Annual Rebalancing Research Articles

A new class of Shariah-compliant portfolio optimization model: diversification analysis

<abstract><p>This study proposes a novel Shariah-compliant portfolio optimization model tested on the daily historical return of 154 Shariah-compliant securities reported by the Shariah Advisory Council of Securities Commission Malaysia from 2011 to 2020. The mathematical model employs an annual rebalancing strategy subject to a Conditional Value-at-Risk (CVaR) constraint while considering practical and Islamic trading concerns, including transaction costs, holding limits, and <italic>zakat</italic> payment. To validate the model, the optimal portfolios are compared against an Islamic benchmark index, a market index, and portfolios generated by the mean-variance model, as well as a forecast accuracy test by the Mean Absolute Percentage Error and Mean Absolute Arctangent Percentage Error. Furthermore, this study examines the inter-stock relationship within the generated portfolios using correlation and Granger causality tests to identify the diversification performance. Results show an outperformance of the model in offering portfolios with higher risk-adjusted returns under a comparably short computational time and an indication of generally well-diversified portfolios by the weak correlations between securities. The study further noted that the model is adept at risk management in addition to higher forecast accuracy during financial crises by showing remarkably fewer causal relationships during bear markets in 2011, 2014, and 2020. The findings of an inversed relationship between portfolio risk and the number of causalities between securities offer new insights into the effect of dynamic relationships between securities on portfolio diversification. In conclusion, the proposed model carries higher moral and social values than the conventional models while portraying high potential in enhancing the efficiency of asset allocation, contributing to economic diversification and the scarce literature on Islamic portfolio optimization modelling. The study also supports the substantially increasing demand for Shariah-compliant strategies following globalization and the changing demographic of the real financial world with growing priorities of social and sustainability values.</p></abstract>

The cost of constituent-rebalancing of Sharīʿah-compliant indexes: lessons for future crises

PurposeThis study aims to quantify the cost of rebalancing Sharīʿah-compliant indexes, both economically and statistically.Design/methodology/approachAn empirical approach is employed where the rebalanced Sharīʿah-compliant index is calculated numerous times with different lags in rebalancing, and the number of stocks and their cost across time are determined in order to identify the optimal rebalancing frequency.FindingsThis paper finds that annual Sharīʿah rebalancing does not lead to significant differences in portfolio returns, even though it does bring some advantages in cumulative wealth starting from the third year onwards and brings about better risk-return characteristics measured in terms of the Sharpe ratio. However, these advantages involve an average annual shifting between 30 and 60% of the portfolio market capitalization, which would be costly at any level of transaction costs.Practical implicationsA private investor may be better off holding a constant portfolio and only rebalancing in three-year intervals since this was shown to possess similar portfolio returns and cumulative wealth results. Any advantages of annual rebalancing in terms of risk-return characteristics may be offset by transaction costs of rebalancing. Sharīʿah scholars and practitioners are to determine when the correct time for rebalancing really is, taking into consideration the cost of rebalancing vis-à-vis the advantages in cumulative wealth and risk-return characteristics of the portfolio.Originality/valuePredictions that Islamic indexes will perform well during financial crises, such as the COVID-19 pandemic, miss the cost of frequent rebalancing. This paper addresses this issue in an empirical manner learning from the previous crisis in 2008.

Portfolio Constraints: An Empirical Analysis

Mean-variance optimization often leads to unreasonable asset allocations. This problem has forced scholars and practitioners alike to introduce portfolio constraints. The scope of our study is to verify which type of constraint is more suitable for achieving efficient performance. We have applied the main techniques developed by the financial community, including classical weight, flexible, norm-based, variance-based, tracking error volatility, and beta constraints. We employed panel data on the monthly returns of the sector indices forming the MSCI All Country World Index from January 1995 to December 2020. The assessment of each strategy was based on out-of-sample performance, measured using a rolling window method with annual rebalancing. We observed that the best strategies are those subject to constraints derived from the equal-weighted model. If the goal is the best compromise between absolute return, efficiency, total risk, economic sustainability, diversification, and ease of implementation, the best solution is a portfolio subject to no short selling and bound either to the equal weighting or to TEV limits. Overall, we found that constrained optimization models represent an efficient alternative to classic investment strategies that provide substantial advantages to investors.

Sunshine vs. predatory trading effects in commodity futures markets: New evidence from index rebalancing

Annual rebalancing of the S&P Goldman Sachs Commodity Index (S&P GSCI) provides a novel identification of the impact of predictable order flows from index investors in commodity futures markets. Using the 24 commodities included in the S&P GSCI for 2004–2019, we show that cumulative abnormal returns to a long-short strategy peaked at 72 basis points in the middle of the week following the rebalancing period, but the impact declines to near zero within the next week. The findings show that the impact of order flows from financial investors on commodity futures prices is modest and temporary, consistent with the prediction of sunshine trading theory.

Is Shari’ah Index Membership Risky? The Case of Malaysia Shari’ah Blue-Chip Index

The study explores the Shariah index membership effect around index revision period especially to the newly added and deleted constituent stocks (termed as event stocks). This study analysed 40 event stocks for Shariah blue-chip index, Dow Jones Islamic Market Titans Malaysia 25 Index (DJIMY25). The analysis was conducted over a period of seven years (2009-2015) using event study methodologies which capture abnormal returns, trading volumes, and return volatility, and discussed the extent of market efficiency. The study divided the event stocks into three groups – additions, deletions due to the index annual rebalancing and deletions due to non-Shariah compliance. The findings of this study provide a new evidence on index additions and deletions contrary to the ones reported in previous studies. Surprisingly, additions to DJIMY25 produces negative results with permanent decrease in stock returns and temporary decrease in trading volumes. The deletions either due to the index annual rebalancing or non-Shariah compliance have shown negative results with the decrease in stock price, temporary decrease in trading volumes and increase in the stock’s absolute volatility. The finding of this study implied that index membership in Shariah index can induce Shariah compliant risk for the firms that are unable to maintain their Shariah compliant status in the long-term.

Sunshine vs. Predatory Trading Effects in Commodity Futures Markets: New Evidence from Index Rebalancing

Abstract Annual rebalancing of the S&P Goldman Sachs Commodity Index (S&P GSCI) provides a novel identification of the impact of predictable order flows from index investors in commodity futures markets. Using the 24 commodities included in the S&P GSCI for 2004–2019, we show that cumulative abnormal returns to a long-short strategy peaked at 72 basis points in the middle of the week following the rebalancing period, but the impact declines to near zero within the next week. The findings show that the impact of order flows from financial investors on commodity futures prices is modest and temporary, consistent with the prediction of sunshine trading theory.

What is the optimal weight for gold in a portfolio?

We show that the statistical properties of gold are negatively correlated with equities and that including gold in a portfolio will provide diversification benefits. As there is no consensus on the proportion of gold that should be included in a strategic portfolio allocation we propose a visual tool that associates a performance metric with a range of possible asset weighting schemes—a Sharpe ratio response surface. This very surface shows that a target performance metric can be achieved with a large number of different allocations. We further argue that the rebalancing approach based on the surface closest to the benchmark surface under the Hausdorrf distance metric should be selected. Using a data sample between 1990 and 2018, we find that annual rebalancing with a 44-week lookback period achieves the minimum distance from the benchmark surface.

Is the Supply Curve for Commodity Futures Contracts Upward Sloping?

Annual rebalancing of the S&P GSCI index provides a novel and strong identification to estimate the shape of supply curves for commodity futures contracts. Using the 24 commodities included in the S&P GSCI for 2004–2017, we show that cumulative abnormal returns (CARs) reach a peak of 59 basis points in the middle of the week following the rebalancing period, but the impact is temporary as it declines to near zero within the next week. The findings provide clear evidence that the supply curve for commodity futures contracts is upward sloping in the short-run but almost flat in the longer-run.

Enhanced Portfolio Performance Using a Momentum Approach to Annual Rebalancing

After diversification, periodic portfolio rebalancing has become one of the most widely practiced methods for reducing portfolio risk and enhancing returns. Most of the rebalancing strategies found in the literature are generally regarded as contrarian approaches to rebalancing. A recent article proposed a rebalancing approach that incorporates a momentum approach to rebalancing. The momentum approach had a better risk adjusted return than either the traditional approach or a Buy-and-Hold approach. This article identifies an improvement to the momentum approach and then examines the impact of transactions costs and taxes on the portfolio performance of four active rebalancing approaches.

What Is the Optimal Weight for Gold in a Portfolio?

We show that the statistical properties of gold are negatively correlated with equities and that including Gold in a portfolio will provide diversification benefits. As there is no consensus on the proportion of gold that should be included in a strategic portfolio allocation we propose a visual tool that associates a performance metric with a range of possible asset weighting schemes; a Sharpe ratio response surface. This very surface shows that a target performance metric can be achieved with a large number of different allocations. We further argue that the rebalancing approach based on the surface closest to the benchmark surface under the Hausdorrf distance metric should be selected. Using a data sample between 1990 and 2018, we find that annual rebalancing with a 44 week lookback period achieves the minimum distance from the benchmark surface.

More on intangibles: Do stockholders benefit from brand values?

This paper analyzes the relationship between brand value and short and long-run stock performance. An equally-weighted portfolio of the American non-financial companies recognized by Interbrand as part of the 100 most valuable global brands earned an eleven-day cumulative abnormal returns (CARs) of 0.54% (17.79% annually) and a three-day CARS of 0.31% (37.97% annually) from 2001 through 2012. The four-factor monthly alpha averaged 1.1428% (13.7136% annually) over the risk-free rate and 1.3317% (15.9804% annually) over the S&P 500 index. Regression results show that the companies' brand values and capitalization were significant contributors to CARS. In addition, the average buy-and-hold return for a portfolio with annual rebalancing to include the recognized companies the preceding year was 15.29%. The annually rebalanced portfolio outperformed the industry average by 3.45% and the S&P 500 by 8.99%. All the above mentioned returns were significant at the 1% level. However, the data shows that consumer reaction to brand ranking is positive but not significant.

Very Smart Beta from Hedge Fund Clones: It's Not 'How' but 'What' to Clone!

We argue that only hedge funds whose returns are driven by beta management of exposures to latent risk factors could be successfully replicated. We develop a methodology for creating a portfolio of ETFs that replicates risk factor exposures taken by successful beta active cloneable hedge funds. The methodology allows any investor to access active factor strategies employed by hedge funds. It could be interpreted as cloning beta exposures of the best beta active hedge funds, delivering outstanding long-term risk-adjusted performance. The active factor ETF portfolio only requires annual rebalancing, and is constructed with a transparent algorithmic approach, which conforms to a definition of a smart beta strategy.

Investible Benchmarks for Actively Managed Mutual Funds

I use exchange traded funds to construct low cost benchmarks for actively managed mutual funds. The benchmarks can be identified in advance, require no leverage or shorting, and require only annual rebalancing. The average fund underperforms its benchmark by 1% per year after expenses, a difference in performance equivalent to a $25 billion per year opportunity cost for investors selecting active management. The fees charged by actively managed funds are the primary reason they underperform. Active management comes at a significant cost, but without any offsetting benefit.

Downside Loss Aversion and Portfolio Growth

Optimizing over power-log utility functions allow for the inclusion of downside loss aversion, a broader range of investor preferences, and account for higher-order moments like skewness and kurtosis in the optimization process. We implement multi-period power-log optimization (PLO) with annual rebalancing on a portfolio consisting of a treasury security, the S&P500 index and a call option on the index. PLO results in higher geometric average realized returns with lower tail risk, and lower standard deviation than meanvariance efficient portfolios with the same ex-ante expected returns. It also provides better downside protection against large, negative return surprises, such as the down markets in 2002 and 2008.

Return Predictability and Dynamic Asset Allocation: How Often Should Investors Rebalance?

To exploit return predictability via dynamic asset allocation, investors face the important practical issue of how often to rebalance their portfolios. More frequent rebalancing uses statistically and economically significant short-horizon return predictability to aggressively pursue the dynamic investment opportunities afforded by changes in expected returns. However, the degree of return predictability typically appears stronger at longer horizons, which, along with lower transaction costs, favors less frequent rebalancing. The authors analyze the performance effects of rebalancing frequency in the context of dynamic portfolios constructed from monthly, quarterly, semi-annual, and annual return forecasts for U.S. stocks, bonds, and bills, where the dynamic portfolios rebalance at the same frequency as the forecast horizon. Along the transaction-cost/rebalancing frontier, monthly (annual) rebalancing provides the greatest outperformance when unit transaction costs are below (above) approximately 50 basis points, and dynamic portfolios based on annual rebalancing typically outperform the benchmarks for unit transaction costs well in excess of 400 basis points. <b>TOPICS:</b>Portfolio theory, statistical methods, portfolio construction

Value investing and technical analysis in Taiwan stock market

Unlike the U.S. and most developed countries, Taiwan stock market has been widely documented to have no value premium. Prior studies on the value premium typically adopt a conventional approach proposed by Fama and French (1992), which suggests a buy-and-hold strategy with annual rebalancing. We argue that a sophisticated investor can do better (obtain higher returns) than a simple buy-and-hold strategy by timing the market with the help of some technical analysis. Specifically, we show that an application of a moving average timing strategy to portfolios sorted by book-to-market (BM) ratios could generate higher returns than the buy-and-hold strategy. Using common stocks listed on the Taiwan Stock Exchange (TWSE), we confirm that the moving average timing strategy does substantially outperform the buy-and-hold strategy. Taking advantage of this observation, we propose a zero-cost portfolio constructed by buying the highest BM portfolio, and short-selling the lowest BM portfolio based on trading signals issued by the moving average rule, and demonstrate that such a new investment strategy can produce significantly positive returns. Robustness of results obtained in this paper is further verified and consolidated by extending the empirical study with a different currency, alternative lag lengths, transaction cost, subperiod analysis, business cycles and market timing.

Australian evidence on the implementation of the size and value premia

AbstractThis study investigates whether passive investment managers can exploit the size and value premia without incurring prohibitive transaction costs or being exposed to substantial tracking error risk. Returns on the value premium are shown to be pervasive across size groups, while the size premium is nonlinear and driven by microcaps. The value premium cannot be explained by the capital asset pricing model; however, returns on value portfolios do covary across monetary regimes. The substantial turnover required to achieve annual rebalancing and the relative illiquidity of Australian small‐cap firms means that investing in a portfolio of large‐cap value firms appears to be the best way for passive fund managers to exploit the Fama and French (1993) premia.

Fundamental Indexation: Rebalancing Assumptions and Performance

The authors show that the performance of a fundamental index with annual rebalancing, as proposed by Arnott, Hsu, and Moore [2005], can be highly sensitive to the subjective choice of when to rebalance. For the year 2009, for example, they found that a fundamental index rebalanced every March outperformed the capitalization-weighted index by over 10%, whereas a fundamental index rebalanced every September underperformed. The authors provide intuitive and statistical evidence in support of the hypothesis that if two fundamental indices diverge, they do not subsequently tend to mean revert (i.e., the gap is likely to be permanent). The performance ambiguity is an undesirable feature for an index that is used for benchmarking purposes. The authors introduce the idea of blending multiple underlying fundamental indices, each one rebalanced annually but at different dates, as an example of how to construct a more robust fundamental index without increasing turnover.

How to Construct Fundamental Risk Factors?

Our paper reexamines the methodology of Fama and French (1993) for creating US empirical risk factors, and proposes an extension on the way to compute the mimicking portfolios. Our objective is to develop a modified Fama and French (F&F) methodology that could be easily implemented on other markets, and that could also easily price other risk fundamentals. We raise three main problems in the F&F methodology. First, their annual rebalancing is consumptive in long time-series which sometimes simply do not exist for small exchange markets. Moreover, this does not match with the investment horizon of the investors. Second, the independent sorting procedure underlying the formation of the 6 F&F two-dimensional portfolios causes moderate level of correlation between premiums. Finally, sorting the stocks into portfolios according to NYSE stock returns tend to over-represent the proportion of small stocks in small and value portfolios. We estimate, along our technology, alternative premiums for the size, book-to-market and momentum risk fundamentals. We compare these three risk premiums to the Fama and French and Carhart benchmarks that Kenneth French make available on his website. In an analysis framework without data snooping bias, we show evidence that although they are correlated, the original F&F premiums and our versions of the F&F premiums bring complementary information. Furthermore, we find that our empirical model better complements the market model for explaining cross-sectional dispersion in returns than the F&F premiums.

Investing in Growth Stocks vs. Value Stocks

This article examines whether the performance in the investment in value stocks vs. growth stocks is different in terms of the holding period and stock market conditions. The study analyzes the performance of high- and low-P/E portfolios for the quarterly and monthly rebalancing as well as the annual rebalancing, using a sample period of April 1986 to March 2003, divided into a general bull market period of April 1986 to March 2000 and a recent bear market period of April 2000 to March 2003. The findings show that regardless of the frequency of portfolio rebalancing, high-P/E portfolios outperform low-P/E portfolios especially for the bull market period. However, when adjusted for the risk inherent in different P/E portfolios, low-P/E portfolios outperform high-P/E portfolios for all rebalancing frequencies. Finally, the evidence shows that more frequent rebalancing tends to improve the performance of low-P/E portfolios but reduces the performance of high-P/E portfolios. <b>TOPICS:</b>Equity portfolio management, performance measurement, portfolio construction