English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 112721/143689 (78%)
Visitors : 49588044      Online Users : 753
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 財務管理學系 > 學位論文 >  Item 140.119/146294
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/146294


    Title: 下行風險是否能解釋橫斷面報酬:以加密貨幣市場為例
    Can downside risk explain the cross-section of cryptocurrency returns?
    Authors: 林冠宇
    Lin, Kuan-Yu
    Contributors: 岳夢蘭
    Yueh, Meng-Lan
    林冠宇
    Lin, Kuan-Yu
    Keywords: 加密貨幣
    下行風險
    情緒
    關注度
    Cryptocyrrency
    Downside risk
    Sentiment
    Attention
    Date: 2023
    Issue Date: 2023-08-02 13:01:17 (UTC+8)
    Abstract: 本文使用風險價值(Value at Risk)衡量個別加密貨幣的下行風險,並闡述了下行風險與橫斷面報酬的正向關係,在單變量投資組合分析、雙變量投資組合分析下的長短策略皆顯著為正,並且在使用三因子模型(Liu et al., 2022)進行風險調整後依然顯著為正。此外,本文使用Fama and MacBeth (1973)迴歸發現在個別貨幣的下行風險特徵與未來報酬具有顯著橫斷面關係。研究結果顯示橫斷面上,下行風險會被加密貨幣市場定價。另外,本文使用全樣本資料並控制貨幣、時間效果後,亦發現下行風險與未來報酬存在跨期關係(Intertemporal relation)。
    本文的額外研究發現股市情緒、加密貨幣關注度對於下行風險具有解釋能力,並且加密貨幣關注度在短、中長期的影響方向相反。本文分別使用Barber and Odean (2007)的關注度理論、Baker and Wurgler (2006)的情緒研究結果進行解釋,並且發現情緒假說能在中長期解釋本文的實證結果,而關注度理論則皆能解釋。
    In this paper, we use Value at Risk as a measure to downside risk, and discuss the positive relationship between downside risk and cross-sectional returns. We find that in both univariate and bivariate portfolio analyses, long and short strategies exhibit a significant positive relationship. Even after adjusting for risk using the three-factor model(Liu et al., 2022), this positive relationship remains significant. Furthermore, employing the Fama and MacBeth (1973) regression, we discover a significant cross-sectional relationship between the downside risk characteristics of individual currencies and future returns. The research results suggest that downside risk is priced in the cryptocurrency market at the cross-sectional level. Additionally, when we analyze the full sample data while controlling for entity and time effects, we also find a cross-period relationship (intertemporal relation) between downside risk and future returns.
    Moreover, our additional research reveals that stock market sentiment and cryptocurrency attention have explanatory power for downside risk. Interestingly, the impact of cryptocurrency attention on downside risk differs in the short and medium to long term. We employ the attention theory proposed by Barber and Odean (2007) and the sentiment research findings of Baker and Wurgler (2006) to explain these results. We find that the sentiment hypothesis can explain the empirical findings in the medium to long term, while the attention theory is able to explain them consistently.
    Reference: Al Guindy, M. (2021). Cryptocurrency price volatility and investor attention. International Review of Economics & Finance, 76, 556-570.
    Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal of Financial Markets, 5(1), 31-56.
    Anamika, Chakraborty, M., & Subramaniam, S. (2023). Does Sentiment Impact Cryptocurrency? Journal of Behavioral Finance, 24(2), 202-218.
    Ang, A., Chen, J., & Xing, Y. (2006). Downside Risk. The Review of Financial Studies, 19(4), 1191-1239.
    Atilgan, Y., Bali, T. G., Demirtas, K. O., & Gunaydin, A. D. (2020). Left-tail momentum: Underreaction to bad news, costly arbitrage and equity returns. Journal of financial economics, 135(3), 725-753.
    Bai, J., Bali, T. G., & Wen, Q. (2019). Common risk factors in the cross-section of corporate bond returns. Journal of financial economics, 131(3), 619-642.
    Baker, M., & Wurgler, J. (2006). Investor Sentiment and the Cross-Section of Stock Returns. The Journal of Finance, 61(4), 1645-1680.
    Bali, T. G., Demirtas, K. O., & Levy, H. (2009). Is There an Intertemporal Relation between Downside Risk and Expected Returns? The Journal of Financial and Quantitative Analysis, 44(4), 883-909.
    Barber, B. M., & Odean, T. (2007). All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors. The Review of Financial Studies, 21(2), 785-818.
    Baur, D. G., Hong, K., & Lee, A. D. (2018). Bitcoin: Medium of exchange or speculative assets? Journal of International Financial Markets, Institutions and Money, 54, 177-189.
    Borri, N. (2019). Conditional tail-risk in cryptocurrency markets. Journal of Empirical Finance, 50, 1-19.
    Conlon, T., & McGee, R. J. (2020). Betting on Bitcoin: Does gambling volume on the blockchain explain Bitcoin price changes? Economics Letters, 191, 108727.
    Corbet, S., Lucey, B., Urquhart, A., & Yarovaya, L. (2019). Cryptocurrencies as a financial asset: A systematic analysis. International Review of Financial Analysis, 62, 182-199.
    Da, Z., Engelberg, J., & Gao, P. (2011). In Search of Attention. The Journal of Finance, 66(5), 1461-1499.
    Dastgir, S., Demir, E., Downing, G., Gozgor, G., & Lau, C. K. M. (2019). The causal relationship between Bitcoin attention and Bitcoin returns: Evidence from the Copula-based Granger causality test. Finance Research Letters, 28, 160-164.
    Detzel, A., Liu, H., Strauss, J., Zhou, G., & Zhu, Y. (2021). Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard-to-value fundamentals. Financial Management, 50(1), 107-137.
    Fama, E. F., & MacBeth, J. D. (1973). Risk, Return, and Equilibrium: Empirical Tests. Journal of Political Economy, 81(3), 607-636.
    Harvey, C. R., & Siddique, A. (2000). Conditional Skewness in Asset Pricing Tests. The Journal of Finance, 55(3), 1263-1295.
    Li, Y., Urquhart, A., Wang, P., & Zhang, W. (2021). MAX momentum in cryptocurrency markets. International Review of Financial Analysis, 77, 101829.
    Liu, Y., & Tsyvinski, A. (2020). Risks and Returns of Cryptocurrency. The Review of Financial Studies, 34(6), 2689-2727.
    Liu, Y., Tsyvinski, A., & Wu, X. (2022). Common Risk Factors in Cryptocurrency. The Journal of Finance, 77(2), 1133-1177.
    Pelster, M., Breitmayer, B., & Hasso, T. (2019). Are cryptocurrency traders pioneers or just risk-seekers? Evidence from brokerage accounts. Economics Letters, 182, 98-100.
    Zhang, W., & Li, Y. (2020). Is idiosyncratic volatility priced in cryptocurrency markets? Research in International Business and Finance, 54, 101252.
    Zhang, W., & Li, Y. (2023). Liquidity risk and expected cryptocurrency returns. International Journal of Finance & Economics, 28(1), 472-492.
    Zhang, W., Li, Y., Xiong, X., & Wang, P. (2021). Downside risk and the cross-section of cryptocurrency returns. Journal of Banking & Finance, 133, 106246.
    Description: 碩士
    國立政治大學
    財務管理學系
    110357036
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0110357036
    Data Type: thesis
    Appears in Collections:[財務管理學系] 學位論文

    Files in This Item:

    File Description SizeFormat
    703601.pdf1529KbAdobe PDF216View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback