An Examination of Portfolio Strategies and Risk

投資組合策略與風險研究

Student thesis: Doctoral Thesis

View graph of relations

Author(s)

Related Research Unit(s)

Detail(s)

Awarding Institution
Supervisors/Advisors
Award date3 Oct 2024

Abstract

Existing studies highlight an upward trend in idiosyncratic volatility (IVOL) over recent decades (e.g., Campbell et al., 2001). In light of changing investment opportunities, investors often struggle to achieve adequate diversification to mitigate this increase in volatility. Consequently, the efficacy of strategies for managing risk, the behavior of IVOL trends, and the relationship between IVOL and expected returns have received significant attention. This thesis contributes to these areas through three studies. First, we compare three investment strategies: Dollar Cost Averaging (DCA), Lump Sum, and Rebalancing, across three performance metrics, using both simulations and empirical analyses. While Lump Sum may offer a higher average rate of return, it often exhibits greater variance in volatile markets. In contrast, both DCA and Rebalancing strategies mitigate risk by sacrificing some returns, leading to higher overall utility. Second, we document stylized facts about idiosyncratic volatility in the U.S. and Chinese markets over the past two decades. We find no clear increase in IVOL in the U.S. market; however, in the Chinese market, IVOL exhibits a noticeable upward trend relative to market volatility. This trend has led to a decline in correlations among individual stocks and reduced diversification in portfolios with a fixed number of stocks in the Chinese market. Third, we explore the relationship between idiosyncratic volatility and expected returns in the Chinese market. We identify a persistent negative relationship between IVOL and expected returns, even after accounting for cross-sectional factors. Decomposing total returns into intraday and overnight returns reveals significant but opposing relationships with IVOL, suggesting that this overall negative correlation may be driven by differing investor behaviors over time.