“…Recently, alternative index concepts aimed at better approximating true firm values have been proposed. These indices rely on smoothed cap weights (Chen et al (2007)) or are weighted by fundamental measures such as earnings, dividends or book values (Arnott et al (2005)). The intuition here is that a weighting scheme based on fundamentals might be less volatile and less driven by sentiment.…”
This study evaluates the out-of-sample performance of numerous asset allocation strategies from the perspective of a Euro zone investor. Besides an increased sample period from January 1973 to December 2008, our contribution to the literature is twofold. First, we compare the performance of a broad spectrum of heuristic portfolio policies with a large set of well-established model extensions of the Markowitz (1952) mean-variance framework. Second, we explicitly differentiate between two prominent ways of diversification that are usually analyzed separately: international diversification in the stock market and diversification over different asset classes. Our analysis allows us to compare and discuss different diversification strategies to construct a "world market portfolio" that is as ex-ante efficient as possible. For international equity diversification, we find that none of the Markowitz-based portfolio models is able to significantly outperform simple heuristics. Among those, the GDP weighting dominates the traditional cap-weighted approach. In the asset allocation case, Markowitz models are again not able to beat a broad spectrum of fixed-weight alternatives out-of-sample. Analyzing more than 5000 heuristics, we find that in fact almost any form of well-balanced allocation over asset classes offers similar diversification gains as even very sophisticated and recently developed portfolio optimization approaches. Based on our findings, we suggest a simple and cost-efficient allocation approach for private investors.
“…Recently, alternative index concepts aimed at better approximating true firm values have been proposed. These indices rely on smoothed cap weights (Chen et al (2007)) or are weighted by fundamental measures such as earnings, dividends or book values (Arnott et al (2005)). The intuition here is that a weighting scheme based on fundamentals might be less volatile and less driven by sentiment.…”
This study evaluates the out-of-sample performance of numerous asset allocation strategies from the perspective of a Euro zone investor. Besides an increased sample period from January 1973 to December 2008, our contribution to the literature is twofold. First, we compare the performance of a broad spectrum of heuristic portfolio policies with a large set of well-established model extensions of the Markowitz (1952) mean-variance framework. Second, we explicitly differentiate between two prominent ways of diversification that are usually analyzed separately: international diversification in the stock market and diversification over different asset classes. Our analysis allows us to compare and discuss different diversification strategies to construct a "world market portfolio" that is as ex-ante efficient as possible. For international equity diversification, we find that none of the Markowitz-based portfolio models is able to significantly outperform simple heuristics. Among those, the GDP weighting dominates the traditional cap-weighted approach. In the asset allocation case, Markowitz models are again not able to beat a broad spectrum of fixed-weight alternatives out-of-sample. Analyzing more than 5000 heuristics, we find that in fact almost any form of well-balanced allocation over asset classes offers similar diversification gains as even very sophisticated and recently developed portfolio optimization approaches. Based on our findings, we suggest a simple and cost-efficient allocation approach for private investors.
“…In a related paper, Chen et al (2007) follow the idea of Arnott et al (2005), but they propose estimating fundamental weights using a smoothed average of standard cap weights. In fact, they replace determination of fundamental size in terms of accounting data with a simple estimate based on price history, i.e., a moving average of past prices provides an estimate of fundamental price.…”
“…The rebalancing of the portfolio occurred once a year. On average, the portfolios built outperformed the S&P 500 by 1.97% per year, with the same volatility for the period between 1964 and 2002. Also in the US, Chen, Chen, and Basset (2007) estimated the fundamental weights of assets by means of a median of weights according to the historical market values of 1000 companies between 1962 and 2003, without employing their accounting information, such as in Arnott et al (2005). The authors argue that this information changes slowly and that prices always converge to the fair price in accordance with the fundamentals.…”
Purpose -This article analyzes fundamental indexation in Brazil relative to the IBrX 100 and selected stock funds in the period between June 2003 and May 2015. This strategy relies on weights based on fundamental indicators and not on market prices.Design/methodology/approach -Fundamental indices built with the IBrX 100 stocks were weighted according to fundamental indicators. The fundamental weighting method sets the weight of each stock as proportional to a previously determined fundament value. This article also considers an ordinal weighting.Findings -The results indicate that fundamental indices do not display positive and statistically significant returns and alphas after adjusting a five risk factor model and transaction costs. The ordinal weighting suggests that fundamental indicator outliers do not drive results. The evidence also suggests that fundamental indices might perform better in bear markets.Originality/value -In general, fundamental indices behave like value stocks and do not present abnormal returns. This is consistent with the absence of fundamental index products in the Brazilian market.Keywords -active portfolio management, passive portfolio management, fundamental indexation, stock funds.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.