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| Title: | 低波動策略的條件績效分析 - 以美國為例
The Conditional Performance of Low Volatility Strategies in the US |
| Authors: | 黃曼如
Huang, Man-Ru |
| Contributors: | 鍾令德
黃曼如
Huang, Man-Ru |
| Keywords: | 低波動策略
低波動度異常現象
Low Volatility Strategies
Low Volatility Anomaly |
| Date: | 2021 |
| Issue Date: | 2021-07-01 16:18:45 (UTC+8) |
| Abstract: | 由於中美貿易戰持續加劇、英國脫歐和全球央行利率變化的不確定性，2019年起全球經濟成長放緩。而 2020 年初開始新型冠狀病毒肆虐，進而影響全球經濟走勢，投資者開始關注於低風險的投資標的。根據資本資產定價模型(CAPM)，低波動策略的報酬率應低於其他高風險投資商品，但在市場風險變高時，低波動策略應可當作避險的投資工具。因此，本文將探討低波動策略在高市場風險下的表現，並與同期的高波動策略作比較。研究對象為 CRSP 資料庫，包含美國證券交易所(American Stock Exchange, AMEX)、紐約證券交易所(New York Stock Exchange, NYSE)及那斯達克證券交易所(Nasdap Stock Exchange, NASDAQ)之上市股票。根據研究樣本中的數據，高風險時期包括亞洲金融風暴(1997)、網路泡沫(2000)、次貸金融海嘯(2008)、新冠肺炎(2020)。本文將利用回測及迴歸進行檢定與分析，從而探討在經濟不景氣期間是否存在低波動度異常現象(Low Volatility Anomaly)，並會透過與市場波動度比較，檢視低波動度投資組合是否有避險功能。
Since 2019, the global economic growth has slowed down, because of the international trade dispute, Brexit, and the uncertainty of global monetary policies. To make matters worse, the outbreak of the COVID-19 in early 2020 has severely disrupted the global economy. According to the capital asset pricing model, investors should receive higher expected return for bearing more systematic risk. Therefore, low volatility strategies should have lower expected returns than their high-risk counterparts. But in periods of market turbulences, low volatility strategies may be more resilience and thus offer better risk-adjusted returns to investors. In this article, I form low volatility strategies using stocks traded on the NYSE, AMEX and NASDAQ and study their conditonal performance versus their high volatility counterparts amid four volatile periods including the Asian financial crisis (1997), the Internet bubble (2000), the
Subprime mortgage crisis (2008), and the COVID-19 (2020). Specifically, I conduct back-testing and regression analysis to study whether low volatility strategies outperform relative to other factors during high volatility periods. |
| Reference: | [1] Alighanbari, M., Doole, S., and Shankar, D. (2016). Designing Low-Volatility Strategies. The Journal of Index Investing, 7(3), 21-33.
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[3] Baker, M., Bradley, B., and Wurgler J. (2011). Benchmarks as Limits to Arbitrage: Understanding the Low-Volatility Anomaly. Financial Analysts Journal, 67(1), 40-54.
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[5] Blitz, D., and Vidojevic, M. (2017). The profitability of low-volatility. Journal of Empirical Finance, vol. 43(C), 33-42.
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[19] Treynor, J. L. (1962). Asset Pricing and Portfolio Performance: Models, Strategy and Performance Metrics. London, Risk Books. p15-22.
網際網路
[20] CBOE Staff. (2019). Whitepaper : Cboe Volatility Index. Retrieved from https://www.cboe.com/tradable_products/ (March 26, 2021).
[21] Kenneth R. French Data Library. Retrieved from http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ (March 12, 2020). |
| Description: | 碩士
國立政治大學
國際經營與貿易學系
108351032 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0108351032 |
| Data Type: | thesis |
| DOI: | 10.6814/NCCU202100536 |
| Appears in Collections: | [國際經營與貿易學系 ] 學位論文
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