IDEAS home Printed from https://ideas.repec.org/a/eee/intfin/v76y2022ics1042443121001682.html
   My bibliography  Save this article

A clientele effect in online lending markets: Evidence from the comovement between investor sentiment and online lending rates

Author

Listed:
  • Chen, Rongda
  • Xu, Guorui
  • Xu, Feng
  • Jin, Chenglu
  • Yu, Jingjing

Abstract

This paper examines how online lending investor sentiment (OLIS) and investors’ heterogeneous requirements on online lending platforms’ compliance interact to affect online lending rates. Online lending platforms can be divided into different groups according to their compliance clientele, such as state-capital-platforms, listed-company-platforms, banking-platforms, venture-capital-platforms and private-platforms. Using data of platform characteristics and online lending rates in China, we find that online lending investor sentiments and online lending rates vary across the five groups of online lending platforms. Thus, there will be misleading if we use the investor sentiment constructed based on the whole online lending market to study the comovement between investor sentiment and online lending rates of each classification of platforms. We further find the evidence on the clientele effect in online lending market. Particularly, investor sentiment has less impact on online lending rates among platforms invested by investors with stronger requirement on the platforms’ compliance.

Suggested Citation

  • Chen, Rongda & Xu, Guorui & Xu, Feng & Jin, Chenglu & Yu, Jingjing, 2022. "A clientele effect in online lending markets: Evidence from the comovement between investor sentiment and online lending rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    • Handle: RePEc:eee:intfin:v:76:y:2022:i:c:s1042443121001682
    DOI: 10.1016/j.intfin.2021.101461
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1042443121001682
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intfin.2021.101461?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    2. Dashan Huang & Fuwei Jiang & Jun Tu & Guofu Zhou, 2015. "Investor Sentiment Aligned: A Powerful Predictor of Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 791-837.
    3. Hirshleifer, David & Daniel, Kent, 2015. "Overconfident investors, predictable returns, and excessive trading," MPRA Paper 69002, University Library of Munich, Germany.
    4. Canepa, Alessandra & de la O. González, María & Skinner, Frank S., 2020. "Hedge fund strategies: A non-parametric analysis," International Review of Financial Analysis, Elsevier, vol. 67(C).
    5. Kedar-Levy, Haim & Yu, Xiaoyan & Kamesaka, Akiko & Ben-Zion, Uri, 2010. "The impact of daily return limit and segmented clientele on stock returns in China," International Review of Financial Analysis, Elsevier, vol. 19(4), pages 223-236, September.
    6. Fong, Kingsley & Krug, Juliane D. & Leung, Henry & Westerholm, Joakim P., 2020. "Determinants of household broker choices and their impacts on performance," Journal of Banking & Finance, Elsevier, vol. 112(C).
    7. Ftiti, Zied & Hadhri, Sinda, 2019. "Can economic policy uncertainty, oil prices, and investor sentiment predict Islamic stock returns? A multi-scale perspective," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 40-55.
    8. Jun, Xiao & Li, Mingsheng & Shi, Jing, 2014. "Volatile market condition and investor clientele effects on mutual fund flow performance relationship," Pacific-Basin Finance Journal, Elsevier, vol. 29(C), pages 310-334.
    9. Kent Daniel & David Hirshleifer, 2015. "Overconfident Investors, Predictable Returns, and Excessive Trading," Journal of Economic Perspectives, American Economic Association, vol. 29(4), pages 61-88, Fall.
    10. Pettit, R. Richardson, 1977. "Taxes, transactions costs and the clientele effect of dividends," Journal of Financial Economics, Elsevier, vol. 5(3), pages 419-436, December.
    11. Grant, Andrew & Jarnecic, Elvis & Su, Mark, 2015. "Asymmetric effects of sell-side analyst optimism and broker market share by clientele," Journal of Financial Markets, Elsevier, vol. 24(C), pages 49-65.
    12. Benhabib, Jess & Liu, Xuewen & Wang, Pengfei, 2016. "Sentiments, financial markets, and macroeconomic fluctuations," Journal of Financial Economics, Elsevier, vol. 120(2), pages 420-443.
    13. CURATOLA, Giuliano & DONADELLI, Michael & KIZYS, Renatas & RIEDEL, Max, 2016. "Investor Sentiment and Sectoral Stock Returns: Evidence from World Cup Games," Finance Research Letters, Elsevier, vol. 17(C), pages 267-274.
    14. Ging‐Ginq Pan & Yung‐Ming Shiu & Tu‐Cheng Wu, 2018. "Analysis of the clientele effect and the information content of short‐term index option returns in Taiwan," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(6), pages 715-730, June.
    15. Jinfang Li & Chunpeng Yang, 2017. "The cross-section and time-series effects of individual stock sentiment on stock prices," Applied Economics, Taylor & Francis Journals, vol. 49(47), pages 4806-4815, October.
    16. Denis, Diane K. & McConnell, John J., 2003. "International Corporate Governance," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 38(1), pages 1-36, March.
    17. Riza Emekter & Yanbin Tu & Benjamas Jirasakuldech & Min Lu, 2015. "Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 54-70, January.
    18. Muñoz, Fernando & Vargas, María & Vicente, Ruth, 2014. "Fund flow bias in market timing skill. Evidence of the clientele effect," International Review of Economics & Finance, Elsevier, vol. 33(C), pages 257-269.
    19. Aboody, David & Even-Tov, Omri & Lehavy, Reuven & Trueman, Brett, 2018. "Overnight Returns and Firm-Specific Investor Sentiment," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(2), pages 485-505, April.
    20. Xuanjuan Chen & Jing-Zhi Huang & Zhenzhen Sun & Tong Yao & Tong Yu, 2020. "Liquidity Premium in the Eye of the Beholder: An Analysis of the Clientele Effect in the Corporate Bond Market," Management Science, INFORMS, vol. 66(2), pages 932-957, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xin, Xinyi & Zhang, Anquan & Liu, Lu, 2024. "Study on the influence of Internet finance on urban household savings rate: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 45-61.
    2. Caglayan, Mustafa & Talavera, Oleksandr & Xiong, Lin, 2022. "Female small business owners in China: Discouraged, not discriminated," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    3. Righi, Riccardo & Pedrazzoli, Alessia & Righi, Simone & Venturelli, Valeria, 2024. "The clientele effects in equity crowdfunding: A complex network analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 42(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Rongda & Wu, Ling & Jin, Chenglu & Wang, Shengnan, 2021. "Unintended investor sentiment on bank financial products: Evidence from China," Emerging Markets Review, Elsevier, vol. 49(C).
    2. Chen, Rongda & Bao, Weiwei & Jin, Chenglu, 2021. "Investor sentiment and predictability for volatility on energy futures Markets: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 112-129.
    3. Han, Yufeng & Huang, Dashan & Huang, Dayong & Zhou, Guofu, 2022. "Expected return, volume, and mispricing," Journal of Financial Economics, Elsevier, vol. 143(3), pages 1295-1315.
    4. Chen, Rongda & Yu, Jingjing & Jin, Chenglu & Bao, Weiwei, 2019. "Internet finance investor sentiment and return comovement," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 151-161.
    5. Bouteska, Ahmed & Kabir Hassan, M. & Gider, Zeynullah & Bataineh, Hassan, 2024. "The role of investor sentiment and market belief in forecasting V-shaped disposition effect: Evidence from a Bayesian learning process with DSSW model," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    6. Chen, Rongda & Wang, Shengnan & Ye, Mengya & Jin, Chenglu & Ren, He & Chen, Shu, 2022. "Cross-Market Investor Sentiment of Energy Futures and Return Comovements," Finance Research Letters, Elsevier, vol. 49(C).
    7. Mbarki, Imen & Omri, Abdelwahed & Naeem, Muhammad Abubakr, 2022. "From sentiment to systemic risk: Information transmission in Asia-Pacific stock markets," Research in International Business and Finance, Elsevier, vol. 63(C).
    8. Mahmoudi, Nader & Docherty, Paul & Melia, Adrian, 2022. "Firm-level investor sentiment and corporate announcement returns," Journal of Banking & Finance, Elsevier, vol. 144(C).
    9. Konstantinos Gkillas & Rangan Gupta & Chi Keung Marco Lau & Muhammad Tahir Suleman, 2020. "Jumps beyond the realms of cricket: India's performance in One Day Internationals and stock market movements," Journal of Applied Statistics, Taylor & Francis Journals, vol. 47(6), pages 1109-1127, April.
    10. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2021. "Stock Market’s responses to intraday investor sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    11. Shah, Syed Faisal & Albaity, Mohamed, 2022. "The role of trust, investor sentiment, and uncertainty on bank stock return performance: Evidence from the MENA region," The Journal of Economic Asymmetries, Elsevier, vol. 26(C).
    12. Guofu Zhou, 2018. "Measuring Investor Sentiment," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 239-259, November.
    13. Reis, Pedro Manuel Nogueira & Pinho, Carlos, 2020. "A new European investor sentiment index (EURsent) and its return and volatility predictability," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    14. Zachary McGurk & Adam Nowak & Joshua C. Hall, 2020. "Stock returns and investor sentiment: textual analysis and social media," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(3), pages 458-485, July.
    15. Chen, Rongda & Wei, Bo & Jin, Chenglu & Liu, Jia, 2021. "Returns and volatilities of energy futures markets: Roles of speculative and hedging sentiments," International Review of Financial Analysis, Elsevier, vol. 76(C).
    16. Hwang, Soosung & Rubesam, Alexandre & Salmon, Mark, 2021. "Beta herding through overconfidence: A behavioral explanation of the low-beta anomaly," Journal of International Money and Finance, Elsevier, vol. 111(C).
    17. Soosung Hwang & Youngha Cho & Jinho Shin, 2020. "The impact of UK household overconfidence in public information on house prices," Journal of Property Research, Taylor & Francis Journals, vol. 37(4), pages 360-389, October.
    18. Sang Ik Seok & Hoon Cho & Chanhi Park & Doojin Ryu, 2019. "Do Overnight Returns Truly Measure Firm-Specific Investor Sentiment in the KOSPI Market?," Sustainability, MDPI, vol. 11(13), pages 1-14, July.
    19. Chen, Zhenxi & Lien, Donald & Lin, Yaheng, 2021. "Sentiment: The bridge between financial markets and macroeconomy," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1177-1190.
    20. Zhou, Xuemei & Liu, Qiang & Guo, Shuxin, 2021. "Do overnight returns explain firm-specific investor sentiment in China?," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 451-477.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:intfin:v:76:y:2022:i:c:s1042443121001682. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/intfin .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.