be a feature
of online sports betting (e.g., the belief that one could be
missing a good bet), the opportunities for FOMO seem
particularly intensied in crypto-trading. Traders are con-
fronted with displays of hundreds of coins. Some of them,
they already own; others they do not. If one which they have
purchased is going up rapidly, they may regret having not
made a larger investment. If another unpurchased coin is
going up which they had previously considered, they feel
annoyed for having missed out on the opportunity. Perhaps
most problematically of all is the situation, when they
observe a green screen of numbers. The market is going up
and they feel compelled to be part of the action. They
purchase a coin when it has reached a short-term peak, only
to watch the price fall soon afterwards. FOMO also applies
to sell decisions. When altcoins, in particular, have rapidly
increased in price (e.g., 10X), there is always the prospect
that the rise might continue. Instead of taking the prot, the
person starts to dream of what they might purchase if the
price increases 40X or 50X, but is then unprepared when the
price falls 3040% in single day when the bull-run ends.
FOMO is a construct that largely arose from social media
research and this is reflected in its associated measure
(Przybylski et al., 2013). In this sense, it is entirely appro-
priate to apply to crypto-trading given its strong presence in
online social networks. Not only do individual traders or
investors experience a FOMO in relation to their own ac-
tions, they are also exposed to testimonials from other
traders on social media sites that may then encourage them
to buy certain coins or to hang on to receive even larger
gains. In the notorious 100,000X ascent of Verge coin in the
201718 bull-run, many traders were discouraged from
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selling because of discussion of even greater potential prots
on social media communities. Even when the coin was
falling in value, some almost felt obliged to keep the faith
and not sell out, even though this would have been in their
individual best interest to take even a 50% or 30% prot
when the coin's value fell rapidly.
Anticipated regret
Cognitive psychology has recognised for some time that
many decisions are based on the desire to minimise antici-
pated regret (Miller & Taylor, 1995;Schwartz et al., 2002).
One of the central ndings in this area is that acts of com-
mission (doing something) usually led to stronger feelings of
regret than acts of omission (not doing something). This
asymmetry has been used to explain why people are reluc-
tant to sell shares which they have held for some time, why
they avoid hitting on 16 in blackjack (Miller & Taylor, 1995),
and why people will value lottery tickets held for a long time
as being more valuable than those held for a shorter period
(Bar-Hillel & Neter, 1995;van den Ven & Zeelenberg, 2011).
Acts of commission involving regret in trading would
include decisions where a stock or coin holding is sold, only
for it to rapidly appreciate in value. Acts of omission involve
situations where ultimately successful stocks or coins were
forgone (not purchased) for other investment decisions.
It is clear that both acts are likely to cause significant
regret in trading and that this may potentially be a risk
factor that is more strongly observed in this activity than in
most forms of gambling, with the exception of wagering. In
the gambling context, perhaps the most regretful event that
might be imagined would be a failure to buy (or to lose) a
lottery ticket in a particular week when the winning
numbers came up. Most other gaming activities, including
the higher risk ones (e.g., gaming machines, card games) are
less likely to involve situations where a person might
consider themselves to blame for missing out on a win. A
reason for this is that the games are usually of a short
duration, and decisions made in one game have no bearing
on outcomes of future games. By contrast, crypto trading
allows traders to observe the folly of their decisions over a
long period of time: what they missed out on (a coin that has
100x in value in 6 months), and what coins they sold too
early. For this reason, the act of commission and omission
effects are both likely to be very strong. However, impor-
tantly, given the very strong FOMO effects often described
as being the downfall of less experienced investors (who buy
into upwards trends), a question arises as to whether the
asymmetry between commission vs. omission based regret
observed in other contexts is as strongly observed in crypto
trading.
Protective factors and strategies
As the popularity of crypto trading rapidly increases over the
next 12 months, it is important to identify what psycho-
logical and other strategies might be used to mitigate against
the risks inherent in this new activity. How can it be kept
enjoyable, potentially productive without reducing a
person's quality of life? General strategies for avoiding harm
associated with excessive trading share some similarities
with gambling: sticking to a budget; not spending more than
can be afforded; and not chasing losses (losses are, in fact,
usually a useful tax offset; e.g., see cryptocurrency as an
investment;www.ato.gov.au). Similarly, it is possible to
dispel some of the erroneous beliefs associated with the
activity, including the degree to which outcomes can be
predicted or controlled. Specically, to temper over-esti-
mated perceptions of control, new investors need to be
aware that crypto value is highly correlated with BTC, so
that it is unlikely that altcoins will rise unless BTC is rising
as well. In effect, even coins based on high quality projects
with good fundamental use cases may not rise unless BTC is
stable and investors are condent about the overall health of
the market. This means that protection against downside
risk is almost more challenging than for conventional share
trading. The best a person can do is to take prots at
appropriate times, maintain some liquidity (e.g., convert
currencies into USD stable coins) and focus on investments
in projects that are likely to have greatest longevity.
Protection against social influences is also important.
Many YouTube channels and social media opinion (e.g., on
Reddit) often involves preaching to a converted audience.
Evidence is posted in support of certain coin purchases, but
often without any fundamental analysis, critical evaluation
of downsides, or consideration of opportunity cost (are there
better purchases that might be made). Such information may
be circulated rapidly and may even be exploited by bad
actors using bots or other means to amplify certain messages
to encourage buying coins to manipulate the market.
Community education around the need to seek out repu-
table and multiple information sources, including the
appropriate magnitude of investment, may therefore be
important in the near future. Inexperienced investors may
also need to be taught about the history or longer-time
horizons for this market. Many panicked in response to
negative news (e.g., the May 2021 Tweets from Tesla CEO,
Elon Musk about divesting from Bitcoin payments) even
though this would have had negligible impact on the market.
Preoccupation or salience is a difficult issue to address if
a person is a professional trader and needs to study price
movements throughout the day. However, for community or
general retail investors, it is important to recognise that
continual monitoring can be an easy habit to develop even
among casual investors. This may begin as a temptation to
check that then becomes an unconscious or automatic ten-
dency to study price movements during work, during social
activities, education, and even during the night. This activity
can disrupt sleep, productivity and be an ongoing distrac-
tion. In this way, crypto trading has the potential to combine
the financially speculative elements of gambling with social
media (e.g., Facebook update checking). Strategies for
dealing with this temptation might involve setting limits or
rules on when, or how often, the prices are checked. Other
activities might be scheduled ahead of price monitoring, so
that checking prices only occurs as a type of reward for
completing other work.
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The principal harm associated with FOMO and regret is
that people may impulsively place more money than they
can afford on risky coins that have already undertaken rapid
growth. As a result, they face a greater risk of buying into the
market when it is due for a major correction (historically
this occurs when the BTC dominance or % of total market
cap is lower). Important advice that can reduce this effect is
to encourage satisficing (Schwartz et al., 2002) in which
people are discouraged from expecting optimal or perfect
decision-making. Even experienced traders will not always
buy at the lowest price or sell at the highest price. Nor will
they pick up every coin that displays very high growth.
Instead, the aim is to encourage protective strategies: buy
before things are too high; buy the dips or corrections to
minimise downside risk; and, stay focused on the positive
outcomes rather than the outcomes that were missed.
Achievement of at least some very good outcomes in a rising
market is likely to be increased if the portfolio is spread over
a wider range of coins, but, as mentioned, cannot protect
against sudden downturns in the BTC price.
CONCLUSIONS
Crypto trading is a rapidly growing activity that is likely to
receive increasing mainstream acceptance over the next few
years. We believe that the topic is important in behavioral
addiction research for two reasons. The first is because it
brings together elements of risk inherent in gambling, but
also in excessive social media use. Particular features that
make this form of speculation unique include its 24-hour
availability, long-form nature, the extreme volatility of out-
comes, and the strong influence of sentiment and social in-
fluence. In this sense, it has the potential to be riskier for
inexperienced traders whose engagement in the market has
been strongly influenced by media attention or FOMO sen-
timents. A second issue is that crypto trading provides many
opportunities to examine the operation of many established
principles of social and cognitive psychology. Opportunities
exist to profile the distinct risk factors that differentiate
crypto trading from other similar activities (day trading and
online sports wagering), but also to identify protective factors
that can avoid the development of the various harms that
might arise when large numbers of inexperienced investors
enter the market. Research programs examining these factors
are likely to be influential to discussions of consumer pro-
tections and inform potential steps for regulation of trading
platforms and other activities that involve cryptocurrencies.
Funding sources: This paper was funded independently with
no support from government, industry or party external to
the University.
Authors' contribution: Initial drafting of paper (PD); Re-
visions and editing (DK, JW)
Conflict of interest: None to declare
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Article
The purpose of the present study was to investigate whether or not there is an association between engaging in traditional forms of gambling and engaging in high-risk stock trading and, if so, to examine game play patterns of high-risk stock traders, as well as identify any socio-demographic similarities or differences between the two groups. Logistic regressions on data from two large Canadian data sets were undertaken to examine which variables best differentiate traditional gamblers from high-risk stock traders. The results indicate that high-risk stock traders have a higher frequency of gambling, engage in a larger range of gambling activities, and are more likely to be problem gamblers. Additionally, the type of gambling activities that high-risk stock traders participate in suggests that they are a sub-group of skill-based gamblers who also prefer gambling on casino table games, sports betting, dog and horse race betting, and games of skill for money over chance based games such as electronic gaming machines, bingo, and instant win tickets. High-risk stock traders, compared to traditional gamblers were more likely to be male, have a higher income, be better educated, and to be of Asian or “other” descent, not be divorced, widowed or separated, and be self-employed or employed full-time. However, unlike other skill-based gamblers, high-risk stock traders tended to be older rather than younger, and had a high income rather than a low income.
Cryptocurrencies have become a very popular topic recently, primarily due to their disruptive potential and reports of unprecedented returns. In addition, academics increasingly acknowledge the predictive power of Twitter for a wide variety of events and more specifically for financial markets. This paper studies to what extent public Twitter sentiment can be used to predict price returns for the nine largest cryptocurrencies: Bitcoin, Ethereum, XRP, Bitcoin Cash, EOS, Litecoin, Cardano, Stellar and TRON. By using a cryptocurrency-specific lexicon-based sentiment analysis approach, financial data and bilateral Granger-causality testing, it was found that Twitter sentiment has predictive power for the returns of Bitcoin, Bitcoin Cash and Litecoin. Using a bullishness ratio, predictive power is found for EOS and TRON. Finally, a heuristic approach is developed to discover that at least 1-14% of the obtained Tweets were posted by Twitter “bot” accounts. This paper is the first to cover the predictive power of Twitter sentiment in the setting of multiple cryptocurrencies and to explore the presence of cryptocurrency-related Twitter bots.