政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/141054

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/141054

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政大典藏 > College of Commerce > Department of Money and Banking > Theses > Item 140.119/141054

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/141054

Title:	企業ESG評分對其股價連動效應以及ESG投資策略之探討 Discussion on the co-movement effect of corporate ESG scores on its stock price and the performance of ESG investment strategy
Authors:	陳信全 Chen, Hsin-Chuan
Contributors:	楊曉文 Yang, Sheau-Wen 陳信全 Chen, Hsin-Chuan
Keywords:	連動性共整合 ESG Co-movement Co-integration ESG
Date:	2022
Issue Date:	2022-08-01 17:27:26 (UTC+8)
Abstract:	近幾年ESG的興起及國際之間永續規範制定，使得ESG投資逐漸成為一種偏好。許多研究已經探討ESG投資組合績效相關議題，但其結果仍不一致。產生不同結果可能為其中兩個原因，一為企業投入ESG後回報期間效果較長，無法在短期當中顯現。另一原因為在現行規範下，ESG投資容易有過度集中而無法充分分散投資組合風險的可能。因此本研究論文採用Bloomberg資料庫ESG分數進行ESG投資組合構建，並使用共整合方法設計連動性集中度，依此建構出相互連動（MC）與非相互連動（NMC）的投資組合族群。研究樣本以2007-2017年美國S&P 500成分股為例，透過ESG資料取得的滯後性搭配共整合檢定，檢驗2010-2020年的投資組合報酬績效是否有較佳的長期報酬。實證結果顯示，ESG Good族群相對ESG Bad族群擁有較高的連動性集中度，並且在ESG連動性投資組合上，ESG Good族群其特雷諾比率（TR）低於ESG Bad族群，代表ESG Good 族群MC的投資組合承擔較高的系統性風險。另外，在NMC的投資組合下，ESG連動性投資組合上績效指標皆優於MC，表示未受關注的股票池確實擁有較高的績效，其中又以ESG Good族群差異最為明顯，表示ESG Good族群相對ESG Bad族群在市場上的期望與需求較高，資訊成本效應下改善其績效表現。最後，透過共整合應用多空策略於連動性投資組合上，ESG整體組合達至Fama-French五因子的5%顯著Alpha，其主要效應來自MC的負向效果，在NMC的投資組合上可能需增加額外的因素考量來獲得顯著Alpha。 In recent years, ESG investing has gradually become an investment style preference. While many studies have explored the issue of ESG and performance, the results have remained inconsistent. There are two possible reasons for this: At first, company invests in ESG for a long-term to return, which cannot be manifested in the short-term. Another reason is that under the current norms, ESG investment is easy to be too concentrated and unable to fully diversify the risk of the portfolio. Therefore, this study uses the Bloomberg ESG score to construct ESG portfolios, and uses the co-integration approach to design co-movement density (CD), thereby constructing the mutual co-movement (MC) and no mutual co-movement (NMC) portfolio groups. The research sample takes the US S&P 500 constituent stocks from 2007 to 2017 as an example, and tests whether the portfolio has better long-tern performance from 2010 to 2020. The empirical results show that the ESG Good group has a higher CD than the ESG Bad group. In the ESG MC portfolio, the Treynor ratio of the ESG Good group is lower than that of the ESG Bad group, representing the portfolio of the ESG Good group MC have higher systemic risk. In addition, under NMC`s portfolio, the performance indicators of ESG co-movement portfolios are all better than MC`s, indicating that the stock pools that have not received attention do have higher performance. Finally, through the co-integration to create long-short strategies portfolio, the ESG_All portfolio has achieved a 5% significant Alpha of the Fama-French five factors model. However, its main effect comes from the negative effect of MC. Therefore, need to other factors to obtain a significant alpha to NMC portfolio.
Reference:	Anton, M., & Polk, C. (2014). Connected Stocks. Journal of Finance, 69(3), 1099-1127. https://doi.org/10.1111/jofi.12149 Amon, J., Rammerstorfer, M., & Weinmayer, K. (2021). Passive ESG Portfolio Management—The Benchmark Strategy for Socially Responsible Investors. Sustainability, 13(16), 9388. https://www.mdpi.com/2071-1050/13/16/9388 Barberis, N., & Shleifer, A. (2003). Style investing. Journal of Financial Economics, 68(2), 161-199. https://doi.org/10.1016/s0304-405x(03)00064-3 Barberis, N., Shleifer, A., & Wurgler, J. (2005). Comovement. Journal of Financial Economics, 75(2), 283-317. https://doi.org/10.1016/j.jfineco.2004.04.003 Black, F. (1972). CAPITAL MARKET EQUILIBRIUM WITH RESTRICTED BORROWING. Journal of Business, 45(3), 444-455. https://doi.org/10.1086/295472 Boginski, V., Butenko, S., & Pardalos, P. M. (2006). Mining market data: A network approach. Computers & Operations Research, 33(11), 3171-3184. https://doi.org/10.1016/j.cor.2005.01.027 Brav, A., & Lehavy, R. (2003). An empirical analysis of analysts` target prices: Short-term informativeness and long-term dynamics. Journal of Finance, 58(5), 1933-1967. https://doi.org/10.1111/1540-6261.00593 Cerqueti, R., Ciciretti, R., Dalò, A., & Nicolosi, M. (2021). ESG investing: A chance to reduce systemic risk. Journal of Financial Stability, 54, 100887. https://doi.org/10.1016/j.jfs.2021.100887 Dunis, C. L., & Ho, R. (2005). Cointegration portfolios of European equities for index tracking and market neutral strategies. Journal of Asset Management, 6(1), 33-52. Ehrmann, M., & Jansen, D.-J. (2020). Stock Return comovement when investors are distracted: More, and more homogeneous. Engle, R. F., & Granger, C. W. J. (1987). COINTEGRATION AND ERROR CORRECTION - REPRESENTATION, ESTIMATION, AND TESTING. Econometrica, 55(2), 251-276. https://doi.org/10.2307/1913236 Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22. https://doi.org/10.1016/j.jfineco.2014.10.010 Friede, G., Busch, T., & Bassen, A. (2015). ESG and financial performance: aggregated evidence from more than 2000 empirical studies. Journal of Sustainable Finance & Investment, 5(4), 210-233. Galenko, A., Popova, E., & Popova, I. (2012). Trading in the presence of cointegration. The Journal of Alternative Investments, 15(1), 85-97. Granger, C. W. J. (1981). SOME PROPERTIES OF TIME-SERIES DATA AND THEIR USE IN ECONOMETRIC-MODEL SPECIFICATION. Journal of Econometrics, 16(1), 121-130. https://doi.org/10.1016/0304-4076(81)90079-8 Greenwood, R. (2008). Excess comovement of stock returns: Evidence from cross-sectional variation in Nikkei 225 weights. Review of Financial Studies, 21(3), 1153-1186. https://doi.org/10.1093/rfs/hhm052 Hameed, A., Morck, R., Shen, J. F., & Yeung, B. (2015). Information, Analysts, and Stock Return Comovement. Review of Financial Studies, 28(11), 3153-3187. https://doi.org/10.1093/rfs/hhv042 Huang, W.-Q., Zhuang, X.-T., & Yao, S. (2009). A network analysis of the Chinese stock market. Physica A: Statistical Mechanics and its Applications, 388(14), 2956-2964. https://doi.org/10.1016/j.physa.2009.03.028 Lintner, J. (1965). THE VALUATION OF RISK ASSETS AND THE SELECTION OF RISKY INVESTMENTS IN STOCK PORTFOLIOS AND CAPITAL BUDGETS. Review of Economics and Statistics, 47(1), 13-37. https://doi.org/10.2307/1924119 Majapa, M., & Gossel, S. J. (2016). Topology of the South African stock market network across the 2008 financial crisis. Physica A-statistical Mechanics and Its Applications, 445, 35-47. Mantegna, R. N. (1999). Hierarchical structure in financial markets. The European Physical Journal B - Condensed Matter and Complex Systems, 11(1), 193-197. https://doi.org/10.1007/s100510050929 Markowitz, H. (1952). PORTFOLIO SELECTION. Journal of Finance, 7(1), 77-91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x Naffa, H., & Fain, M. (2022). A factor approach to the performance of ESG leaders and laggards. Finance Research Letters, 44, 102073. https://doi.org/10.1016/j.frl.2021.102073 Obrien, P. C., & Bhushan, R. (1990). ANALYST FOLLOWING AND INSTITUTIONAL OWNERSHIP. Journal of Accounting Research, 28, 55-76. https://doi.org/10.2307/2491247 Pindyck, R. S., & Rotemberg, J. J. (1993). THE COMOVEMENT OF STOCK-PRICES. Quarterly Journal of Economics, 108(4), 1073-1104. https://doi.org/10.2307/2118460 Sharpe, W. F. (1964). CAPITAL-ASSET PRICES - A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK. Journal of Finance, 19(3), 425-442. https://doi.org/10.2307/2977928 Stock, J. H., & Watson, M. W. (1993). A SIMPLE ESTIMATOR OF COINTEGRATING VECTORS IN HIGHER ORDER INTEGRATED SYSTEMS. Econometrica, 61, 783-820. Tse, C. K., Liu, J., & Lau, F. C. M. (2010). A network perspective of the stock market. Journal of Empirical Finance, 17(4), 659-667. https://doi.org/10.1016/j.jempfin.2010.04.008 Tu, C. (2014). Cointegration-based financial networks study in Chinese stock market. Physica A-statistical Mechanics and Its Applications, 402, 245-254. Tumminello, M., Di Matteo, T., Aste, T., & Mantegna, R. N. (2007). Correlation based networks of equity returns sampled at different time horizons. The European Physical Journal B, 55(2), 209-217. https://doi.org/10.1140/epjb/e2006-00414-4 Veldkamp, L. L. (2006). Information markets and the comovement of asset prices. Review of Economic Studies, 73(3), 823-845. https://doi.org/10.1111/j.1467-937X.2006.00397.x Vijh, A. M. (1994). STANDARD-AND-POOR-500 TRADING STRATEGIES AND STOCK-BETAS. Review of Financial Studies, 7(1), 215-251. https://doi.org/10.1093/rfs/7.1.215 Wang, L., & Maxfield, S. (2018). The Impact of Socially Responsible Investing: What Can We Learn from Different Performance Measures? Unpublished Dissertation. School of Business, Providence College, IN. USA. Yu, J.-W., Xie, W.-J., & Jiang, Z.-Q. (2018). Early warning model based on correlated networks in global crude oil markets. Physica A: Statistical Mechanics and its Applications, 490, 1335-1343.
Description:	碩士國立政治大學金融學系 108352006
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0108352006
Data Type:	thesis
DOI:	10.6814/NCCU202200731
Appears in Collections:	[Department of Money and Banking] Theses

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