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Disposition effect and herding behavior in the cryptocurrency market
Abstract
This paper investigates two behavioral biases—the disposition effect and herding—using the Mt. Gox data between 2011–2013 in the bitcoin cryptocurrency market. Using trade round-trip and survival analysis, it shows the market exhibits a reverse disposition effect in bullish periods and the usual positive disposition effect in bearish periods. It finds evidence of herding in bearish as well as bullish periods using a return dispersion model. Additionally, it shows that herding moves along the market trend. Herding increases in both bullish and bearish periods when the bitcoin price increases and decreases, respectively.
... However, cryptocurrency is a more volatile investment vehicle (Sun et al. 2021) compared to conventional asset classes of the stock market like commodities, stocks, and bonds (Subramaniam and Chakraborty 2020), and it is not backed by any government or commodity (Sood and Singh 2022). Corollary, the fundamental analysis of cryptocurrency investments for return predictability fails (Rubbaniy et al. 2022), whilst non-fundamental approaches such as herding (Gurdgiev and Corbet 2018;Bouri et al. 2019;Kaiser and Stöckl 2020;Vidal-Tomás et al. 2019;Yarovaya et al. 2021), loss aversion (Popova 2019;Haryanto et al. 2020), and overconfidence (Sudzina et al. 2021;Kim and Hanna 2021;Jalal and Leonelli 2021;Nurbarani and Soepriyanto 2022) emerged as the most prevalent drivers in the cryptocurrency market, which makes it more challenging to go through tough periods of downturns and dips. Despite this, the cryptocurrency market is seeing positive momentum day by day. ...
... The term "herding" was originally studied in zoology and, subsequently, psychology (Haryanto et al. 2020). Herding is a process in which one economic agent imitates the decisions of others instead of acting independently (Baddeley 2010), which results in the synchronization of price co-movements of related financial assets (Caferra 2020). ...
... In contrast, da Gama et al. (2019) found that when the market is bearish, there is a herding effect. However, Haryanto et al. (2020) observed that herding follows the market trend. When the bitcoin price rises, herding becomes more prevalent in both bullish and bearish periods. ...
The study's purpose is to examine the effect of herding, loss aversion, overconfidence, and fear of missing out (FOMO) biases on crypto investors’ investment decisions. The study also looks at how FOMO plays a mediating role between herding, loss aversion, overconfidence, and crypto investment decisions. To acquire data from crypto retail investors, the study used a questionnaire survey. A total of 473 responses were gathered and analyzed with SmartPLS. To achieve the study's aims, factor analysis and partial least square structural equation modelling were used. The study's findings found that FOMO, herding, loss aversion, and overconfidence biases have a substantial effect on the investment decisions of crypto investors, in respective order. In addition, FOMO bias establishes a complementary partial mediation on the relationship between herding, loss aversion, and crypto investors’ decision-making behavior. Ergo, the present study assisted individual and institutional cryptocurrency investors, crypto portfolio managers, policymakers, researchers, and market regulators in broadening their knowledge base about cryptocurrency and forecasting investors' behavior. Hence, this study contributes to the field of behavioral finance.
... Furthermore, with their analysis they introduce a new paradigm for analysing behavioural drivers of the cryptocurrency assets based on the use of natural language AI to extract better quality data on investor sentiment. On a similar aspect of the literature on herding Haryanto et al. (2020) using trade round-trip and survival analysis, show that the cryptocurrency market exhibits a reverse disposition effect in bullish periods and the usual positive disposition effect in bearish periods. King and Koutmos (2021) examines the extent to which herding, and feedback trading behaviours drive price dynamics across nine major cryptocurrencies, documenting heterogeneity in the types of feedback trading strategies investors utilise across markets. ...
... Indeed, the research further shows that an increase in news positivity is related with reduced returns dispersion, demonstrating investor convergence. The study of Hidajat (2019) tried to fill the research gap on cryptocurrencies Main findings Al-Mansour (2020) The findings of the study demonstrate that herding theory, prospect theory and heuristic theory have a substantial impact on investors' Bitcoin investing decisions Aloosh and Ouzan (2020) The study shows that the cryptocurrency market has a significant small price bias, which supports the idea that investors respond to news differently depending on the price level Caferra (2020) The results showcase that the peaks and falls of optimism determine returns variability using both cross-sectional standard and absolute deviation Cao and Rhue (2019) They find that positive sentiment contributes significantly negatively to Bitcoin return on the same day (negative sentiment day contributes positively, although not significantly), extending the understanding of disposition effect Grobys and Junttila (2021) The results suggest that parallel to stock markets, similar behavioural mechanisms of underlying investor behaviour are present also in new virtual currency markets Haryanto et al. (2020) The analysis reveals that the cryptocurrency market exhibits a reverse disposition effect in bullish periods and the usual positive disposition effect in bearish periods Hidajat (2019) The analysis implies that prices and Bitcoin transactions are more determined by psychological factors Li et al. (2020) This research finds that cryptocurrencies with small market value tend to perform better in the future Li et al. (2021a, b, c) The results demonstrate that cryptocurrencies with higher maximum daily returns tend to achieve higher returns in the future and call this the "MAX momentum" effect Lin et al. (2021) The results showcase a lottery-like momentum, meaning that a higher maximum return leads to a higher future return amongst 64 cryptocurrencies Luo et al. (2021) Results show that Bitcoin investors exhibit, on average, an increasing aversion to ambiguity. Furthermore, investors are found to earn abnormal returns only when ambiguity is low Ozdamar et al. (2021) The analysis provides evidence for a positive and statistically significant relationship between the maximum daily return within the previous month (MAX) and the expected returns on cryptocurrencies Schatzmann and Haslhofer (2020) The analysis shows that investors are indeed subject to the disposition effect, tending to sell their winning positions too soon and holding on to their losing position for too long Zhang et al. (2019) The study finds that investors' response to authority-related news is negative and statistically significant (2020) use behavioural economics to examine the dynamics of Bitcoin pricing. ...
... Authors state that these findings extend the understanding of disposition effect to the cryptocurrency market. Haryanto et al. (2020) investigate the disposition effect using the Mt. Gox data between 2011 and 2013. ...
Purpose
The present study sets out to examine the empirical literature on the behavioural aspects of cryptocurrencies, showing the findings of related studies and discussing the various results. A systematic literature review of cryptocurrencies in behavioural finance seems to be timely and particularly important in terms of providing a guide for future research. Key topics include an extent review on the issue of herding behaviour amongst cryptocurrencies, momentum effects and overreaction, contagion effect, sentiment and uncertainty, along with studies related to investment decision-making, optimism bias, disposition, lottery and size effects.
Design/methodology/approach
Systematic literature review.
Findings
A systematic literature review of cryptocurrencies in behavioural finance seems to be timely and particularly important in terms of providing a guide for future research. Key topics include an extent review on the issue of herding behaviour amongst cryptocurrencies, momentum effects and overreaction, contagion effect, sentiment (investor's, market's) and uncertainty, along with studies related to investment decision-making, optimism bias, disposition, lottery and size effect.
Originality/value
The authors' survey paper complements recent papers in the area by offering a systematic account on the influence of behavioural factors on cryptocurrencies. Further, this study's purpose is not just to index the relevant literature, but rather to showcase and pinpoint several research areas that have emerged in the field of behavioural cryptocurrency research. For all these reasons, a systematic literature review of cryptocurrencies in behavioural finance seems to be timely and particularly important.
... The disposition effect adversely affects an investor's rational decision-making. Sharma and Firoz (2022) revealed that the disposition effect has a strong influence on investor rationality and affects their investment decisions, which is consistent with other studies (Andreu et al., 2020;Haryanto et al., 2020;Prosad et al., 2017). However, some studies argue that the magnitude of the disposition effect varies across countries due to cultural differences (Breitmayer et al., 2019), social interactions (Heimer, 2016), and different market conditions . ...
... This is because they ignore information that does not match their initial assessment, and therefore continue to hold on to their losing stocks. The results of the study are consistent with previous studies that this bias exists among investors when making investment decisions in financial markets, and that it strongly affects their rationality (Andreu et al., 2020;Haryanto et al., 2020;Prosad et al., 2017;Sharma & Firoz, 2022).However, these findings do not confirm those of Lin (2011), who finds that this relationship is not significant in the Taiwanese market. They also contradict those of Sharma and Firoz (2022), who find no statistically significant relationship between these variables in the Indian equity market. ...
The paper proposes a behavioral model of investment decisions under the Adaptive Market Hypothesis (AMH) in the Moroccan financial market. This model examines the existence of rationality alongside irrational behavioral biases that might affect investors, as well as investors' tendency to adapt to market conditions. The paper uses Partial Least Squares Structural Equation Modeling (PLS-SEM) to test the proposed hypothetical model based on primary data collected from individual and institutional investors active in the Moroccan financial market. The results of the study show that, although investors tend to follow the rational decision-making process, some irrational biases might arise during this process. Specifically, the empirical evidence reveals that during the 'searching information" stage, investors are subjected to the disposition effect. Then, the losses accumulated because of the disposition bias attenuate the overconfidence bias, and prompt investors to correct their perception of risk rationally. Therefore, the findings are consistent with the adaptive investor behavior implied by the AMH theory. Regarding investor type, the study shows that individual and institutional investors are likely to be affected by behavioural biases alike. This study is the first to use a different approach, to empirically test the AMH, based on heterogeneous and adaptive investor behavior using primary data. This approach can provide a more accurate measure of investor behavior dynamics. The study is also the first to use the PLS approach to investigate adaptive investor behavior, both at the level of individual and institutional investors, in the Moroccan context. This study has implications for trading strategies and regulatory policies. Insights from the research make investors aware of their biases, which could help them try to de-bias themselves by complying with certain rational rules. In addition, the study findings suggest that investors can exploit arbitrage opportunities resulting from irrational behavior. Moreover, the results of the study enable policymakers to understand the real behavior of investors and take appropriate regulatory measures to prevent the market from being inefficient and unstable.
... Prior studies (e.g. Haryanto et al., 2020;Popova, 2019) have demonstrated that individual investors' investment decisions in the crypto market are influenced by loss aversion, which can manifest itself during the blow-off phase when investors who have lost money due to price drops continue to hold Bitcoin because they will suffer greatly if they have to sell it at a loss (Hidajat, 2019). ...
... This finding is consistent with previous research studies (e.g. Nurbarani and Soepriyanto, 2022;Rubbaniy et al., 2022;Ballis and Drakos, 2020;Gurdgiev and O'Loughlin, 2020;Gama et al., 2019;Bouri et al., 2019;Poyser, 2018;Vidal-Tom as and Ibañez, 2018;Haryanto et al., 2020). In this regard, the study outcome has stated that herding is rapidly growing in the cryptocurrency market as a result of market stress, significant price volatility, a lack of quality information, and cryptocurrency investors' expectations of unprecedented positive returns. ...
Purpose
Research in the domain of behavioral finance has proven that investors demonstrate irrational behavior while making investment decisions. In a similar domain, the primary objective of this research is to prioritize the behavioral biases that influence cryptocurrency investors' investment decisions in the Indian context.
Design/methodology/approach
A fuzzy analytic hierarchy process (F-AHP) was used to prioritize the behavioral factors impacting cryptocurrency investors' investment decisions. Overconfidence and optimism, anchoring, representativeness, information availability, herding, regret aversion, and loss aversion are among the primary biases evaluated in the present study.
Findings
The findings suggested that the two most important influential criteria were herding and regret aversion, with loss aversion and information availability being the least influential criteria. Opinions of family, friends, and colleagues about investment in cryptocurrency, the sale of cryptocurrencies that have increased in value, the avoidance of selling currencies that have decreased in value, the agony of holding losing cryptocurrencies for too long rather than selling winning cryptocurrencies too soon, and the purchase of cryptocurrencies that have fallen significantly from their all-time high are the most important sub-criteria.
Research limitations/implications
This survey only covered active cryptocurrency participants. Additionally, the study was limited to individual crypto investors in one country, India, with a sample size of 467 participants. Although the sample size is appropriate, a larger sample size might reflect the more realistic scenario of the Indian crypto market.
Practical implications
The study is relevant to individual and institutional cryptocurrency investors, crypto portfolio managers, policymakers, researchers, market regulators, and society at large.
Originality/value
To the best of the authors' knowledge, no prior research has attempted to explain how the overall importance of various criteria and sub-criteria related to behavioral factors that influence the decision-making process of crypto retail investors can be assessed and how the priority of focus can be established, particularly in the Indian context.
... The market tends to believe in the role of big players and makes a few investors make investment decisions without being based on sufficient literacy regarding the decisions that have been made, thus triggering the emergence of herding behavior [22]. The significance of the influence of herding behavior in the cryptocurrency market on investors' investment decisions is also evidenced by [6] [7] and [23]. ...
... This result is in line with [7] [10] [23] where the herding factor has a significant and positive influence on investment decisions. This is understandable considering that cryptocurrency investors are young investors who do not have complete knowledge and information. ...
... All studies documented that majority of investor's exhibit disposition effect while making investment in the stock market. Some studies in the literature also identified that disposition effect leads to risk and irrational behaviour (Dhar and Zhu, 2006;Prosad et al., 2017;Haryanto et al., 2020). Researchers have observed the presence of disposition bias in both institutional as well as individual investors (Cheng and Lin, 2012;Van Dooren and Galema, 2018;Andrikogiannopoulou and Papakonstantinou, 2020). ...
... Van Dooren and Galema (2018) argued that investors investing in socially responsible stocks show a greater disposition effect as compared to the traditional investors. This effect is also a behavioural anomaly which affects the rational process of decision making (Andreu et al., 2020;Haryanto et al., 2020) and thereby affecting the investors' rationality. Therefore, authors hypothesise that the disposition effect will show a positive influence on investors' rationality (i.e., identification of demand, searching relevant information and evaluating alternatives). ...
The present research is conducted to determine the relationship between behavioural biases and investors' rationality in the Indian equity market. The study has followed the Mintzberg et al. (1976) decision-making model for measuring investors' rationality. Data has been collected from 400 individual investors of National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) by using a structured questionnaire. An advanced approach of structural equation modelling (SEM) has been used to determine the relationship between behavioural biases and investors' rationality. The findings of the study indicate that behavioural biases are significantly related to the investor's rationality. Whereby, herding, optimism and disposition effect bias show a strong influence on the investor's rationality and affect their investment decisions. The outcomes of the present study also offer meaningful insights to the investment professionals, investors, fund administrators, regulators, and policymakers, as they will be able to develop a unique and bias-free portfolio which will reduce or eliminate the effect of behavioural biases on investor decisions. The results of this study also generate a strong need to update the existing norms and regulations related to investment in Indian stock market.
... Many studies have already found that cryptocurrencies markets are inefficient (see Urquhart, 2016;Al-Yahyaee et al. 2018;Ahmed et al. 2020). These markets exhibit positive disposition effects in bearish conditions and negative disposition effects during bullish times (Haryanto et al. 2020). The asymmetric herding behaviour also suggests the evidence of market inefficiencies in cryptocoin pricing. ...
... Hence, virtually no fundamentals are available to judge the real value of a cryptocoin. Crypto markets exhibit reverse disposition effects during bullish times and positive disposition effects in bearish conditions (Haryanto et al. 2020). Such asymmetric herding behaviour suggests the evidence of price reversions and market inefficiency. ...
Purpose
Research on price extremes and overreactions as potential violations of market efficiency has a long tradition in investment literature. Arguably, very few studies to date have addressed this issue in cryptocurrencies trading. The purpose of this paper is to consider the extreme value modelling for forecasting COVID-19 effects on cryptocoin markets. Additionally, this paper examines the importance of technical trading indicators in predicting the extreme price behaviour of cryptocurrencies.
Design/methodology/approach
This paper decomposes the daily-time series returns of four cryptocurrency returns into potential maximum gains (PMGs) and potential maximum losses (PMLs) at first and then tests their lead–lag relations under an econometric framework. This paper also investigates the non-random properties of cryptocoins by computing the incremental explanatory power of PML–PMG modelling with technical trading indicators controlled. Besides, this paper executes an event study to identify significant changes caused by COVID-19-related events, which is capable of analysing the cryptocoin market overreactions.
Findings
The findings of this paper produce the evidence of both market overreactions and trend persistence in the potential gains and losses from coins trading. Extreme price behaviour explains volatility and price trends in crypto markets before and after the outbreak of a pandemic that substantiate the non-random walk behaviour of crypto returns. The presence of technical trading indicators as control variables in the extreme value regressions significantly improves the predictive power of models. COVID-19 crisis affects the market efficiency of cryptocurrencies that improves the usefulness of extreme value predictions with technical analysis.
Research limitations/implications
This paper strongly supports for the robustness of technical trading strategies in cryptocurrency markets. However, the “beast is moving quick” and uncertainty as to the new normalcy about the post-COVID-19 world puts constraint on making best predictions.
Practical implications
The paper contributes substantially to our understanding of the pricing efficiency of cryptocurrency markets after the COVID-19 outbreak. The findings of continuing return predictability and price volatility during COVID-19 show that profitable investment opportunities for cryptocoin traders are prevailing in pandemic times.
Originality/value
The paper is unique to understand extreme return reversals behaviour of cryptocurrency markets regarding events related to COVID-19 breakout.
... Gox Bitcoin exchange was examined from April 2011 to November 2013, focusing on the disposition effect and herding behavior. The study analyzes how these behaviors manifest during bullish and bearish market conditions, as well as how trading frequency, market trends, and data granularity influence them (Haryanto et al., 2019). ...
This study seeks to investigate and synthesize existing literature on the cryptocurrency. The researcher adopted for NVIVO 14 software to perform a bibliometric analysis and elaborate a systematic literature review on cryptocurrency with a sample of 52 papers published in reputed journals, considering the different field of knowledge. The researcher explored a growing body of literature on factors affecting the investment behavior in cryptocurrency, which are Age, Gender, Behavioral Intention, Heuristic Factors, Prior Experience, Prospect, Governance, and the Cryptocurrency bubble. The secondary line of variables adopted from the analysis include price, financial literacy, the disposition effect, and investor sentiment, role of Blockchain technology, risks, herding behavior, and uncertainties related to cryptocurrency. Additionally, a dearth of literature has been observed on challenges faced by cryptocurrency and its investors, regulatory framework of cryptocurrency, factors which are motivating the cryptocurrency investors, impact of social media, and how technical knowledge can influence behavioral intention of investors in Indian context. This study helps the researchers and academics, by providing the research gaps on which further researches can take place in the field of cryptocurrency.
... Herding behavior in the context of cryptocurrency investment refers to the tendency of investors to follow the actions of the majority or crowd without conducting independent analysis [38]. We compiled herding behavior variable from the previous studies in the studies of Sood et al. [48], and Haryanto et al. [49]. This phenomenon often occurs in the cryptocurrency market which is highly influenced by sentiment and media hype. ...
... In addition to over confidence, disposition effects also influence the investment decisions of investors (Grinblatt et al., 2012;Rau, 2015). Some previous studies show how disposition effects influence investment decisions (Guenther and Lordan, 2023;Haryanto et al., 2020). Other studies also investigated the contribution of overconfidence to disposition effects and its influence on investment decisions (Abideen et al., 2023;Trejos et al., 2019). ...
Purpose
The purpose of this study is to investigate the impact of behavioral biases on investment decisions through a serial mediation of overconfidence and disposition effects.
Design/methodology/approach
The authors assess the behavioral biases affecting the investment decisions of life insurance policyholders through the serial mediation of overconfidence and disposition effects using a structured questionnaire. The study included 501 life insurance policyholders who were selected using a snowball sampling technique.
Findings
The results of this study revealed that behavioral biases influence the investment decisions of life insurance policyholders. The results also support the serial mediation model, where behavioral biases influence the investment decisions of life insurance policyholders via overconfidence and disposition effects.
Research limitations/implications
This study makes a theoretical contribution to the field of behavioral finance by exploring the influences of behavioral biases on investment decisions. It also introduces overconfidence and disposition effects as serial mediators between behavioral biases and investment decisions. The study will be helpful for researchers, academicians and policymakers in the development of a more comprehensive model in the area of behavioral finance and in raising awareness regarding those biases among policyholders in order to improve their investment strategy.
Originality/value
This study has extended the ongoing simple mediation model by integrating overconfidence and disposition effects in a serial mediation model between behavioral biases and investment decisions. The study will contribute to the area of behavioral finance, as it is the first time this particular study has been conducted according to the authors’ knowledge.
... Автордың шектеулі біліміне сүйене отырып, инвесторларға криптовалюта нарығында инвестициялық шешім қабылдауға көмектесетін мінез-құлық факторларының әсерін зерттейтін зерттеулердің жетіспеушілігі бар. Сонымен қатар, бірнеше зерттеулер табындық факторлар, криптовалюта нарығының құбылмалылығы және криптовалюта нарығындағы нарықтық көңіл-күй сияқты айнымалыларды зерттеуге бағытталған (Haryanto, 2020) [5]. Дегенмен, бұл зерттеу табындық факторлар, эвристика және перспективалар сияқты мінез-құлық қаржысының әртүрлі негізгі аспектілері мен факторларын қарастыру арқылы криптовалюта нарығына қатысты әдебиеттерді алға жылжытуға бағытталған. ...
The relevance of the research topic is due to the fact that many crypto investors are attracted by the high liquidity of cryptocurrencies, low transaction costs and ease of transactions via the Internet. In contrast from Fiat currencies, corporate stocks, and bonds, cryptocurrencies do not have an underlying value. demand therefore market cost to a greater extent depends on how wellknown and popular this cryptocurrency is. Also, the price of cryptocurrencies is influenced by market sentiment, namely the thoughts, feelings and emotions of investors regarding the asset. With the help of traditional asset valuation models, it is impossible to qualitatively explain the latest changes in the price of cryptocurrencies. However, some financial models point to that cryptocurrency is currently overvalued. Apparently, the hypothesis of financial instability is better than any of the verified economic theories suitable to explain recent changesin prices of cryptoassets. The theory suggests that because the cryptocurrency market is moving against the macroeconomic fundamentals of the economy, emotions are a major factor. determining demand on a given market. In this article, the authors examined the influence of behavioral financial factors on investment decisions in the cryptocurrency market. Multiple regression analysis was used to examine this effect. The purpose of the article is to study the development of cryptocurrency in Kazakhstan and assess the impact of events on the value of cryptocurrency. Based on this goal, the authors put forward the following tasks: to analyze and evaluate the use of cryptocurrencies in the modern economy; explore the features of cryptocurrency pricing.
... answers these questions by challenging such existence of "rational investment decisions" and emphases on the behaviour aspects of financial decision-making done by investors (Semenov, 2009). The fundamental assumption of traditional theory is that investors are rational and constantly try towards benefitting themselves by improving overall wealth (Haryanto et. al., 2020), whereas, the truth is investors make investment related decisions based on their personal experiences apart from applying the knowledge and skills of financial markets possessed by them (Akhtar et. al., 2019). Behavioral finance is a discipline of financial study which describes the irrationality of investors and related biases that ar ...
The current research focuses on the effect of emotional biases on the investment decision-making process among individual investors of India. This article is steered by conducting a survey on 631 individual investors of India participating in Indian stock market. Through a structured questionnaire as a research instrument, the study gauges behavioural biases of individual investors. An exploratory study by nature, the analysis of the study supports evidence establishing the adverse nature of behavioral biases affecting investment analysis and further their decision-making. The research implies a statistically significant association among behavioural biases and investment related decisions. The findings are significant for all the stakeholders of Indian stock markets, be it investors, financial advisors, industry experts and others indulged in the process of asset management or portfolio construction. This study can act as an aid towards informed investment decisions by analysing the vulnerability of investors associated with emotional biases.
... 2.2.4 Herding effect (HRE). HRE was initially studied in zoology and, subsequently, psychology (Haryanto et al., 2020). It is a psychological phenomenon where people choose to follow and imitate the crowd instead of acting independently (Baddeley, 2010) since they think the majority decision is always right (Bakar et al., 2016). ...
Purpose
Investment decisions hold immense significance for investors and eventually affect their portfolio performance. Investors are advised to weigh the costs and benefits associated with every decision in order to make rational investment decisions. However, behavioral finance research reveals that investors' choices often stem from a blend of economic, psychological and sociological factors, leading to irrationality. Moreover, environmental, social and corporate governance (ESG) factors, aligned with behavioral finance hypotheses, also sway opinions and stock prices. Hence, this study aims to identify how individual equity investors prioritize key determinants of investment decisions in the Indian stock market.
Design/methodology/approach
The current research gathered data from 391 individual equity investors through a structured questionnaire. Thereafter, a fuzzy analytic hierarchy process (F-AHP) was used to meet the purpose of the research.
Findings
Information availability, representative heuristics belonging to psychological factors and macroeconomic indicators falling under economic factors were discovered to be the three most prioritized criteria, whereas environmental issues within the realm of ESG factors, recommendations of brokers or investment consultants of sociological factors, and social issues belonging to ESG factors were found to be the least prioritized criteria, respectively.
Research limitations/implications
Only active and experienced individual equity investors were surveyed in this study. Furthermore, with a sample size of 391 participants, the study was confined to individual equity investors in one nation, India.
Practical implications
This research has implications for individual investors, institutional investors, market regulators, corporations, financial advisors, portfolio managers, policymakers and society as a whole.
Originality/value
To the best of the authors' knowledge, no real attempt has been made to comprehend how active and experienced individual investors prioritize critical determinants of investment decisions by taking economic, psychological, sociological and ESG factors collectively under consideration.
... Poyser (2018) found that herding behavior is present in positive market returns when examining asymmetric herding for 100 cryptocurrencies. Haryanto, Subroto, and Ulpah (2020) detected herding behavior in up and down markets to distinguish between positive and negative market returns and suggested that herding behavior follows market trends. Vidal-Tomás (2021) observed swarm behavior only in down markets when analyzing asymmetric swarming for 65 cryptocurrencies. ...
Herding behavior is expected to intensify with increasing uncertainty infinancial markets, especially after jarring structural changes such as thepandemic. For this reason, in this study we examined herding behavior inthe cryptocurrency market amid market crashes. Using daily cryptocurrencyprice data in 02.01.2018 - 22.03.2023 of the 9 most traded cryptocurrencies,the presence of herding behavior was investigated using the cross-sectionalabsolute deviation (CSAD) method. The dynamics of herding behaviorwas explored in 3 sub-periods: the Pre-Covid Period, the Covid-19 Periodand the Post Market Crash Period after Tesla’s Announcement. We alsotested if the largest cryptocurrencies were driving small cryptocurrenciesin the 3 sub-periods as well as the whole period. The findings of thestudy reveal that there is no herding in the market in significant marketfluctuations. Moreover, there seems to be no asymmetric herding behavioras we distinguish between up and down markets. Hence, our findings implyrational investment decision-making. Yet, the results indicate that the largestcryptocurrencies are wielding a substantial influence over the rest of themarket across the overall period and in the Post Covid Period (Period 2)in both up and down markets. However, in Period 1 and Period 3, theherding of small cryptocurrencies varies depending on whether the marketreturns are positive or negative. Our findings imply that the dynamics of theherding behavior between large and small cryptocurrencies has shifted withsignificant market crashes (outbreak of Covid-19, Tesla’s announcement).
... Behavioural finance answers these questions by challenging such existence of "rational investment decisions" and emphasizing the behavioural aspects of financial decision-making done by investors (Semenov, 2009). The fundamental assumption of the traditional theory is that investors are rational and constantly try to benefit themselves by improving overall wealth (Haryanto et al., 2020), whereas, the truth is investors make investmentrelated decisions based on their personal experiences apart from applying the knowledge and skills of financial markets possessed by them (Akhtar et. al., 2019). ...
The stock market is a crucial aspect of India's financial market and the world's economy, which results in massive investment performances. In the fast-moving financial scenario, traditional finance is incapable of explaining the irrationality of an investor. The investors are irrational and are influenced by irregularities in the financial market. The current research focuses on the effect of behavioural biases on the investment decision-making process among individual investors in India. This article is driven by conducting a survey on 540 individual investors of India who participate in one or the other form in the Indian stock market. An empirical study by nature, the analysis of the study supports evidence establishing the adverse nature of behavioural biases affecting investment analysis and further their decision-making. The research implies a statistically significant association between behavioural biases and investment-related decisions. The results revealed a substantial impact of the behavioural biases affecting the investment decisions of the individual investors, namely, Loss aversion bias, Status quo bias, and Optimism bias. The results also exhibited that Loss Aversion bias had the maximum impact on the investment decision-making of an Indian individual investor. Key-takeaways: 1. Emergence of behavioural finance. 2. Existence of behavioural biases among individual investors. 3. Effect of behavioural biases in investment decision-making.
... Blockchain technology and cryptocurrencies which perform independently of the conventional banking system might represent a real risk to commercial banks' processes and a potential threat to the existence of the banking system in the years ahead, where the cryptocurrency competes with the same targets as the banking system to execute the payments for goods and services or transfer assets, without the need for a third party or intermediary (Giudici et al., 2019). Furthermore, the cryptocurrencies industry prompts customers to transfer their bank deposits into cryptocurrencies to obtain the benefits of cryptocurrencies in transactions, as well as capital gains (Haryanto et al., 2020), in addition, the cryptocurrency system has an electronic wallet for each customer, which is more secure and easy to access compared to the banking system transactions (Marella et al., 2020). Therefore, the competition with the cryptocurrency system may lead to substantial losses for financial intermediary institutions, such as banks, which traditionally facilitate transactions and provide savings for investment. ...
Purpose
This study aims to analyze the effect of cryptocurrency capitalization market development on bank deposits variability in the United Arab Emirates (UAE) spanning the period 2005M1–2020M4 using the novel nonlinear autoregressive distributive lag (NARDL).
Design/methodology/approach
The study employs the NARDL recently developed by Shin et al . (2014) to estimate the long and short-run relationships between the variables rather than the widely known ARDL (Pesaran et al., 2001), which suffers from a complex structure in the estimation equation that usually includes lags and differences in both short and long terms. The implementation of NARDL required several proceedings after plotting the descriptive data, commencing with unit root tests, selection of lag length, estimating the long-and-short variables coefficients, heteroscedasticity test and Wald test for symmetries.
Findings
The long-run estimations of the positive and negative asymmetric coefficients indicate that cryptocurrencies capitalization has a negative impact on bank deposits in the UAE. Further, the short-run estimations coefficients exhibit that both significant positive and negative partial sum squares of cryptocurrencies decrease bank deposits.
Research limitations/implications
The study has applied to the UAE spanning the period 2005M1–2020M4 using the NARDL.
Practical implications
The short-run estimations coefficients exhibit that both significant positive and negative partial sum squares of cryptocurrencies decreases bank deposits, which means that the increase in the magnitude of cryptocurrencies capitalization stimulates depositors and speculators to adjust their portfolios towards contracting their deposits in banks to invest partially in cryptocurrencies, on the other hand, the decline in cryptocurrencies capitalization process spur depositors and speculators to reduce their deposits for purchasing cryptocurrencies at lower prices.
Social implications
The study infers that individuals and businesses are cautious when investing in cryptocurrencies, and they need more certainty and trust to include these types of assets in their portfolios. The fluctuation in cryptocurrencies capitalization prompts speculators to change their deposits according to the cryptocurrencies' prices.
Originality/value
This study explores the short-and long-run asymmetric impacts of cryptocurrencies capitalization development on bank deposits volatility in the UAE, based on a NARDL, for providing a manifest depiction of whether the cryptocurrencies industry might be a threat to conventional banking system performance in the potential future.
... Due to investor overexcitement, which results in high-volume trading, herding is confirmed in cryptocurrencies in the upper quantiles during bullish and high volatility moments. Their research, however, finds little proof of an impact on the stock market's intra-dependence on cryptocurrencies.In line with the literature on herding,Haryanto et al. (2020) demonstrate that the cryptocurrency market exhibits a reverse disposition effect in bullish periods and the typical positive disposition effect in bearish periods by employing trade round-trip and survival analysis. While according toGurdgiev and O'Loughlin (2020), the interaction between the psychological elements that impact investor choices and data flows that are available to the general public affect cryptocurrency price trends. ...
This article aims to investigate the presence of herding behavior in artificial intelligence (AI)–themed cryptocurrencies following the launch of ChatGPT. The authors analyze daily data from major AI-themed cryptocurrencies between November 2022 and February 2023. This study finds evidence of irrationality among investors in this market segment who tend to imitate others’ decisions regardless of their own beliefs during down events. The authors connect this finding to the herding theory in financial economics and highlight the implications for investors and policymakers. This article contributes to the literature on the impact of AI on financial markets and suggests the need for further research in this area. Finally, this study provides important policy implications, as it could help investors better understand the risks associated with this emerging asset class.
... The leaked dataset has been widely analyzed already by a number of prior works but in relation to research topics distinct from arbitrage, e.g., the presence of metaorder executions (Donier and Bonart, 2015), unusual price jumps in the BTC/USD exchange rate (Scaillet et al., 2020), the effects of distributed denial-of-service (DDoS) attacks on trading activity (Feder et al., 2018), the impact of suspicious activity in the Mt. Gox exchange that likely engaged price manipulation (Gandal et al., 2018, andChen et al., 2019, the latter trying to answer the same question through the lenses of network science), herding behavior (Haryanto et al., 2019), and wash trading (Aloosh and Li, 2019)). ...
... Our findings contribute to the existing literature by demonstrating that the disposition effect is not uniform and can vary depending on market conditions (Cheng et al. 2013;Bernard et al. 2021). Furthermore, our research contributes to the emerging literature on the disposition effect in volatile markets, particularly the cryptocurrency market (Haryanto et al. 2020;Schatzmann and Haslhofer 2020). ...
This study investigates the anchoring bias and disposition effect in investor trading decisions under different market volatility conditions (stable and volatile markets) and examines their impact on portfolio performance. Employing a quasi-experimental design, participants engage in interactive trading with four securities—two with potential negative returns and two with positive returns—within a simulated asset market. The findings reveal the presence of both the disposition effect and the anchoring bias among individual investors in India. Notably, market volatility influences these behavioral biases, with the disposition effect more pronounced in volatile markets, while the anchoring bias is significant in stable markets. Furthermore, investors exhibiting the disposition effect tend to have lower portfolio performance, while those influenced by the anchoring bias achieve relatively better results. These insights can aid individual investors in recognizing their behavioral biases and making informed trading decisions to enhance portfolio performance. Additionally, this study presents valuable suggestions to financial institutions and regulatory government agencies engaged in similar experiments, with the goal of improving financial decision-making and investment behavior.
... Our findings contribute to the existing literature by demonstrating that the disposition effect is not uniform and can vary depending on market conditions (Cheng et al., 2013;Bernard et al., 2021). Furthermore, our research contributes to the emerging literature on disposition effect in volatile markets, particularly the cryptocurrency market (Haryanto et al., 2020;Schatzmann & Haslhofer, 2020) The presence of anchoring bias is notably significant in stable and total markets, as demonstrated in Table 4. The results indicate that investors are more influenced by the previous lowest price of losing securities rather than the previous highest price of winning securities. ...
We present evidence of the anchoring bias and disposition effect (DE) in investor trading decisions across different asset markets (stable and volatile assets) and market scenarios (stable and volatile markets), as well as how these biases affect investors' portfolio performance. The study employs a quasi-experimental design, allowing subjects to engage in interactive trading with four securities, two with potential negative returns and two with potential positive returns, within a simulated asset market. Our findings reveal the presence of the disposition effect and anchoring bias among individual investors in India. Second, market scenarios or volatility can influence the investors’ behavioral biases. The disposition effect was more prominent in volatile markets and the total market, while the anchoring bias was significant in stable and total markets. Additionally, investors exhibiting the disposition effect exhibit lower portfolio performance, while those demonstrating anchoring bias perform relatively better. The study's findings can help individual investors understand their behavioral biases, avoid them in future trading decisions, and improve portfolio performance. Financial institutions and regulatory agencies could identify investment products and supportive investor interactions towards better market trade decisions.
... Facing an impending collapse, they panic and sell their holdings. Haryanto et al. (2020) in their study tested the herd behavior and disposition effect in the bitcoin prices using data from Gox covering the period 2011-2013. In the research, 21.2 million transaction data belonging to 127 thousand different traders were used. ...
Bitcoin first emerged as a peer-to-peer payment system without using any financial institution. Later, thousands of cryptocurrencies emerged and cryptocurrencies reached a market value of hundreds of billions of dollars. Bitcoin was launched in 2009 and its use as a cash payment system is quite limited even though years have passed. Today, cryptocurrencies similar to bitcoin are used mostly for speculative purposes. On the other hand, in today's conditions, users of cryptocurrencies trade on certain exchanges and often cannot effectively ensure the security of their accounts. In addition, some cryptocurrencies have problems such as slowness, security problems, and high energy costs. Despite all this, the popularity of cryptocurrencies among investors is increasing. In this book section, the factors that cause investment in cryptocurrencies to become widespread are examined based on the studies in the literature. For this purpose, studies examining the relationships between social media messages, financial literacy level, herd behavior, and cryptocurrency price movements are reviewed.
... With the help of a morphological box, various possible characteristics that an asset can have identified and assigned to these attributes. Haryanto, Subroto and Ulpah (2020), in their study, remarked on the disposition effect and the herding behaviour in the cryptocurrency realm by investigating the trading behaviour at a crypto exchange. Authors find a reverse disposition effect in bullish periods where the Bitcoin price increases while a positive disposition effect is observed in bearish periods. ...
The paper endeavour to explore the nexus between Bitcoin Rouble exchange rate and the Russian capital market using cointegration and vector error correction analysis taking the capital market indicators namely US Dollar Rouble exchange rate, MOEX index, RTX index, Moscow exchange trade turn over and RUONIA of Russia using daily data from 1/11/2021 to 18/4/2022 as a consequence of post pandemic recovery and sets back from war between Russia and Ukraine. The paper found that the trend line of Bitcoin Rouble rate is cyclical with four phases whose Wavelet threshold signal curve is explosive oscillatory. There are no short run causalities from the indicators of capital market to the Bitcoin Rouble price but there is insignificant and converging cointegrating long run causalities from those indicators where the relation between Bitcoin Rouble and US Dollar Rouble rate and MOEX index are significantly negative and the relation with RTX index is significantly positive. It was evident that there is little significant influence of Bitcoin Rouble pricing on the Russian capital market in the long run.
... All studies documented that most investors exhibit disposition effects while investing in the stock market. Some studies also identified that the disposition effect leads to risk and irrational behaviour (Dhar & Zhu, 2006;Prosad et al., 2017;Haryanto et al., 2020). Researchers have observed the presence of disposition bias in both institutional and individual investors (Cheng & Lin, 2012;van Dooren & Galema, 2018; Andrikogiannopoulou & Papakonstantinou, 2020). ...
Piyasa katılımcılarının, yatırım kararı verirken rasyonel davranamamalarına sebep olan sürü davranışı davranışsal finans kapsamında yer alan bir kavramdır. Bu çalışmada BRICS-T Ülkelerinde sürü davranışı varlığını araştırmak amacıyla Christie ve Huang (1995) ve Chang, Cheng ve Khorana (2000) modelleri kullanılmıştır. 2011-2021 yılları arasındaki günlük piyasa verileri kullanılarak analiz gerçekleştirilmiştir. Tüm, düşen ve yükselen ve piyasalar için regresyon analizi sonuçları ayrı ayrı incelenmiştir. CH (1995) modelinde Brezilya, Rusya, Hindistan, Güney Afrika ve Türkiye yükselen piyasa dönemlerinde sürü davranışı varlığı tespit edilirken Çin finansal piyasasında sürü davranışı etkisi görülmemiştir. CCK (2000) modelinde ise Hindistan yükselen piyasasında sürü davranışına dair kanıtlar elde edilirken diğer BRICS-T ülkelerinde bu modele göre herhangi bir sürü davranışı bulgusuna rastlanılmamıştır. Elde edilen analiz sonuçlarına göre volatilitenin sürü davranışı üzerinde asimetrik bir etkisi gözlemlenmemiştir.
In previous papers regarding market microstructure and price information in the stock market, the VAR model (vector auto regressions) has been frequently mentioned as a benchmark, and there are various discussions about the pros and cons of this model. Here, we would like to extend the usage of this model to the cryptocurrency market and see how VAR performs in a new setting. Our result shows that although VAR might yield some gaps in terms of price prediction, it still catches the trend with a fair amount of accuracy and could still serve as a potential benchmark model.
The influence that digital currency has had on the activities of platform companies are discussed in this article. Companies employ digital platforms to increase productivity, strengthen client relationships, and cut expenses. The study applied quantitative method by collected 116 questionnaires. Finally, the findings revealed that, demand side and the demand side the study focused on (Security, Usability, Irrevocability, Marketing and reputational effects) positively and significantly have influence on financial market. Moreover, it was found that the supply side had more influence than demand side on financial market.
Bu çalışma, kripto para yatırımcılarının sürü davranışı sergileyip sergilemediğini araştırarak literatüre katkıda bulunmayı amaçlamaktadır. Ayrıca, bu çalışma kripto para piyasasındaki sürü davranışını günlük frekanslar yerine yüksek frekanslı veriler kullanarak incelemektedir. Kripto para piyasasının küresel yapısı göz önüne alındığında, gün içi veriler daha hassas bir analizi kolaylaştırmaktadır. Bu bağlamda, değişen zaman aralıkları ile sürü davranışının değişme olasılığı araştırılmaktadır. Bu şekilde, yatırımcıların hangi zaman aralıklarında kendi bilgi ve kanıtlarını yeterince kullanmadan diğer yatırımcıların hareketlerini takip ettikleri tespit edilmeye çalışılmaktadır. Bu çalışma, hem Yatay Kesit Standart Sapma (CSSD) hem de Yatay Kesit Mutlak Sapma (CSAD) metodolojilerini kullanarak kripto para yatırımcılarının sürü davranışı sergileyip sergilemediğini araştırmaktadır. Sürü davranışının zaman boyutu da 15 dakika, 30 dakika, 1 saat, 2 saat, 3 saat, 6 saat, 12 saat ve günlük veri setleri olmak üzere farklı zaman aralıklarında sürü davranışı analizi yapılarak incelenmiştir. Analiz, 1 Ocak 2017’den 31 Aralık 2022’ye kadar olan dönemi kapsamaktadır ve toplam piyasa değerinin %70’sinden fazlasını temsil eden başlıca kripto para birimlerinden (BTC, ETH, LTC, XRP ve BCH) oluşmaktadır. Bu çalışmada, tüm dönem göz önünde bulundurulduğunda, yüksek frekanslı verilerde sürü davranışına dair herhangi bir kanıt bulunamamıştır. Aşırı fiyat hareketleri rasyonel varlık fiyatlandırma modelleri ile açıklanabilir. Başka bir deyişle, kripto para yatırımcılarının alım satım kararları diğer yatırımcıların davranışlarını taklit etmiyor ve yatırımcılar kendi bilgilerine dayanarak karar almaktadır. Dahası, kripto para yatırımcıları için negatif etkilerin pozitif etkilerden daha baskın olduğu söylenebilir. Sonuç olarak, kripto para yatırımcıları negatif bilgiye pozitif bilgiden daha duyarlıdır. Bu çalışmanın sonuçları kripto para piyasası için çeşitli çıkarımlara sahiptir. İlk olarak, sürü davranışının olmaması, kripto para yatırımcılarının kendi bilgilerine dayanarak rasyonel yatırım kararları alma olasılıklarının daha yüksek olduğunu göstermektedir. Bu, sürü davranışının sıklıkla gözlemlendiği geleneksel finans piyasalarının aksine bir durumdur. İkinci olarak, sonuçlar kripto para yatırımcılarının negatif bilgiye pozitif bilgiden daha duyarlı olduğunu göstermektedir. Bu durum, kripto para piyasasının hala nispeten yeni ve değişken bir piyasa olmasından kaynaklanıyor olabilir. Sonuç olarak, yatırımcıların olumsuz haberler karşısında pozisyonlarını satma olasılığı, olumlu haberler karşısında pozisyonlarını satın alma olasılığından daha yüksek olabilir. Son olarak, bu çalışmanın sonuçları özellikle bilgili yatırımcıların ve muhtemelen kurumsal yatırımcıların kripto para piyasasındaki hakimiyetini vurgulamaktadır. Bunun nedeni, bu yatırımcıların rasyonel yatırım kararları almalarını sağlayacak bilgi ve kaynaklara erişimlerinin daha yüksek olması olabilir. Buna ek olarak, önemli piyasa değerine sahip kripto para birimleri daha rasyonel yatırımcılar tarafından tutulduğu için sürü davranışını gözlemlemek mümkün olmamış olabilir. Yüksek frekanslı verilerde sürü davranışının görülmemesi, kripto para piyasasındaki yatırımcıların bilgiyi fiyatlara hızlı bir şekilde dahil ettiğini ve bunun da kısa zaman aralıklarında etkin bir piyasanın göstergesi olduğunu göstermektedir. Sonuçlarımız, yatırımcıların kısa zaman aralıklarında kitlesel davranışların neden olduğu ani ve irrasyonel piyasa hareketlerinden daha az endişe duyabileceğini göstermektedir. Dahası, bu durum yatırımcıların başkalarının eylemlerinden aşırı derecede veya hızlı piyasa hareketlerine yol açabilecek şekilde etkilenmediğini göstermektedir. Dolayısıyla çalışmamız, yüksek frekanslı kripto para verilerinde sürü davranışının olmamasının önemini vurgulamakta ve etkin piyasalar, yatırım stratejileri ve risk yönetimi uygulamaları için değerli bilgiler sağlamaktadır.
Purpose
This study probes the psychological interplay between investor sentiment and the returns of cryptocurrencies Bitcoin and Ethereum. Employing the Granger causality test, the authors aim to gauge how extensively the Fear and Greed Index (FGI) can predict cryptocurrency return movements, exploring the intricate bond between investor emotions and market behavior.
Design/methodology/approach
The authors used the Granger causality test to achieve research objectives. Going beyond conventional linear analysis, the authors applied Smooth Quantile Regression, scrutinizing weekly data from July 2022 to June 2023 for Bitcoin and Ethereum. The study focus was to determine if the FGI, an indicator of investor sentiment, predicts shifts in cryptocurrency returns.
Findings
The study findings underscore the profound psychological sway within cryptocurrency markets. The FGI notably predicts the returns of Bitcoin and Ethereum, underscoring the lasting connection between investor emotions and market behavior. An intriguing feedback loop between the FGI and cryptocurrency returns was identified, accentuating emotions' persistent role in shaping market dynamics. While associations between sentiment and returns were observed at specific lag periods, the nonlinear Granger causality test didn't statistically support nonlinear causality. This suggests linear interactions predominantly govern variable relationships. Cointegration tests highlighted a stable, enduring link between the returns of Bitcoin, Ethereum and the FGI over the long term.
Practical implications
Despite valuable insights, it's crucial to acknowledge our nonlinear analysis's sensitivity to methodological choices. Specifics of time series data and the chosen time frame may have influenced outcomes. Additionally, direct exploration of macroeconomic and geopolitical factors was absent, signaling opportunities for future research.
Originality/value
This study enriches theoretical understanding by illuminating causal dynamics between investor sentiment and cryptocurrency returns. Its significance lies in spotlighting the pivotal role of investor sentiment in shaping cryptocurrency market behavior. It emphasizes the importance of considering this factor when navigating investment decisions in a highly volatile, dynamic market environment.
This study comprehensively analyzes herding behavior in the cryptocurrency market. First, we conduct an in-depth investigation of herding behavior in the overall cryptocurrency market. Second, we form several groups of cryptocurrencies according to their characteristics and analyze whether each group behaves similarly in volatile market regimes. Third, we investigate whether herding existed in each cryptocurrency group before and during the COVID-19 pandemic. Using a sample of 227 cryptocurrencies constituting nearly 95% of market capitalization, we reveal that herding behavior was absent in the overall sample and sub-samples comprising cryptocurrency groups. Further, the anti-herding behavior implies a contrarian response to the crowd. This anti-herding can be explained from two views: rational behavior of taking profit from market irrationality and irrational behavior due to fear or recency bias.
This paper provides a review of the literature on digital finance, cryptocurrency, and financial dependence in relation to economic development and growth. We summarize the evidence of how cryptocurrencies and digital finance impact growth. We show further that financial dependence and credit ratings are also critical to growth, along with language and culture. We introduce the papers in this special issue and elaborate on future research opportunities for these topics.
In recent years cryptocurrency trading has been very active and received attention from worldwide investors. Given its short history and lack of effective regulatory frameworks, cryptocurrency trading is still like the wild west. This study selected the top 21 dominant cryptocurrencies to analyze the
trading behavior associated with them over the period from 2016 to May 2023. We adopted the cross-sectional absolute deviations (CSAD) model to investigate investors’ trading behavior. Two
calculation methods are used: the capitalization-weighted method and the equally weighted method. Our analysis results have indicated that no matter which calculation method is used, the
cryptocurrency marketplace has shown strong and significant herd behavior from 2016 to March 12, 2020. However, significant herd behavior couldn’t be detected after March 12, 2020. This is a very interesting and yet important finding from our study. The implication is that March 12, 2020 appeared to be a turning point where important market conditions might have changed, such as the dominant cryptocurrency trading force has transformed from individuals to institutional investors.
This study investigates how Indonesian Islamic Banks implement mudharabah contracts on financing product. This study uses descriptive research, namely research that defines facts, data, and information gathered from published studies such as books and journals to research findings relevant to the research topic. According to this study, the development of Islamic banks in Indonesia has seen positive growth. One of the products offered by Islamic banks is financing products. This financing is accomplished through the use of various contracts, one of which is the mudharabah contract, which employs a profit-sharing system. This profit-sharing system will be devoted to customers who apply for financing from Islamic Banks that are used to run businesses owned by customers. In the process, the bank will carry out several stages and procedures such as verification to determine the provision of such financing to customers. If it has been verified, the Bank will provide funds or capital to the client to be managed. The customer’s results or profits will be divided between both the customer and the bank under the terms of mudharabah contract. In the process of implementation, this mudharabah contract is based on Islamic law such as the Qur'an and al-Hadith as well as legislation such as MUI fatwas, PSAK as well as OJK, and Bank Indonesia policies.
There are various behavioral aspects that influence the financial decisions of individual investors, such as overconfidence, herding behavior, loss aversion, and regret aversion. Other psychological elements may play a substantial influence in deciding the success or failure of any financial action. The primary aims of the present research article are to examine the effects of overconfidence bias and herding behavior on individual financial decisions regarding crypto currency investment. The markets for crypto currencies are extremely sensitive to any minute or significant changes in the economy, as well as to any changes in the individual behaviors of investors. To achieve these aims, 650 questionnaires were distributed to individual investors employed by various financial institutions, multinational corporations, including oil and gas exploration and production companies, operating in Pakistan, individual investors dealing in stocks, and students regardless of investment size. Purposive sampling was used to choose 311 valid responses from a total of 593. Those investors that engage in crypto currency investments were deemed valid responses. Classifications of investments were outlined, and demographic information was requested from respondents. SPSS-based empirical analysis provided the basis for the conclusions. The primary findings indicate that both overconfidence bias and herding tendency have a favorable and statistically significant impact on investors' financial decisions when investing in cryptocurrencies. In this study's sample, however, the majority of investors were overconfident in their crypto currency investing decisions.
In recent years, the Indian Government has adopted potent measures to
expedite the transition from the cash-dependent to the cashless economy.
The introduction of ATMs enhanced the banking operations’ efficiency
and allowed the customers more convenient access to their money. Similarly,
funds transfer systems such as NEFT, RTGS and IMPS have enabled
more reliable and faster transfers. However, the next revolution has been
unleashed by applying transaction systems such as UPI (Unified Payment
Interface). India has been scaled by the 4G network, which has ensured
the availability of internet services in every part of the country. Hence
the UPI applications can be easily accessed and used by people. The
sudden announcement of demonetization has also provided an impetus to
adopting e-money as the mode of payment. The government has rightly
sensed this as an excellent opportunity to propagate Fintech tools among
the citizens to decrease the dependence on cash. This paper explores the
need for reducing the reliance on cash for the day-to-day transactions,
prospects and the challenges associated with initiatives adopted for India’s
drive in the direction of a Cashless economy
The aim of this paper is to investigate if herd behaviour is present in crypto assets at industry level. Using price information extracted from coinmarketcap.com between 29 April 2013 and 9 May 2022, we find evidence of herding and reverse herding in the crypto assets market. Concentrated periods of herding and reverse herding are particularly evident in the January 2020–April 2022 Covid period. At industry level, herding is more profound in large sectors with higher volatility. In smaller sectors where ventures are backed by ‘real assets’, very short periods of herding with marginal significance are detected. Reverse herding is present in all industries except Real Estate between June 2021 and May 2022, implying that strategies such as excessive ‘flight to quality’ or/and token picking are at play during the recent crypto crash. We also detect varying asymmetric herding at industry level. This paper further examines the factors that drive such industry herding and reverse herding in the crypto assets market, and our results show that industry concentration and investor sentiments contribute to the probability of herding/reverse herding. Our study provides further insights to the forces that drive the dispersion in crypto assets prices and contribute to the behavioural studies of the crypto market.
The disposition effect is the tendency of investors to sell winning stocks and hold losing stocks and the herding behavior is an investment behavior in a group of investors who trade in the same direction. Both are regarded as irrational investment behaviors. This research examines the herding behavior in the Stock Exchange of Thailand during the COVID-19 pandemic and the disposition effect situation. We used daily data from January 2011 to December 2020 of complete observed stocks in the Stock Exchange of Thailand (SET). We modified the average holding period following Atkins and Dyl (Journal of Finance 52(1):309–325, 1997 [5]) and adapted the method for investigating the disposition effect after Visaltanachoti et al. (Applied Financial Economics 17(15):1265–1274, 2007 [45]). Then we constructed the dummy variable to represent the month in which the disposition effect took place in the market. After that, we tested the existence of the herding behavior during the COVID-19 pandemic and when the disposition effect was occurring. The herding behavior was tested following Yao et al. (International Review of Economics & Finance 29:12–29, 2014 [48]) and Filip et al. (Procedia Economics and Finance 32:307–315, 2015 [19]) using the cross-sectional absolute deviation (CSAD). The results reveal the herding behavior to occur during the disposition effect situation but not during the COVID-19 pandemic.
This paper investigates the characteristics of labor demand for different levels of qualification in family-managed firms. As the majority of firms in Germany but also in other European countries is family-controlled, the outcome of this study is relevant on an international level. While most studies on employment in family firms have focused on the firms' total workforce, this study analyzes labor demand in family-managed firms on three different skill levels. Applying large panel data from German establishments and a fractional panel probit regression model, the outcomes show that there are some remarkable differences between family-and non-family-managed firms. On average, only medium-skilled workers experienced higher job stability in family-managed firms, whereas highly-and low-skilled workers do not. Highly skilled workers might have valid outside opportunities and probably do not seek higher job stability, while low-skilled probably do not profit from the firm owners' loyalty.
This paper examines the evidence of herding in the revolutionary cryptocurrency market for the period from January 2017 to December 2020. The study employs quantile regression technique for investigating herd behaviour during market asymmetries of rising and falling returns, extreme market returns, high volatility, and the exogenous event of the COVID-19 pandemic. The results provide evidence of pronounced herding during the bull phase, extreme down-markets, and high volatility. These results indicate that herd hunch is prevalent in the cryptocurrency market as investors exhibit imitation while ignoring their own knowledge and beliefs. Also, the phenomenon is more vividly observed during the panic period of COVID-19.
The present study sets out to examine the empirical literature on the behavioural aspects of cryptocurrencies, showing the findings of related studies and discussing the various results. A systematic literature review of cryptocurrencies in behavioural finance seems to be timely and particularly important in terms of providing a guide for future research. Key topics include an extent review on the issue of herding behaviour among cryptocurrencies, momentum effects and overreaction, contagion effect, sentiment and uncertainty, along with studies related to investment decision making, optimism bias, disposition, lottery and size effects.
Cryptocurrency, operated through blockchain technology, is a new
form of digital currency which is used as a medium of exchange. It is
used in many countries but Bangladesh Bank, the central bank of
Bangladesh, halts a ban on its use and/or trading considering its
negative aspects. So, the perception towards virtual currency in
Bangladesh remains under shadow. Hence, the study investigates the
perception of a total 155 persons (having sound knowledge in this
new technology e.g., central bankers, bankers and finance and
accounting graduates) behind the intended use of cryptocurrency using
structural equation modelling. The study has four observed variables
(perceived ease of use, perceived usefulness, trust and perceived risk)
and one latent variable (behavioral intention to use cryptocurrency).
Finally, the result demonstrates that perceived usefulness and trust
have a significant impact, but perceived ease of use and perceived
risk have no significant impact on the intention to use cryptocurrency.
The paper enlightens the unexplored perception of the people of
Bangladesh towards cryptocurrency. The findings recommend that the
Bangladesh Bank may reconsider its decision regarding fintech
innovation considering cryptocurrency’s positivity and minimize the
dilemma keeping the deleterious sides under strict monitoring.
Keywords: Bangladesh Bank, Block chain, Cryptocurrency, Perceived
Ease of Use, Perceived Usefulness
JEL Classification: C51, C59, D40, G12
Today, one of the most important reasons for the pervasiveness of digital currencies is the unique benefits it provides to users, which can be attributed to the speed and efficiency of payments, especially overseas payments. This study aimed to provide a multiple infrastructure model for bitcoin use. This research has been done qualitatively using interview tools. The survey community consists of academic experts including Profesor universitarios specializing
in the fields of digital currencies, e-commerce, international finance and finance, and empirical experts consisting of managers and experts of monetary
and financial organizations (banks, stock exchanges). The selection of samples is saturated and purposeful. Finally, 18 people were selected to answer
the interview questions. Data analysis was performed with the context theory (GT) approach. Based on the obtained results, 6 main networks, 14 main
components and 77 sub-components were obtained as multiple infrastructures for bitcoin use. The results also showed that economic and social infrastructure can affect the use of bitcoin. If there is funding to buy the necessary devices and welcome bitcoin in the community, bitcoin will be more usable as a digital and acceptable currency.
Purpose: Traditional Finance theories assume that the investor uses all available information and make rational decisions while investing, but the scenario is not the same. As the literature presents the increasing importance of behavioral Finance, the present study investigates the impact of different behavioral factors on the retail investors' investment decisions directly and through the mediation of investor's perceptions. Besides, insufficient knowledge exists regarding the behavior of retail investors during COVID-19. The current study addresses this gap and examines the impact of COVID-19 between the association of these behavioral factors disposition effect, herd behaviors, optimism, and overconfidence and retail investors' investment intentions. Design/Methodology/Approach: The current study collected data from retail investors and gathered 499 responses as a final sample size through convenience sampling technique. The current research employed structural equation modeling technique for the empirical findings. Findings: The results of current study show the positive and significant association between the Behavioral factors and retail investors' decision making while investment. The results further demonstrate that the retail investor's perception partially mediate the relationship that behavioral factors has with retail investors' decision making. In addition, the findings direct that the COVID-19 moderate the relationship and change the behaviors of Retail investors regarding the inventors' perception. Research Limitations: As far as the limitations are concern, firstly, the present research considers only a few behavioral factors that influence investment behaviors; other factors are not part of the current study but may be associated with the investment decisions. Secondly, the research is limited to retail investors and does not consider the factors influencing institutional investors' intention while making investment decisions. Lastly, the current study is cross-sectional in nature that may not capture the impact of time lags. An Examination of Behavioral Factors Affecting the Retail Investor's… 106 Practical Implementation: The current study identifies various aspects and factors that significantly impact retail investors in investing decisions. The Brokerage firms may use the results of this study to analyze their clients' intentions (retail investors) and then decide about the appropriate investment opportunity for them. Originality/Value: This is the first study that identifies retail investors' behavior while making investment decisions under the current economic crises of COVID-19. Also, no other study so far conducted to identify the association of behavioral factors and retail investors' intentions for investment through the indirect path of investor's perception; this is the first attempt of this kind.
What is the role of social interactions in the creation of price bubbles? Answering this question requires obtaining collective behavioural traces generated by the activity of a large number of actors. Digital currencies offer a unique possibility to measure socio-economic signals from such digital traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has experienced periods of rapid increase in exchange rates (price) followed by sharp decline; we hypothesize that these fluctuations are largely driven by the interplay between different social phenomena. We thus quantify four socio-economic signals about Bitcoin from large datasets: price on online exchanges, volume of word-of-mouth communication in online social media, volume of information search and user base growth. By using vector autoregression, we identify two positive feedback loops that lead to price bubbles in the absence of exogenous stimuli: one driven by word of mouth, and the other by new Bitcoin adopters. We also observe that spikes in information search, presumably linked to external events, precede drastic price declines. Understanding the interplay between the socio-economic signals we measured can lead to applications beyond cryptocurrencies to other phenomena that leave digital footprints, such as online social network usage.
We investigate how distributed denial-of-service (DDoS) attacks and other disruptions affect the Bitcoin ecosystem. In particular, we investigate the impact of shocks on trading activity at the leading Mt. Gox exchange between April 2011 and November 2013. We find that following DDoS attacks on Mt. Gox, the number of large trades on the exchange fell sharply. In particular, the distribution of the daily trading volume becomes less skewed (fewer big trades) and had smaller kurtosis on days following DDoS attacks. The results are robust to alternative specifications, as well as to restricting the data to activity prior to March 2013, i.e., the period before the first large appreciation in the price of and attention paid to Bitcoin.
This paper investigates the dynamics of individual portfolios in a unique data set containing the disaggregated wealth of all households in Sweden. Between 1999 and 2002, we observe little aggregate rebalancing in the financial portfolio of participants. These patterns conceal strong household-level evidence of active rebalancing, which on average offsets about one-half of idiosyncratic passive variations in the risky asset share. Wealthy, educated investors with better diversified portfolios tend to rebalance more actively. We find some evidence that households rebalance toward a greater risky share as they become richer. We also study the decisions to trade individual assets. Households are more likely to fully sell directly held stocks if those stocks have performed well, and more likely to exit direct stockholding if their stock portfolios have performed well; but these relationships are much weaker for mutual funds, a pattern that is consistent with previous research on the disposition effect among direct stockholders and performance sensitivity among mutual fund investors. When households continue to hold individual assets, however, they rebalance both stocks and mutual funds to offset about one-sixth of the passive variations in individual asset shares. Households rebalance primarily by adjusting purchases of risky assets if their risky portfolios have performed poorly, and by adjusting both fund purchases and full sales of stocks if their risky portfolios have performed well. Finally, the tendency for households to fully sell winning stocks is weaker for wealthy investors with diversified portfolios of individual stocks. © 2009 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
Crashes have fascinated and baffled many canny observers of financial
markets. In the strict orthodoxy of the efficient market theory, crashes must
be due to sudden changes of the fundamental valuation of assets. However,
detailed empirical studies suggest that large price jumps cannot be explained
by news and are the result of endogenous feedback loops. Although plausible, a
clear-cut empirical evidence for such a scenario is still lacking. Here we show
how crashes are conditioned by the market liquidity, for which we propose a new
measure inspired by recent theories of market impact and based on readily
available, public information. Our results open the possibility of a dynamical
evaluation of liquidity risk and early warning signs of market instabilities,
and could lead to a quantitative description of the mechanisms leading to
market crashes.
We present a thorough empirical analysis of market impact on the Bitcoin/USD
exchange market using a complete dataset that allows us to reconstruct more
than one million metaorders. We empirically confirm the "square-root law" for
market impact, which holds on four decades in spite of the quasi-absence of
statistical arbitrage and market marking strategies. We show that the
square-root impact holds during the whole trajectory of a metaorder and not
only for the final execution price. We also attempt to decompose the order flow
into an "informed" and "uninformed" component, the latter leading to an almost
complete long-term decay of impact. This study sheds light on the hypotheses
and predictions of several market impact models recently proposed in the
literature. Our empirical results strongly supports the statistical latent
order book model as the most relevant candidate to explain price impact on the
Bitcoin market - and therefore probably on other markets as well.
What is the role of social interactions in the creation of price bubbles?
Answering this question requires obtaining collective behavioural traces
generated by the activity of a large number of actors. Digital currencies offer
a unique possibility to measure socio-economic signals from such digital
traces. Here, we focus on Bitcoin, the most popular cryptocurrency. Bitcoin has
experienced periods of rapid increase in exchange rates (price) followed by
sharp decline; we hypothesise that these fluctuations are largely driven by the
interplay between different social phenomena. We thus quantify four
socio-economic signals about Bitcoin from large data sets: price on on-line
exchanges, volume of word-of-mouth communication in on-line social media,
volume of information search, and user base growth. By using vector
autoregression, we identify two positive feedback loops that lead to price
bubbles in the absence of exogenous stimuli: one driven by word of mouth, and
the other by new Bitcoin adopters. We also observe that spikes in information
search, presumably linked to external events, precede drastic price declines.
Understanding the interplay between the socio-economic signals we measured can
lead to applications beyond cryptocurrencies to other phenomena which leave
digital footprints, such as on-line social network usage.
In this paper we examine the price movements of contracts that represent bets on NBA games and find that the disposition effect causes significant deviations between contract prices and values. The contracts under examination are listed on Tradesports, a prediction market which provides an ideal venue for testing this and other behavioral theories because of its asset properties, market structure, and the absence of the joint hypothesis problem. In our analysis, we forecast the projected final combined scores of both teams in a contest based on observed withingame scores and game time remaining. At all points in time throughout each game, mean future returns (measured as Ticks to Expiry) should be no different than zero. However, we find that contracts which have fallen off pace to exceed the stated contract total become overpriced and
experience negative future returns. Likewise, we provide evidence that contracts on games in which teams are on pace to exceed the stated total become underpriced and experience significantly positive future returns. These findings are consistent with the disposition effect in which traders tend to hold losing positions to avoid realizing losses yet prematurely unwind winning positions to realize gains.
Opinion of geological experts is often formed despite a paucity of data and is usually based on prior experience. In such situations humans employ heuristics (rules of thumb) to aid analysis and interpretation of data. As a result, future judgements are bootstrapped from, and hence biased by, both the heuristics employed and prior opinion.
This paper reviews the causes of bias and error inherent in prior information derived from the probabilistic judgements of people. Parallels are developed between the evolution of scientific opinion on one hand and the limits on rational behaviour on the other. We show that the combination of data paucity and commonly employed heuristics can lead to herding behaviour within groups of experts. Elicitation theory mitigates the effects of such behaviour, but a method to estimate reliable uncertainties on expert judgements remains elusive.
We have also identified several key directions in which future research is likely to lead to methods that reduce such emergent group behaviour, thereby increasing the probability that the stock of common knowledge will converge in a stable manner towards facts about the Earth as it really is. These include: (1) measuring the frequency with which different heuristics tend to be employed by experts within the geosciences; (2) developing geoscience-specific methods to reduce biases originating from the use of such heuristics; (3) creating methods to detect scientific herding behaviour; and (4) researching how best to reconcile opinions from multiple experts in order to obtain the best probabilistic description of an unknown, objective reality (in cases where one exists).
Do equity returns indicate the presence of herd behavior on the part of investors during periods of market stress? To test this proposition, the cross-sectional standard deviation of returns, or dispersion, is used to capture herd behavior. When individual returns herd around the market consensus, dispersions are predicted to be relatively low. In contrast, rational asset pricing models predict an increase in dispersion because individual returns are repelled away from the market return when stocks differ in their sensitivity to market movements. The results for both daily and monthly returns are inconsistent with the presence of herding during periods of large price movements. For example, during extreme down markets, when herding is expected to be most prevalent, the magnitude of the increase in the dispersion of actual returns is mirrored by the increase in the dispersion of predicted returns that are estimated from a rational asset pricing model.
A new model of consumer behavior is developed using a hybrid of cognitive psychology and microeconomics. The development of the model starts with the mental coding of combinations of gains and losses using the prospect theory value function. Then the evaluation of purchases is modeled using the new concept of “transaction utility.” The household budgeting process is also incorporated to complete the characterization of mental accounting. Several implications to marketing, particularly in the area of pricing, are developed.
Although many economists, most notably Strotz, have discussed dynamic inconsistency and precommitment, none have dealt directly with the essence of the problem: self-control. This paper attempts to fill that gap by modeling man as an organization. The Strotz model is recast to include the control features missing in his formulation. The organizational analogy permits us to draw on the theory of agency. We thus relate the individual's control problems with those that exist in agency relationships.
An informational cascade occurs when it is optimal for an individual, having observed the actions of those ahead of him, to follow the behavior of the preceding individual with regard to his own information. The authors argue that localized conformity of behavior and the fragility of mass behaviors can be explained by informational cascades. Copyright 1992 by University of Chicago Press.
This paper provides an overview of the recent theoretical and empirical research on herd behavior in financial markets. It looks at what precisely is meant by herding, the causes of herd behavior, the success of existing studies in identifying the phenomenon, and the effect that herding has on financial markets. Copyright 2001, International Monetary Fund
This paper examines the presence of herd formation in Chinese markets using both individual firm- and sector-level data. We analyze the behavior of return dispersions during periods of unusually large upward and downward changes in the market index. We also distinguish between the Shanghai and Shenzhen stock exchanges at the sector-level. Our findings indicate that herd formation does not exist in Chinese markets. We find that equity return dispersions are significantly higher during periods of large changes in the aggregate market index. However, comparing return dispersions for upside and downside movements of the market, we observe that return dispersions during extreme downside movements of the market are much lower than those for upside movements, indicating that stock returns behave more similarly during down markets. The findings support rational asset pricing models and market efficiency. Policy implications of the results for policymakers are discussed.
This paper calculates indices of central bank autonomy (CBA) for 163 central banks as of end-2003, and comparable indices for a subgroup of 68 central banks as of the end of the 1980s. The results confirm strong improvements in both economic and political CBA over the past couple of decades, although more progress is needed to boost political autonomy of the central banks in emerging market and developing countries. Our analysis confirms that greater CBA has on average helped to maintain low inflation levels. The paper identifies four broad principles of CBA that have been shared by the majority of countries. Significant differences exist in the area of banking supervision where many central banks have retained a key role. Finally, we discuss the sequencing of reforms to separate the conduct of monetary and fiscal policies. IMF Staff Papers (2009) 56, 263–296. doi:10.1057/imfsp.2008.25; published online 23 September 2008
This study analyzes the extent to which mutual funds purchase stocks based on their past returns as well as their tendency to exhibit 'herding' behavior (i.e., buying and selling the same stocks at the same time). The authors find that 77 percent of the mutual funds were 'momentum investors,' buying stocks that were past winners; however, most did not systematically sell past losers. On average, funds that invested on momentum realized significantly better performance than other funds. The authors also find relatively weak evidence that funds tended to buy and sell the same stocks at the same time. Copyright 1995 by American Economic Association.
To its proponents, the cryptocurrency Bitcoin offers the potential to disrupt payment systems and traditional currencies. It has also been subject to security breaches and wild price fluctuations. This paper identifies and analyzes the impact of suspicious trading activity on the Mt. Gox Bitcoin currency exchange, in which approximately 600,000 bitcoins (BTC) valued at 150 to more than $1,000 in two months.
Investor and media attention in Bitcoin has increased substantially in recently years, reflected by the incredible surge in news articles and considerable rise in the price of Bitcoin. Given the increased attention, there little is known about the behaviour of Bitcoin prices and therefore we add to the literature by studying price clustering. We find significant evidence of clustering at round numbers, with over 10% of prices ending with 00 decimals compared to other variations but there is no significant pattern of returns after the round number. We also support the negotiation hypothesis of Harris (1991) by showing that price and volume have a significant positive relationship with price clustering at whole numbers.
In this paper, we analyze the investment patterns of a large number of clients of a major Israeli brokerage house during 1994. We compare the behavior of clients making independent investment decisions to that of investors whose accounts were managed by brokerage professionals. Our main objective is to investigate whether the disposition effect (i.e., the tendency to sell winners quicker than losers), demonstrated in the US only for individual investors, also holds for professional investors. This analysis is important, as accepted financial theory predicts that prices are determined mainly by decisions made by professionals. We show that both professional and independent investors exhibit the disposition effect, although the effect is stronger for independent investors. The second objective of our study is the comparison of trade frequency, volume and profitability between independent and professionally managed accounts. We believe that these comparisons not only provide insights of their own, but also help to put the differences in the disposition effect in a wider perspective. We demonstrate that professionally managed accounts were more diversified and that round trips were both less correlated with the market and slightly more profitable than those of independent accounts.
Expected utility theory reigned for several decades as the dominant normative and descriptive model of decision making under uncertainty, but it has come under serious question in recent years. There is now general agreement that the theory does not provide an adequate description of individual choice: a substantial body of evidence shows that decision makers systematically violate its basic tenets. Many alternative models have been proposed in response to this empirical challenge (for reviews, see Camerer J Risk Uncertain 2:61–104, 1989; Fishburn Nonlinear preference and utility theory. The Johns Hopkins University Press, Baltimore, 1988; Machina Econ Perspect 1(1):121–154, 1987). Some time ago we presented a model of choice, called prospect theory, which explained the major violations of expected utility theory in choices between risky prospects with a small number of outcomes (Kahneman and Tversky Econometrica 47:263–291, 1979; Tversky and Kahneman J Bus 59(4):S251–S278, 1986). The key elements of this theory are (1) a value function that is concave for gains, convex for losses, and steeper for losses than for gains, and (2) a nonlinear transformation of the probability scale, which overweights small probabilities and underweights moderate and high probabilities. In an important later development, several authors (Quiggin J Econ Behav Organ 3, 323–343; Schmeidler Econometrica 57:571–587, 1989; Yaari Econometrica 55:95–115, 1987; Weymark Math Soc Sci 1:409–430, 1981) have advanced a new representation, called the rank-dependent or the cumulative functional, that transforms cumulative rather than individual probabilities. This article presents a new version of prospect theory that incorporates the cumulative functional and extends the theory to uncertain as well to risky prospects with any number of outcomes. The resulting model, called cumulative prospect theory, combines some of the attractive features of both developments (see also Luce and Fishburn J Risk Uncertain 4:29–59, 1991). It gives rise to different evaluations of gains and losses, which are not distinguished in the standard cumulative model, and it provides a unified treatment of both risk and uncertainty.
Amid its rapidly increasing usage and immense public interest the subject of Bitcoin has raised profound economic and societal issues. In this paper we undertake economic and econometric modelling of Bitcoin prices. As with many asset classes we show that Bitcoin exhibits speculative bubbles. Further, we find empirical evidence that the fundamental price of Bitcoin is zero.
In this paper, we analyze the investment patterns of a large number of clients of a major Israeli brokerage house during 1994. We compare the behavior of clients making independent investment decisions to that of investors whose accounts were managed by brokerage professionals. Our main objective is to investigate whether the disposition effect (i.e., the tendency to sell winners quicker than losers), demonstrated in the US only for individual investors, also holds for professional investors. This analysis is important, as accepted financial theory predicts that prices are determined mainly by decisions made by professionals. We show that both professional and independent investors exhibit the disposition effect, although the effect is stronger for independent investors.The second objective of our study is the comparison of trade frequency, volume and profitability between independent and professionally managed accounts. We believe that these comparisons not only provide insights of their own, but also help to put the differences in the disposition effect in a wider perspective. We demonstrate that professionally managed accounts were more diversified and that round trips were both less correlated with the market and slightly more profitable than those of independent accounts.
We document that mutual fund managers exhibit the disposition bias, or the tendency to hold on too long to poorly performing stocks. This bias arises because of the psychological unwillingness to admit past mistakes. We show that new fund managers, who are emotionally unattached to their predecessors' decisions, sell the momentum losers they have inherited more readily than continuing fund managers. They also sell more losers than winners, and this difference is higher than for continuing managers. The results are robust to various measures of trade and definitions of the control group. The effects are more pronounced when the outgoing manager is young, perhaps because new managers have less respect for the portfolio decisions of younger predecessors. Given that mutual funds hold a large fraction of the U.S. equity market, this finding may shed light on the origins of price momentum.
for their helpful comments and suggestions. All remaining errors are our own.
Examining NFL betting contracts at Tradesports.com, we find mispricing consistent with the disposition effect, where investors are more likely to close out profitable positions than losing positions. Prices are too low when teams are ahead and too high when teams are behind. Returns following news events exhibit short-term reversals and longer-term momentum. These results do not appear driven by liquidity or non-financial reasons for trade. Finding the disposition effect in a negative expected return gambling market questions standard explanations for the effect (belief in mean reversion, prospect theory). It is consistent with cognitive dissonance, and models with time-inconsistent behaviour.
While several studies have documented behavioral biases in the behavior of individual investors, very little is known about the existence of such biases in corporations. We utilize the unique nature of Real Estate Investment Trusts (REITs) to test for the presence of one of the most widely discussed biases, the disposition effect. Using property level REIT data, we find strong statistical evidence that REIT managers tend to sell winners and hold losers, where winners and losers are defined using changes in properties' prices since they were acquired. In addition, we find evidence that this behavior is consistent with the disposition effect. REIT managers are significantly less likely to sell properties that have a loss relative to a reference point based on inflation or historical average returns, controlling for the properties' recent returns. Management of corporations with greater tendencies toward disposition effect behavior tend to sell winner properties at lower prices, all else equal. We find no support for three alternative explanations, optimal tax timing, mean reverting property-level returns, and asymmetric information.
Using brokerage account data from China, we study investment decision making in an emerging market. We find that Chinese investors make poor trading decisions: the stocks they purchase underperform those they sell. We also find that Chinese investors suffer from three behavioral biases: (i) they tend to sell stocks that have appreciated in price, but not those that have depreciated in price, consistent with a disposition effect, acknowledging gains but not losses; (ii) they seem overconfident; and (iii) they appear to believe that past returns are indicative of future returns (a representativeness bias). In comparisons to prior findings, Chinese investors seem more overconfident than U.S. investors (i.e., the Chinese hold fewer stocks, yet trade very often) and their disposition effect appears stronger. Finally, we categorize Chinese investors based on proxy measures of experience and find that “experienced” investors are not always less prone to behavioral biases than are “inexperienced” ones. Copyright © 2007 John Wiley & Sons, Ltd.
This study examines whether the disposition effect (DE), i.e., the tendency of investors to ride losses and realize gains, exists in the Korean stock index futures market. Using a unique database, we find strong evidence for the DE and explain this in terms of investor characteristics. We also investigate the effect that the disposition bias has on investment performance. There are four main findings. First, individual investors are much more susceptible to the DE than institutional and foreign investors. Second, sophistication and trading experience tend to reduce the DE. Third, the DE is stronger in long positions than in short positions. Finally, there is a negative relationship between the DE and investment performance. This result is consistent with Odean (1998, Journal of Finance, 53, 1775–1798), but contrasts with Locke and Mann (2005, Journal of Financial Economics, 76, 401–444) who find no evidence of any contemporaneous measurable costs associated with the DE. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 29:496–522, 2009
Anew model of consumer behavior is developed using a hybrid of cognitive psychology and microeconomics. The development of the model starts with the mental coding of combinations of gains and losses using the prospect theory value function. Then the evaluation of purchases is modeled using the new concept of “transaction utility.” The household budgeting process is also incorporated to complete the characterization of mental accounting. Several implications to marketing, particularly in the area of pricing, are developed.
This article was originally published in Marketing Science, Volume 4, Issue 3, pages 199–214, in 1985.
We examine the investment behavior of market participants within different international markets (i.e., US, Hong Kong, Japan, South Korea, and Taiwan), specifically with regard to their tendency to exhibit herd behavior. We find no evidence of herding on the part of market participants in the US and Hong Kong and partial evidence of herding in Japan. However, for South Korea and Taiwan, the two emerging markets in our sample, we document significant evidence of herding. The results are robust across various size-based portfolios and over time. Furthermore, macroeconomic information rather than firm-specific information tends to have a more significant impact on investor behavior in markets which exhibit herding. In all five markets, the rate of increase in security return dispersion as a function of the aggregate market return is higher in up market, relative to down market days. This is consistent with the directional asymmetry documented by McQueen et al. (1996) (McQueen, G., Pinegar, M.A., Thorley, S., 1996. Journal of Finance 51, 889–919).
This paper shows that prospect theory is unlikely to explain the disposition effect. Prospect theory predicts that the propensity to sell a stock declines as its price moves away from the purchase price in either direction. Trading data, on the other hand, show that the propensity to sell jumps at zero return, but it is approximately constant over a wide range of losses and increasing or constant over a wide range of gains. Further, the pattern of realized returns does not seem to stem from optimal after-tax portfolio rebalancing, a belief in mean-reverting returns, or investors acting on target prices.
We investigate whether prospect theory preferences can predict a disposition effect. We consider two implementations of prospect theory: in one case, preferences are defined over "annual" gains and losses; in the other, they are defined over "realized" gains and losses. Surprisingly, the annual gain/loss model often fails to predict a disposition effect. The realized gain/loss model, however, predicts a disposition effect more reliably. Utility from realized gains and losses may therefore be a useful way of thinking about certain aspects of individual investor trading. Copyright (c) 2009 the American Finance Association.
The author analyzes a sequential decision model in which each decisionmaker looks at the decisions made by previous decisionmakers in taking her own decision. This is rational for her because these other decisionmakers may have some information that is important for her. The author then shows that the decision rules that are chosen by optimizing individuals will be characterized by herd behavior; i.e., people will be doing what others are doing rather than using their information. The author then shows that the resulting equilibrium is inefficient. Copyright 1992, the President and Fellows of Harvard College and the Massachusetts Institute of Technology.
We propose a theory based on investor overconfidence and biased self- attribution to explain several of the securities returns patterns that seem anomalous from the perspective of efficient markets with rational investors. The theory is based on two premises derived from evidence in psychological studies. The first is that individuals are overconfident about their ability to evaluate securities, in the sense that they overestimate the precision of their private information signals. The second is that investors' confidence changes in a biased fashion as a function of their decision outcomes. The first premise implies overreaction to private information arrival and underreaction to public information arrival. This is consistent with (1) post-corporate event and post-earnings announcement stock price 'drift', (2) negative long- lag autocorrelations (long-run 'overreaction'), and (3) excess volatility of asset prices. Adding the second premise leads to (4) positive short-lag autocorrelations ('momentum'), and (5) short-run post-earnings announcement 'drift,' and negative correlation between future stock returns and long-term measures of past accounting performance. The model also offers several untested empirical implications and implications for corporate financial policy.
We develop a new version of prospect theory that employs cumulative rather than separable decision weights and extends the theory in several respects. This version, called cumulative prospect theory, applies to uncertain as well as to risky prospects with any number of outcomes, and it allows different weighting functions for gains and for losses. Two principles, diminishing sensitivity and loss aversion, are invoked to explain the characteristic curvature of the value function and the weighting functions. A review of the experimental evidence and the results of a new experiment confirm a distinctive fourfold pattern of risk: risk aversion for gains and risk seeking for losses of high probability; risk seeking for gains and risk aversion for losses of low probability. Copyright 1992 by Kluwer Academic Publishers
This paper provides an in depth analysis of an investor’s reluctance to realize losses and his propensity to realize gains – a behavior known as the disposition effect. Together, sophistication (static differences across investors) and trading experience (evolving behavior of a single investor) eliminate the reluctance to realize losses. However, an asymmetry exists as sophistication and trading experience reduce the propensity to realize gains by 37% (but fail to eliminate this part of the behavior.) Our research design allows us to follow an individual’s behavior from the start of his investing life/career. This ability makes it possible to track the evolution of the disposition effect as it is reduced and/or disappears. Our results are robust to alternative explanations including feedback trading, calendar effects, and frequency of observation. Copyright Springer 2005
A unique data set allows us to monitor the buys, sells, and holds of individuals and institutions in the Finnish stock market on a daily basis. With this data set, we employ Logit regressions to identify the determinants of buying and selling activity over a two-year period. We find evidence that investors are reluctant to realize losses, that they engage in tax-loss selling activity, and that past returns and historical price patterns, such as being at a monthly high or low, affect trading. There also is modest evidence that life-cycle trading plays a role in the pattern of buys and sells. Copyright The American Finance Association 2001.
I test the disposition effect, the tendency of investors to hold losing investments too long and sell winning investments too soon, by analyzing trading records for 10,000 accounts at a large discount brokerage house. These investors demonstrate a strong preference for realizing winners rather than losers. Their behavior does not appear to be motivated by a desire to rebalance portfolios, or to avoid the higher trading costs of low priced stocks. Nor is it justified by subsequent portfolio performance. For taxable investments, it is suboptimal and leads to lower after-tax returns. Tax-motivated selling is most evident in December. Copyright The American Finance Association 1998.
The net buying (selling) volume of the most net buyer (seller) brokers over a unit period is a widely followed piece of information in Istanbul Stock Market, which most market commentaries inaccurately refer to as “the net money in- or outflow”. It is, in fact, a proxy for big investors’ trading. In this note, we test whether this information has predictive value, whether market participants’ emphasis on this information is justified, or just an illusion. By doing so, we add to the literature on the relationship between big investors’ trading and stock returns, using a unique information set. Results suggest a significant contemporaneous association between the “net inflow” and current returns, but little predictive value
Analysis of decision making under risk has been dominated by expected utility theory, which generally accounts for people's actions. Presents a critique of expected utility theory as a descriptive model of decision making under risk, and argues that common forms of utility theory are not adequate, and proposes an alternative theory of choice under risk called prospect theory. In expected utility theory, utilities of outcomes are weighted by their probabilities. Considers results of responses to various hypothetical decision situations under risk and shows results that violate the tenets of expected utility theory. People overweight outcomes considered certain, relative to outcomes that are merely probable, a situation called the "certainty effect." This effect contributes to risk aversion in choices involving sure gains, and to risk seeking in choices involving sure losses. In choices where gains are replaced by losses, the pattern is called the "reflection effect." People discard components shared by all prospects under consideration, a tendency called the "isolation effect." Also shows that in choice situations, preferences may be altered by different representations of probabilities. Develops an alternative theory of individual decision making under risk, called prospect theory, developed for simple prospects with monetary outcomes and stated probabilities, in which value is given to gains and losses (i.e., changes in wealth or welfare) rather than to final assets, and probabilities are replaced by decision weights. The theory has two phases. The editing phase organizes and reformulates the options to simplify later evaluation and choice. The edited prospects are evaluated and the highest value prospect chosen. Discusses and models this theory, and offers directions for extending prospect theory are offered. (TNM)
Standard models of informed speculation suggest that traders try to learn information that others do not have. This result implicitly relies on the assumption that speculators have long horizons, i.e., can hold the asset forever. By contrast, the authors show that if speculators have short horizons, they may herd on the same information, trying to learn what other informed traders also know. There can be multiple herding equilibria, and herding speculators may even choose to study information that is completely unrelated to fundamentals. Copyright 1992 by American Finance Association.