股票收益影響因素的實證研究 - 來自美國市場證據
Factors Affecting Stock Returns - Evidence from the U.S. Market
Student thesis: Doctoral Thesis
Author(s)
Related Research Unit(s)
Detail(s)
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| Award date | 27 May 2020 |
Link(s)
| Permanent Link | https://scholars.cityu.edu.hk/en/theses/theses(520b859c-1a36-41a9-9413-dd3937ffd8fc).html |
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| Other link(s) | Links |
Abstract
資本資產的定價，尤其是涉及股票或投資組合的收益問題，是學術界、投資界都熱衷研究的核心問題，特別是在當下人工智能、量化交易風起雲湧的背景下更是備受關注。
本文緣起著名經濟學家凱恩斯（John Maynard Keynes）對股票收益來源的定義，笔者通過分析該定義而構建了股票收益的理論函數，從該函數中本文獲得了影響股票收益的四個重要變量——ROE（淨資產收益率）、PB（市淨率）、PE（市盈率）、DPR（分紅率）。同時，根據該理論函數和變量，本文提出了與股票收益相關的五個假設。
為證明該假設，本文選取了1965年至2017年美國WRDS（Wharton Research Data Services）數據庫、沃頓商學院Crsp數據庫和Compustat數據庫，研究的對象為NYSE、NASDAQ、AMEX三大交易所數千家上市公司。在研究方法上，本文採用了變量獨立分組方法、Fama-Macbeth 回歸，Fama-French三因子模型，以及Carhart四因子模型，對ROE、PB、PE、DPR四個因素進行比較分析，統計分析了1年期、5年期、10年期、20年期四個不同時間週期的投資組合收益，獲得了較為全面、系統、重要的如下結論：
（1）長期來看，ROE對股票收益呈正相關，ROE高的公司比ROE低的公司，股票的收益更大；（2）在ROE相同分組內，市盈率（PE）因素對股票收益呈負相關，低市盈率比高市盈率的股票收益更大；（3）在ROE相同分組內，市淨率（PB）因素對股票收益呈負相關，低市淨率比高市淨率的股票收益更大；（4）分紅率（DPR）對股票收益的相關性並不顯著；（5）長期來看，市場因素（PE、PB）對股票收益的影響較小，基本面數據ROE的影響較大。
最後，該結論通過了加權平均法、非獨立分組以及Carhart四因子模型的穩健性檢驗。
本文構建的四因素模型揭示了股票或投資組合收益的主要來源因素（變量），能說明投資者厘定投資的本質邏輯。從研究的結果來看，重點突出了ROE對股票收益影響這一核心因素，而且對PB、PE因素對投資組合收益的貢獻進行了量化分析。
本文還有以下重要研究發現：ROE對投資組合收益的解釋力度為60-70%，PB對投資組合的收益解釋力度為15-20%左右，PE對投資組合的收益解釋力度僅為5-6%左右。ROE、PB、PE三個因素構建的回歸方程，擬合優度超過了80%，是目前所有文獻中擬合優度较高的。
總之，本文通過理論推導，構建股票收益來源的模型，獲得與股票收益相關的四個變量，並提出五個重要假設，探討了股票收益的本質和來源，為投資者的交易策略、投資組合、量化交易、人工智能交易等提供了基礎方法和理論支持，為投資者更好地理解證券市場的定價行為，更有效地制定投資策略提供了理論指導和決策依據。
本文緣起著名經濟學家凱恩斯（John Maynard Keynes）對股票收益來源的定義，笔者通過分析該定義而構建了股票收益的理論函數，從該函數中本文獲得了影響股票收益的四個重要變量——ROE（淨資產收益率）、PB（市淨率）、PE（市盈率）、DPR（分紅率）。同時，根據該理論函數和變量，本文提出了與股票收益相關的五個假設。
為證明該假設，本文選取了1965年至2017年美國WRDS（Wharton Research Data Services）數據庫、沃頓商學院Crsp數據庫和Compustat數據庫，研究的對象為NYSE、NASDAQ、AMEX三大交易所數千家上市公司。在研究方法上，本文採用了變量獨立分組方法、Fama-Macbeth 回歸，Fama-French三因子模型，以及Carhart四因子模型，對ROE、PB、PE、DPR四個因素進行比較分析，統計分析了1年期、5年期、10年期、20年期四個不同時間週期的投資組合收益，獲得了較為全面、系統、重要的如下結論：
（1）長期來看，ROE對股票收益呈正相關，ROE高的公司比ROE低的公司，股票的收益更大；（2）在ROE相同分組內，市盈率（PE）因素對股票收益呈負相關，低市盈率比高市盈率的股票收益更大；（3）在ROE相同分組內，市淨率（PB）因素對股票收益呈負相關，低市淨率比高市淨率的股票收益更大；（4）分紅率（DPR）對股票收益的相關性並不顯著；（5）長期來看，市場因素（PE、PB）對股票收益的影響較小，基本面數據ROE的影響較大。
最後，該結論通過了加權平均法、非獨立分組以及Carhart四因子模型的穩健性檢驗。
本文構建的四因素模型揭示了股票或投資組合收益的主要來源因素（變量），能說明投資者厘定投資的本質邏輯。從研究的結果來看，重點突出了ROE對股票收益影響這一核心因素，而且對PB、PE因素對投資組合收益的貢獻進行了量化分析。
本文還有以下重要研究發現：ROE對投資組合收益的解釋力度為60-70%，PB對投資組合的收益解釋力度為15-20%左右，PE對投資組合的收益解釋力度僅為5-6%左右。ROE、PB、PE三個因素構建的回歸方程，擬合優度超過了80%，是目前所有文獻中擬合優度较高的。
總之，本文通過理論推導，構建股票收益來源的模型，獲得與股票收益相關的四個變量，並提出五個重要假設，探討了股票收益的本質和來源，為投資者的交易策略、投資組合、量化交易、人工智能交易等提供了基礎方法和理論支持，為投資者更好地理解證券市場的定價行為，更有效地制定投資策略提供了理論指導和決策依據。
Assets pricing, especially the expected returns of stocks or investment portfolios, is the core issue that academics and investment communities are keen to study, especially in the context of the current surge of artificial intelligence and quantitative trading.
This article originates from the definition of the source of stock returns by John Maynard Keynes, and builds a theoretical function of stock returns based on that definition. From this function, this article obtains four important variables that affect expected stock returns: ROE (Return on net assets), PB (price-to-book ratio), PE (price-earnings ratio) and DPR (dividend ratio). At the same time, based on the theoretical functions and variables, this paper proposes five hypotheses related to expected returns.
In order to prove these hypotheses, we use the US WRDS (Wharton Research Data Services) database, the Wharton Business School Crsp database, and the Compustat database. Our sample includes thousands of listed companies on the three major exchanges of NYSE, NASDAQ and AMEX for the period 1965 to 2017. We conducts independent sort analysis, Fama-Macbeth regression, Fama-French three-factor model, and Carhart four-factor model to analyze the explanatory power of ROE, PB, PE and DPR to expected stock returns. We study the portfolio returns of four different time periods of 1 year, 5 years, 10 years, and 20 years. The main conclusions are as follows :
(1) In the long run, ROE has a positive correlation with expected returns. Companies with high ROE have greater expected returns than companies with low ROE. (2) Given ROE, higher PE rations and PB ratios imply lower expected returns. (3) In the same ROE group, PB ratios have a negative correlation to expected returns. Firms with lower PB ratios have greater returns; (4) the explanatory power of DPR to expected stock returns is not significant; (5) In the long run, PE ratios and PB ratios have a small impact on expected stock returns, while ROE has a greater impact. Finally, the conclusion passes the robustness test of weighted average method, dependent sort analysis and Carhart four-factor model.
The four-factor model constructed in this article reveals the main source of stock or portfolio returns, which can help investors understand the essential logic of investment. Our study highlights the impact of ROE on expected stock returns and analysis the explanatory power of PB ratios and PE ratios to expected returns.
The important results of this study show: The explanatory power of ROE is 60-70%, the explanatory power of PB is about 15-20%, while PE ratio can only explain 5-6% of the deviations in excepted returns. The model constructed by the three factors of ROE, PB, and PE has a R^2 of more than 80%.
In short, this paper constructs a model which contains the source of expected stock returns through theoretical derivation, obtains four variables related to expected returns, and proposes five important hypotheses. This study explores the nature and source of expected returns, which provides basic methods and theoretical support for investors' trading strategies, investment portfolios, quantitative trading, artificial intelligence trading, etc., and provides investors with a theoretical guidance and a better understanding of the asset pricing.
This article originates from the definition of the source of stock returns by John Maynard Keynes, and builds a theoretical function of stock returns based on that definition. From this function, this article obtains four important variables that affect expected stock returns: ROE (Return on net assets), PB (price-to-book ratio), PE (price-earnings ratio) and DPR (dividend ratio). At the same time, based on the theoretical functions and variables, this paper proposes five hypotheses related to expected returns.
In order to prove these hypotheses, we use the US WRDS (Wharton Research Data Services) database, the Wharton Business School Crsp database, and the Compustat database. Our sample includes thousands of listed companies on the three major exchanges of NYSE, NASDAQ and AMEX for the period 1965 to 2017. We conducts independent sort analysis, Fama-Macbeth regression, Fama-French three-factor model, and Carhart four-factor model to analyze the explanatory power of ROE, PB, PE and DPR to expected stock returns. We study the portfolio returns of four different time periods of 1 year, 5 years, 10 years, and 20 years. The main conclusions are as follows :
(1) In the long run, ROE has a positive correlation with expected returns. Companies with high ROE have greater expected returns than companies with low ROE. (2) Given ROE, higher PE rations and PB ratios imply lower expected returns. (3) In the same ROE group, PB ratios have a negative correlation to expected returns. Firms with lower PB ratios have greater returns; (4) the explanatory power of DPR to expected stock returns is not significant; (5) In the long run, PE ratios and PB ratios have a small impact on expected stock returns, while ROE has a greater impact. Finally, the conclusion passes the robustness test of weighted average method, dependent sort analysis and Carhart four-factor model.
The four-factor model constructed in this article reveals the main source of stock or portfolio returns, which can help investors understand the essential logic of investment. Our study highlights the impact of ROE on expected stock returns and analysis the explanatory power of PB ratios and PE ratios to expected returns.
The important results of this study show: The explanatory power of ROE is 60-70%, the explanatory power of PB is about 15-20%, while PE ratio can only explain 5-6% of the deviations in excepted returns. The model constructed by the three factors of ROE, PB, and PE has a R^2 of more than 80%.
In short, this paper constructs a model which contains the source of expected stock returns through theoretical derivation, obtains four variables related to expected returns, and proposes five important hypotheses. This study explores the nature and source of expected returns, which provides basic methods and theoretical support for investors' trading strategies, investment portfolios, quantitative trading, artificial intelligence trading, etc., and provides investors with a theoretical guidance and a better understanding of the asset pricing.
