• 제목/요약/키워드: Herding Behavior

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Herd behavior and volatility in financial markets

  • Park, Beum-Jo
    • Journal of the Korean Data and Information Science Society
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    • 제22권6호
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    • pp.1199-1215
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    • 2011
  • Relaxing an unrealistic assumption of a representative percolation model, this paper demonstrates that herd behavior leads to a high increase in volatility but not trading volume, in contrast with information flows that give rise to increases in both volatility and trading volume. Although detecting herd behavior has posed a great challenge due to its empirical difficulty, this paper proposes a new methodology for detecting trading days with herding. Furthermore, this paper suggests a herd-behavior-stochastic-volatility model, which accounts for herding in financial markets. Strong evidence in favor of the model specification over the standard stochastic volatility model is based on empirical application with high frequency data in the Korean equity market, strongly supporting the intuition that herd behavior causes excess volatility. In addition, this research indicates that strong persistence in volatility, which is a prevalent feature in financial markets, is likely attributed to herd behavior rather than news.

Behavioral Factors on Individual Investors' Decision Making and Investment Performance: A Survey from the Vietnam Stock Market

  • CAO, Minh Man;NGUYEN, Nhu-Ty;TRAN, Thanh-Tuyen
    • The Journal of Asian Finance, Economics and Business
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    • 제8권3호
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    • pp.845-853
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    • 2021
  • The stock market shows the current health of an economy, and investment performance represents it. This study aims to clarify the relationship between financial behavior and investment decisions as well as its impact on investment results. Determine the influence of behavioral factors on individual investors' investment decisions and investment performance on the Vietnam stock market. The study surveyed 250 investors. The main analytical methods used are Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM). Research results show that Heuristic, Prospect, Market, and Herding directly and positively affect investment decision-making. Besides, the above factors have a direct and positive effect on investment performance. In particular, the Prospect factor has the strongest influence on investment decision-making and investment performance. The major findings of this study suggested that the important role of Heuristic, Prospect, Market, and Herding on Investment Decision-making and Investment Performance. Prospect had the strongest impact on Investment decision-making (β = 0.275). Heuristic had the second strongest impact (β = 0.257), then Herding (β = 0.202), and finally Market (β = 0.189) had the weakest effect. Regarding Investment Performance, the Prospect factor has a higher degree of impact than Heuristic Herding and Market.

Herding in Fast Moving Consumer Group Sector: Equity Market Asymmetry and Crisis

  • BHARTI, Bharti;KUMAR, Ashish
    • The Journal of Asian Finance, Economics and Business
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    • 제7권9호
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    • pp.39-49
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    • 2020
  • This study empirically examines herd behavior for fast moving consumer goods (FMCG) sector stocks under varied market return conditions and the period during the global financial crisis and its aftermath. We examine the sample of stocks trading on the Nifty FMCG Index of the Indian equity market from January 2008 up to December 2018 using the dispersion measure of cross sectional absolute deviation and examine its relationship with the market return to explore herd phenomenon. Quantile regression estimate is used and the results of the study validate rational asset pricing models as the sector does not display herding. In contrast, anti-herd behavior at lower and median quantile values is observed. A possible reason can be the non-cyclical nature of the industry where investors rely more on the fundamentals rather than crowd chasing. We also findthe absence of herd phenomenon during the market asymmetries of bull and bear phases, extreme movements, the period of the global financial crisis, and afterward. We further examine herding under the impact of the information technology (IT) industry and conclude that significant return movements in IT sector impact dispersions in the FMCG industry. Also, there is a co-varying risk between the two sectors confirming the spillover in an integrated market.

Herding Behavior: Do Domestic Investors Herd Toward Foreign Investors in Vietnam Stock Market?

  • NGUYEN P., Quynh
    • The Journal of Asian Finance, Economics and Business
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    • 제9권9호
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    • pp.9-24
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    • 2022
  • With a view to attracting foreign investment and growing the economy, the Vietnamese government has hastened financial reforms, including the lifting of limitations on foreign investment, which has resulted in rapidly rising foreign ownership in recent years. To study the relationship between transactions of foreign investors and transactions of domestic investors on two stock exchanges in Vietnam Ho Chi Minh City Stock Exchange (HSX) and Hanoi Stock Exchange (HNX). This study applies a secondary dataset comprising daily market trading information of 912 stocks from 18 industries listed on 2 Vietnam stock exchanges, including HSX and HNX, which includes executed price, executed volume, daily Buy Orders, and Sell Orders categorized into domestic investors' orders and foreign investors orders from 01.04.2010 to 10.04.2018. The regression results show a significantly positive relationship between foreign investors' trading and domestic investors' transaction in all trading activities in both up and down markets. Therefore, these results indicate that domestic investors in Vietnam are concerned with foreign investors' trading as an important sign, and domestic investors tend to follow their counterparties without appropriate fundamental information. From there, there are signs of herding behavior of domestic investors following foreign investors in transactions on the stock market in Vietnam.

Choosing Solitude in Turmoil, Herding in the Decentralized Finance (DeFi) Token Market: An International Perspective

  • OZCAN, Rasim;KHAN, Asad ul Islam;TURGUT, Murat;NAPARI, Ayuba
    • The Journal of Asian Finance, Economics and Business
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    • 제9권9호
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    • pp.105-114
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    • 2022
  • Financial markets have long been known to be prone to behavioral biases. One such behavioural bias that is consequential yet pervasive in financial markets is the herd effect. The objective of this study is to determine whether or not there exist herd behaviour in the new and bourgeoning Decentralized Finance (DeFi) Tokens market. This is accomplished by using daily returns of 22 DeFi tokens from January 29, 2017 to August 19, 2021, and the Cross-sectional Absolute Deviation (CSAD) of market returns to capture herd behavior. The results fail to provide any evidence of herding in the DeFi token market on bullish days, that is days for which the average market returns is positive. For bearish days however, that is days for which the market returns is negative, our empirical findings point to the presence of adverse herding in the DeFi token market. This phenomenon can be explained to some extent by the investor composition of the DeFi market. The DeFi token space is a growth market dominated by experts and/or enthusiasts who are insulated against the temptation and panic of negative market swings by the level of market and technical information they possess on the assets they invest.

Quantitative Analysis of the Swimming Movements of Flatfish Reacting to the Ground Gear of Bottom Trawls

  • Kim, Yong-Hae;Wardle Clem S.
    • Fisheries and Aquatic Sciences
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    • 제9권4호
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    • pp.167-174
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    • 2006
  • Two typical responses have been documented for flatfish when they encounter the ground gear of bottom trawls: herding response and falling back response. These two responses were analyzed from video recordings of fish and were characterized by time sequences for four parameters: swimming speed, angular velocity, acceleration, and distance between the fish and the ground gear. When flatfish displayed the falling-back response, absolute values of the three swimming parameters and their deviations were significantly higher than those during the herding response. However, the swimming parameters were not dependent on the distance between the flatfish and the ground gear, regardless of which response occurred. The dominant periods for most of the movement parameters ranged from 2.0 to 3.7 s, except that no periodicity was observed for swimming speed or angular velocity during the falling-back response. However, variations in the four parameters during the falling -back response revealed greater irregularity in periodicity and higher amplitudes. This complex behavior is best described as a chaos phenomenon' and is discussed as the building block for a model predicting the responses of flatfish to ground gear as part of the general understanding of the fish capture process.

Modeling the Selectivity of the Cod-end of a Trawl Using Chaotic Fish Behavior and Neural Networks

  • Kim, Yong-Hae;Wardle, Clement S.
    • Fisheries and Aquatic Sciences
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    • 제11권1호
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    • pp.61-69
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    • 2008
  • Using empirical data of fish performance and physiological limits as well as physical stimuli and environmental data, a cod-end selectivity model based on a chaotic behavior model using the psycho-hydraulic wheel and neural-network approach was established to predict fish escape or herding responses in trawl and cod-end designs. Fish responses in the cod-end were categorized as escape or herding reactions based on their relative positions and reactions to the net wall. Fish movements were regulated by three factors: escape time, a visual looming effect, and an index of body girth-mesh size. The model was applied to haddock in a North Sea bottom trawl including frequencies of movement components, swimming speed, angular velocity, distance to net wall, and the caught-fish ratio; simulation results were similar to field observations. The ratio of retained fish in the cod-end was limited to 37-95% by optomotor coefficient values of 0.3-1.0 and to 13-67% by looming coefficient values of 0.1-1.0. The selectivity curves generated by this model were sensitive to changes in mesh size, towing speed, mesh type, and mesh shape.

개별 주가에 반영된 시변 무리행동 연구 (Study on time-varying herd behavior in individual stocks)

  • 박범조
    • Journal of the Korean Data and Information Science Society
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    • 제22권3호
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    • pp.423-436
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    • 2011
  • 정보기술의 발달과 함께 금융 자유화 확대 및 글로벌 금융시장의 동조화 등으로 인해 금융시장의 변동성이 현저하게 증폭되는 현상을 나타내고 있다. 최근 행태경제학 분야에서 이에 대한 주요 원인으로 금융시장의 무리행동에 대한 이론적 연구가 활발하게 진행되고 있지만 무리행동의 동적 속성에 대한 계량적 측정이 쉽지 않기 때문에 무리행동의 시계열적 속성을 파악할 수 있는 경험적 연구는 거의 전무하다. 따라서 본 연구는 QR-GARCH (quantile regression for generalized autoregressive conditional heteroskedasticity)모형을 이용하여 시변 무리행동을 시계열적으로 측정할 수 있는 무리 행동 측정법을 새롭게 제안하였다. 이 무리행동 측정법의 유용성과 개별 주가의 시변 무리행동 행태를 분석하기 위해 기업 규모별 세 그룹 (대기업, 일반기업, 소기업)으로 나눈 개별 주가 자료를 이용한 실증분석 결과를 수행하였으며 몇 가지 의미 있는 사실을 발견하였다. 우선 일부 대기업을 제외한 대부분의 주식 거래자에게서 무리행동이 발생하고 있으며 특히 일반기업 주식 거래자들의 경우 대기업과 소기업 주식 거래자들에 비해 강한 무리행동과 함께 심한 무리행동의 변화를 보여준다. 또한 예상과 달리 일부 무리행동 파라미터 시계열 자료에서 자기상관이 지속적으로 나타나고 있는데 이런 결과는 기업에 따라 주식 거래자의 쏠림현상이 오래 지속될 수도 있음을 의미한다.

Behavioral Biases on Investment Decision: A Case Study in Indonesia

  • KARTINI, Kartini;NAHDA, Katiya
    • The Journal of Asian Finance, Economics and Business
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    • 제8권3호
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    • pp.1231-1240
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    • 2021
  • A shift in perspective from standard finance to behavioral finance has taken place in the past two decades that explains how cognition and emotions are associated with financial decision making. This study aims to investigate the influence of various psychological factors on investment decision-making. The psychological factors that are investigated are differentiated into two aspects, cognitive and emotional aspects. From the cognitive aspect, we examine the influence of anchoring, representativeness, loss aversion, overconfidence, and optimism biases on investor decisions. Meanwhile, from the emotional aspect, the influence of herding behavior on investment decisions is analyzed. A quantitative approach is used based on a survey method and a snowball sampling that result in 165 questionnaires from individual investors in Yogyakarta. Further, we use the One-Sample t-test in testing all hypotheses. The research findings show that all of the variables, anchoring bias, representativeness bias, loss aversion bias, overconfidence bias, optimism bias, and herding behavior have a significant effect on investment decisions. This result emphasizes the influence of behavioral factors on investor's decisions. It contributes to the existing literature in understanding the dynamics of investor's behaviors and enhance the ability of investors in making more informed decision by reducing all potential biases.

사회적 특성과 개인적 특성이 가상자산 구매 의도에 미치는 영향 - NFT를 중심으로 (An Empirical Validation of Effecting Social Characteristics and Personal Characteristics on Virtual Asset Purchase Intention - Focusing on NFT)

  • 서재석;김상일;김정욱
    • 디지털산업정보학회논문지
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    • 제19권2호
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    • pp.161-175
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    • 2023
  • The purpose of this study is the effects of Social Characteristics and Personal Characteristics on Virtual Asset Purchase Intention. TPB (Theory of Planned Behavior) model is validated as a theoretical background. possessiveness, and innovation tendency, herding, subjective norm, attitude, and Purchase intention were composed of variables. The method of the study collected 474 data of those experienced in NFT through a survey and conducted as a structural equation modeling method using AMOS. The result of this paper shows that 4 hypotheses are accepted statistically significant except 1 hypotheses among 5 hypotheses. Therefore, this study demonstrated the factors that influence the purchase intention of non-fungible tokens. This study concluded that possessiveness, herding, subjective norm, attitude had a statistically significant effect on Purchase intention. NFT research is just getting started, and there are not many empirical studies targeting investors, interested people, and companies. In this respect, this study will be able to provide useful information for NFT research.