Fundamental indexation: essays on stock mispricing, portfolio diversification, and rebalancing
Creators: name: Shi, Xiaofeng
Publisher: name: Monash University
Year: 2017
Subjects: Uncategorized

description: Using stocks from the Russell 1000 Index from 1974 to 2010, this thesis conducts three studies in relation to the indexation technique known as fundamental indexation (FI). The first study advances mispricing as an explanation for FI’s outperformance over alternative benchmark indexation techniques, namely, capitalization-weighted indexation (CWI), equally weighted indexation (EWI), and price-weighted indexation (PWI). The second study investigates the effectiveness of FI in relation to the benchmark indexation techniques as a function of portfolio size (number of stocks). The third study develops a market volatility-based rebalancing strategy. More specifically, in this study, our market volatility-based rebalancing strategy responds only when the market enters a volatile cycle, unlike rebalancing on a calendar basis. We compare returns, risk, and risk-adjusted returns both before and after consideration of transaction costs. The results of the first study reveal how FI is able to take advantage of stock mispricing to outperform the alternative benchmark indexation techniques considered in this thesis. Specifically, we find that FI outperforms the alternative benchmark portfolios (i) when the portfolio stocks are tilted toward small-cap stocks and (ii) when the market is volatile. We confirm a close linkage between FI portfolio returns and the Fama–French three-factor model. We demonstrate that FI relies on value stocks to generate higher returns and on large stocks to reduce portfolio risks. Finally, we provide evidence that book to market and small firm size effects can be attributed to mispricing. Thus, controversially, rather than argue that FI represents a repackaging of value and size factors, we argue that these factors are at least partly the outcome of stock mispricing. The results of the second study reveal how the benefits of diversification as a function of the number of stocks are differentiated across the various indexation approaches adopted. Specifically, our findings determine how significantly lower idiosyncratic risk and higher risk-adjusted returns can be achieved by increasing portfolio size. While the majority of diversification benefits are acquired 8 with fewer than 200 stocks for EWI portfolios, additional stocks are required for the alternative non-EWI portfolios. CWI, PWI, and FI portfolios require 600, 300, and 400 stocks, respectively, to extract similar diversification benefits as EWI portfolios with 200 stocks. The results of our third study reveal that a market volatility-based rebalancing strategy as developed in this thesis allows FI portfolios to continue to outperform, with significantly lower turnover and subsequently lower transaction costs. Specifically, when return, risk, and transaction costs are assessed in combination, our market volatility-based rebalancing strategy significantly outperforms alternative calendar-based rebalancing strategies, including monthly rebalancing, quarterly rebalancing, and annual rebalancing strategies. We conclude that a market volatility-based rebalancing strategy has the potential to improve portfolio performance from a practical (transaction cost) perspective. As a whole, this thesis provides new insights on how to construct and manage index tracking funds based on FI, as well as on alternative indexation techniques. The first study presents the underlying foundations for FI’s success, as well as informs the fund manager about the optimal application of FI in regard to both (i) optimal stock characteristics and (ii) optimal market conditions. The second study informs the fund manager about the optimal number of stocks in the risk–return relation. The third study provides fund managers an alternative to traditional calendar portfolio rebalancing that is effective in reducing transaction costs without compromising on returns and risks.