Herding behavior in online P2P lending: An empirical investigation

Lee, Eun‐Kyoung; Lee, Byungtae

doi:10.1016/j.elerap.2012.02.001

Cited by 312 publications

(160 citation statements)

References 36 publications

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“…Traditionally, as financial intermediaries, banks play a significant role in reducing information asymmetries because they are thought to have the financial expertise and extensive experience to evaluate the creditworthiness of borrowers and allocate capital accordingly (Diamond, 1984). In the P2P online lending market, transaction costs are reduced by eliminating expensive intermediaries, but as non-financial experts dominate in this pseudonymous online lending market, the problems associated with information asymmetry, particularly adverse selection, may become more severe than those that emerge in the traditional lending market (Lee and Lee, 2012). How to mitigate information asymmetry between borrowers and lenders is critical for the online lending market's long-term success.…”

Section: Introductionmentioning

confidence: 99%

Who can get money? Evidence from the Chinese peer-to-peer lending platform

2017

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This paper explores how borrowers' financial and personal information, loan characteristics and lending models affect peer-to-peer (P2P) loan funding outcomes. Using a large sample of listings from one of the largest Chinese online P2P lending platforms, we find that those borrowers earning a higher income or who own a car are more likely to receive a loan, pay lower interest rates, and are less likely to default. The credit grade assigned by the lending platform may not represent the creditworthiness of potential borrowers. We also find that the unique offline process in the Chinese P2P online lending platform exerts significant influence on the lending decision. We discuss the implications of our results for the design of big databased lending markets.

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Section: Introductionmentioning

confidence: 99%

Who can get money? Evidence from the Chinese peer-to-peer lending platform

2017

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“…Furthermore, investors may lack the ability to properly identify the probability of success of a project. The effects of this information asymmetry may multiply to a large number of investors if the first investors funding a project signal its financial and operational soundness, which creates herding (Lee and Lee, 2012).…”

Section: Consumer Protection Issuesmentioning

confidence: 99%

Alternative Finance (Crowdfunding) Regulation in Latin America and the Caribbean: A Balancing Act

Herrera¹

2016

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work is licensed under a Creative Commons IGO 3.0 Attribution-NonCommercial-NoDerivatives (CC-IGO BY-NC-ND 3.0 IGO) license (http://creativecommons.org/ licenses/by-nc-nd/3.0/igo/legalcode) and may be reproduced with attribution to the IDB and for any noncommercial purpose. No derivative work is allowed.Any dispute related to the use of the works of the IDB that cannot be settled amicably shall be submitted to arbitration pursuant to the UNCITRAL rules. The use of the IDB's name for any purpose other than for attribution, and the use of IDB's logo shall be subject to a separate written license agreement between the IDB and the user and is not authorized as part of this CC-IGO license.Note that link provided above includes additional terms and conditions of the license.The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the Inter-American Development Bank, its Board of Directors, or the countries they represent.http://www.iadb.org 2016 Abstract * Alternative finance (AF) or "crowdfunding" is the most notable financial technology (fintech) business model in Latin America and the Caribbean. Although still small in volume, reaching US$110.46 million across the region, its rapid growth poses a challenge for regulators. This paper offers a conceptual understanding of the typical enterprise model for AF, and from it describes the main challenges for regulators. It proposes recommendations for policymakers and regulators, taking into account the need for balance and proportion in terms of the nature, size, and character of the platform.JEL Codes: G23, G28

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“…Our findings of herding from the confirmation of diminishing marginal returns in the extreme outliers are by inference that may not be imputable to other large cap stocks listed on the NYSE. 7) Lee, Lee, and Chae (2012) develop two hypotheses: H1, an auction with a higher participation rate attracts more bids, and H2, there is a diminishing marginal effect of the participation rate when herding is detected.…”

Section: The Market Return On Day T Lies In the Extremementioning

confidence: 99%

“…In order to develop testable hypotheses, we cross pollinate the analytical frameworks of Christie and Huang (1995) and Chang et al(2000) with those of Lee et al (2012), which provide the experimental hypotheses for an empirical herd study that deals with the relationship between stock price and trading volume. 7) It should be noted that we use a 20-day moving average of both price and trading volume changes as the basis of calculating abnormal returns of individual stocks involved rather than Christie and Huang's market returns as the basis for calculating equity returns.…”

Section: The Market Return On Day T Lies In the Extremementioning

confidence: 99%

“…al. (2000) and the logistic regression of Lee, Lee and Chae (2012), we measure the diminishing marginal effect in the return dispersion series with the log-log regression analysis. In our case, we infer that investor herding exists when beta values of our log-log regression are positive at less than one, that is 0 < X < 1.…”

Section: The Market Return On Day T Lies In the Extremementioning

confidence: 99%

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Herding in Large Cap Stocks during Bull Markets: Evidence from Dow Jones Industrial Stocks

Kang¹,

Pyun²

2014

Glob Bus Financ Rev

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A B S T R A C TWe investigate evidence of investor herding in individual component stocks of the Dow Jones Industrial Index. In the correlation analysis, all stocks show positive correlations between their price and trading volume changes. In the dummy regression, most stocks in their equal-and value-weights show strong herd behavior in the upper values relative to their moving average prices. In log-log regression, we find a diminishing marginal effect in the upper values of their moving average prices. We find that the greater the dispersion of a stock away from its moving average line, the stronger the evidence of true herding in the movement of its price and concomitant change in trading volume.

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Herding behavior in online P2P lending: An empirical investigation

Cited by 312 publications

References 36 publications

Who can get money? Evidence from the Chinese peer-to-peer lending platform

Who can get money? Evidence from the Chinese peer-to-peer lending platform

Alternative Finance (Crowdfunding) Regulation in Latin America and the Caribbean: A Balancing Act

Herding in Large Cap Stocks during Bull Markets: Evidence from Dow Jones Industrial Stocks

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