Equal-weighted Portfolio Research Articles

The relationship between asset growth and the cross-section of stock returns

There is a large body of literature examining the association between stock characteristics and the cross-section of stock returns in international markets. Recently, Cooper et al. (2008) reported a strong association between total asset growth and stock returns in the US. In this paper, we show that an asset-growth effect also exists in the Australian equity market. Of particular interest, it is present amongst the largest Australian stocks. Over the 1983–2007 period, an equally-weighted portfolio of low-growth Big stocks outperforms a portfolio of high-growth Big stocks by an average 1% per month, equating to nearly 13% per annum. At an individual stock level of analysis, the asset-growth effect remains even after controlling for other variables whose association with the cross-section of returns is well known. Finally, we explicitly test whether asset growth is a priced risk factor using the common two-stage cross-sectional regression methodology. We find no evidence to support a risk-based explanation, thereby lending credence to Cooper et al.’s (2008) suggestion that the asset-growth effect is attributable to mispricing.

Select Sector SPDRs and the S&P 500: Is the Sum of the Parts Greater than the Whole?

In December 1998, Select-Sector ETFs, which subdivide the S&amp;P 500 SPDR (SPY) into nine distinct industry/sector groupings, were introduced into the market. In the study presented in this article, the author compares the returns from actively managing a portfolio of the nine Select-Sector funds using various techniques from the academic literature to the benchmark SPY. To test the funds’ performance, the author forms portfolios based on an equal weighting of the nine funds, the Markowitz mean-variance selection process, and momentum and overreaction price behaviors. His findings indicate that an equal-weighted portfolio of the sector funds reliably outperforms the SPY over all measures of performance and are robust across time. <b>TOPICS:</b>Exchange-traded funds and applications, portfolio construction, analysis of individual factors/risk premia, performance measurement

Removing biases in computed returns

This paper presents a straightforward method for asymptotically removing the well-known upward bias in observed returns of equally-weighted portfolios. Our method removes all of the bias due to any random transient errors such as bid-ask bounce and allows for the estimation of short horizon returns. We apply our method to the CRSP equally-weighted monthly return indexes for the NYSE, Amex, and NASDAQ and show that the bias is cumulative. In particular, a NASDAQ index (with a base of 100 in 1973) grows to the level of 17,975 by 2006, but nearly half of the increase is due to cumulative bias. We also conduct a simulation in which we simulate true prices and set spreads according to a discrete pricing grid. True prices are then not necessarily at the midpoint of the spread. In the simulation we compare our method to calculating returns based on observed closing quote midpoints and find that the returns from our method are statistically indistinguishable from the (simulated) true returns. While the mid-quote method results in an improvement over using closing transaction prices, it still results in a statistically significant amount of upward bias. We demonstrate that applying our methodology results in a reversal of the relative performance of NASDAQ stocks versus NYSE stocks over a 25 year window.

Informed Trading, Earnings Surprises, and Stock Returns

Entries and exits are often triggered by substantive private information, and we propose PC_NII, the percentage change in the number of a stock’s institutional investors, as a measure of informed trading. Over the 1982 to 2010 period, the top PC_NII decile outperforms the bottom PC_NII decile by 10% and 14% per annum for equal- and value-weighted portfolios, respectively. PC_NII subsumes the information content of standard institutional trading or herding measures in the forecast of stock returns, and the predictive power of PC_NII reflects its information content of future earnings surprises. The relationship between PC_NII and short-run future stock returns has attenuated noticeably for the equal-weighted portfolio since the Securities and Exchange Commission introduced Regulation Fair Disclosure in October 2000; however, we do not observe such a change for the value-weighted portfolio.

Mutual Fund Performance at the Oslo Stock Exchange

Using a newly constructed survivorship-bias free dataset, I examine the performance and persistence of all Norwegian equity mutual funds that have been listed on the Oslo Stock Exchange between 1982 and 2008. Controlling for the factors in the Fama-French model, there is no statistically significant evidence of risk-adjusted abnormal performance for an equal-weighted portfolio of mutual funds. Bootstrapping methods disentangling skill from luck find only weak signs of skill in the right tail of the cross-sectional distribution of alphas, but several inferior fund products in the left tail. There is no persistence in the performance of either winners or losers.

Diversification Properties of Investments in Shipping

In contrast to the more established alternative asset classes like real estate or hedge funds, there is not much research available for investments in shipping. This article contributes to closing this gap in the literature and investigates the diversification properties of investments in shipping. During the sample period, an investment in shipping stocks earned an attractive risk-return combination. In general, the addition of an investment in shipping stocks to a base portfolio of stocks and bonds enhanced diversification. The results also reveal other insights. First, the composition of the shipping stocks portfolio mattered much. Compared with the MSCI World Marine Index, which is a capitalization-weighted aggregate of 10 stocks, the diversification benefit of the broader and equally-weighted shipping stocks portfolio of our Research Index, with 41 stocks, was much more pronounced and somewhat statistically significant. Second, diversification properties were not stable through the course of time with larger diversification benefits during the bear market from March 2000 to March 2003 compared to the bull market from April 2003 to October 2007. The positive overall view of the diversification properties of shipping stocks is based on a single full stock market cycle.

Removing Biases in Computed Returns

This paper presents a straightforward method for asymptotically removing the well-known upward bias in observed returns of equally-weighted portfolios. Our method removes all of the bias due to any random transient errors such as bid-ask bounce and allows for the estimation of short horizon returns. We apply our method to the CRSP equally-weighted monthly return indexes for the NYSE, Amex, and NASDAQ and show that the bias is cumulative. In particular, a NASDAQ index (with a base of 100 in 1973) grows to the level of 17,975 by 2006, but nearly half of the increase is due to cumulative bias. We also conduct a simulation in which we simulate true prices and set spreads according to a discrete pricing grid. True prices are then not necessarily at the midpoint of the spread. In the simulation we compare our method to calculating returns based on observed closing quote midpoints and find that the returns from our method are statistically indistinguishable from the (simulated) true returns. While the mid-quote method results in an improvement over using closing transaction prices, it still results in a statistically significant amount of upward bias. We demonstrate that applying our methodology results in a reversal of the relative performance of NASDAQ stocks versus NYSE stocks over a 25 year window.

Testing conditional factor models: A nonparametric approach

Some recent studies of conditional factor models do not specify conditioning information but use data from small windows to estimate the time series of conditional alphas and betas. In this paper, we propose a nonparametric method using an optimal window to estimate time-varying coefficients. In addition, we offer two empirical tests of a conditional factor model. Using our new method, we examine the performance of the conditional CAPM and the conditional Fama–French three-factor model in explaining the return variations of portfolios sorted by size, book-to-market ratios, and past returns, for which recent literature has generated controversial results. We find that, although in general the conditional FF model outperforms the conditional CAPM, both models fail to explain well-known asset-pricing anomalies. Moreover, for both models, the failure is more pronounced for the equally-weighted portfolios than for the value-weighted ones.

Return Reversals, Idiosyncratic Risk, and Expected Returns

The empirical evidence on the cross-sectional relation between idiosyncratic risk and expected stock returns is mixed. We demonstrate that the omission of the previous month's stock returns can lead to a negatively biased estimate of the relation. The magnitude of the omitted variable bias depends on the approach to estimating the conditional idiosyncratic volatility. Although a negative relation exists when the estimate is based on daily returns, it disappears after return reversals are controlled for. Return reversals can explain both the negative relation between value-weighted portfolio returns and idiosyncratic volatility and the insignificant relation between equal-weighted portfolio returns and idiosyncratic volatility. In contrast, there is a significantly positive relation between the conditional idiosyncratic volatility estimated from monthly data and expected returns. This relation remains robust after controlling for return reversals. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Large Portfolio Risk Management with Dynamic Copulas

Modeling the dynamic high-dimensional multivariate distribution is very useful for active risk management and optimal portfolio allocation; however, available dynamic models are not easily applied for high-dimensional problems due to the curse of dimensionality. In the light of the recent development of multivariate GARCH techniques for a large number of underlying securities, I extend the framework of the Dynamic Conditional Correlation/Equicorrelation (DCC/DECO) (Engle, 2002 and Engle and Kelly, 2008) and an extreme value approach (McNeil and Frey, 2000) into a series of Dynamic Conditional Elliptical Copulas. By constructing portfolios of 89 stocks from CDX-listed …rms between 1995 and 2005, I examine Value at Risk (VaR) and Expected Shortfall (ES) by Monte Carlo simulation for passive portfolios and dynamic optimal portfolios through Mean-Variance and ES criteria. I …nd: (1) Modeling the marginal distribution is important for the dynamic high-dimensional multivariate models. (2) Neglecting the dynamic dependence in the copula causes over-aggressive risk management. (3) The DCC/DECO Gaussian copula and t-copula work very well for both VaR and ES. The DCC copula is necessary for value-weighted portfolios. For equally-weighted portfolios, the DECO copula performs about as well as the DCC copula. (4) Grouped t-copula and t-copula with dynamic degrees of freedom further match the fat tail. (5) Correctly modeling dependence structure makes an improvement in portfolio optimization. The optimal portfolio by ES does a good job against the tail risk in both DECO and DCC copulas. (6) Since portfolio optimization induces statistical error maximization, the assumption of multivariate t innovations with exogenously given degrees of freedom provides a ‡exible and applicable method for optimal portfolio risk management.

Temporary Components of Stock Prices: New Univariate Results

While there is growing evidence that stock prices do not follow pure random walks, the degree of existence of temporary components in stock prices is not well known. Modelling stock prices as the sum of a random walk and a general stationary (predictable) component, we propose an estimable lower bound on the proportion of total stock return variance caused by the predictable component. Contrary to the absolute value of the first-order autocorrelation coefficient estimates of Fama and French (1988), this lower bound reasonably estimates the true variance roportion in finite samples also when the temporary component does not follow a first-order autoregressive process. The estimated mean values of the lower bound reach a maximum of 10% for the equal-weighted market portfolio of NYSE stocks over the post-war period 1947-1986, while the maximum is 25% for the pre-war period 1926-46. The value-weighted market portfolio exhibits generally smaller variance proportion estimates. We also reexamine the pure random walk hypothesis using our univariate variance proportion statistic.

Does International Diversification Work for Property Securities?

In this paper we examine the construction of international indirect property portfolios available for the UK, France and Japan during three overlapping periods, 1980-88,1986-94 and 1992-2001. The purpose of this analysis is to consider whether the rewards from international property diversification of this form are sufficient to compensate for the higher cost of internationalization for domestic investors. While we use two covariance optimization algorithms these give ex post results, and to provide some evidence that has some relevance ex ante we also construct equally-weighted portfolios across the markets available for each period examined. We provide our analysis using the domestic currencies of the UK, France and Japan as the numeraire for each set of portfolios constructed as it is likely that potential investors from those countries in overseas markets will be making the comparison with the domestic returns from the same sector in order to be persuaded to invest. It seems clear from our analysis that there is a strong case for investors in the UK, France and Japan to invest in internationally diversified property securities portfolios rather than just in their own domestic sectors.

Stationary Component in Stock Prices: A Reappraisal of Empirical Findings

This paper re-examines the issue of mean reversion in stock prices by incorporating the structural break effect in the long horizon regression. Before adjusting for structural break, the paper finds that previous studies understate the evidence of mean-reversion. The understatement is mainly due to the clustering heteroskedasticity and autocorrelation in the overlapping returns. After adjusting for structural break(s), no evidence of predictability for value-weighted returns has been documented. However, stronger evidence of mean reversion in stock prices is documented for equally-weighted portfolios. The reverse effect of structural break can be explained by the switch to mean aversion in the last subperiod of value-weighted portfolios while no such switch in equally weighted portfolios (JEL: G1, C22).

Research Impacts and Correction of the Upward Biased CRSP Daily Equal-Weighted Index

Loughran and Ritter (1995), and Canina et al. (1998) show that compounding the CRSP daily Equal-Weighted Return with Dividend (EWRETD) to obtain a monthly index will generate a substantial bias. To overcome the influences of bid-ask bounce, Blume and Stambaugh (1983), non-synchronous trading, Roll (1983), we design a better method to generate a monthly EWRETD index from the CRSP daily data. Using our method, the average annual bias between the generated monthly time series and the corresponding values drawn from the CRSP monthly tape is 0.02%, considerably smaller than 6% reported in Canina et al. (1998). In the paper, we explain the reasons why the conventional way to construct a daily equal-weighted portfolio lacks the ability to filter out the undesired impacts of the microstructure and is inconsistent with corresponding monthly data. More importantly, we offer a new method to generate an unbiased CRSP daily EWRETD, which is free of the problems associated with the microstructure and consistent with the CRSP monthly index. Benchmarked on this unbiased daily time series, we study the impacts of the upward biased CRSP daily EWRETD on the estimations of beta, Jensen's alpha and event study.

A Two-Factor Asset Pricing Model and the Fat Tail Distribution of Firm Sizes

We derive a theoretical two-factor model which has empirically a similar explanatory power as the Fama-French three-factor model. In addition to the usual market risk, our model accounts for a diversification risk, proxied by the equally-weighted portfolio, and which results from an internal consistency appearing for arbitrary large economies, as a consequence of the concentration of the market portfolio when the distribution of the capitalization of firms is sufficiently heavy-tailed as in real economies. Our model rationalizes the superior performance of the Fama and French three-factor model in explaining the cross section of stock returns: the size factor constitutes an alternative proxy of the diversification factor while the book-to-market effect is related to the increasing sensitivity of value stocks to this factor.

Do IPOs Really Underperform in The Long-Run? New Evidence from the Canadian Market

Kooli, L9Her, and Suret analyze 141 Canadian IPOs from the period 1986 to 2000 and take a different approach. They question the method of how to measure long-term performance and if other analysts are using the right benchmark. The issue is whether to use a value-weighted or equally-weighted portfolio to compare returns. Their review will help sharpen the measurement issues as you measure your own portfolio9s performance.

Modelling and Forecasting Dynamic VaR Thresholds for Risk Management and Regulation

The paper describes alternative methods of estimating Value-at-Risk (VaR) thresholds based on two calibrated models and three conditional volatility or GARCH models. The five models of volatility are used to estimate and forecast the VaR thresholds of an equally-weighted portfolio, comprising four financial stock indexes, namely S&P500, CAC40, FTSE100 a Swiss market index (SMI). On the basis of the number of (non-)violations of the Basel Accord thresholds, the best performing model is PS-GARCH, followed closely by VARMA-AGARCH, neither of which would lead to the imposition of any penalties. The next best performing threshold forecasts are given by the Portfolio-GARCH and RiskmetricsTM-EWMA models, both of which would have a penalty of 0.5. Not surprisingly, the worst forecasts are obtained from the standard normal method based on historical variances.

The Cross-Sectional Variability of Stock-Price Returns: Country and Sector Effects Revisited

We investigate the impact of country and sector as variables in explaining the cross-sectional variability of price returns for a sample of over 1900 companies comprising the MSCI Developed World Index, drawn from 21 countries, over the period 1992-2001. For the value-weighted world portfolio, the country effect dominates although the sector effect increases markedly, and the country effect decreases, in the post-2000 period. The country effect is, however, much stronger when the largest 300 companies are excluded from the analysis. The same pattern is observed for the portfolio comprising companies from the EMU countries. For equally-weighted portfolios, the apparent dominance of the sector effect is largely attributable to the inclusion of the TMT sector. The negative trend in market-wide indices and the volatility experienced at the end of the sample period also account for the assertion that the sector effect has overtaken the country effect in the post-2000 period.

Long-horizon event studies and event firm portfolio weights: Evidence from U.K. rights issues re-visited

Empirical results, in long-horizon event studies, are sensitive to whether equal- or value-weighting schemes are used to form event firm portfolios. In this paper we propose, as a first step, an evaluation of the economic value to investing in an equal-weighted and a value-weighted event firm portfolio prior to the event study. Using tests for mean-variance spanning we find in our data a significant improvement in an investor's investment opportunity set to investing in an equal-weighted portfolio. We then re-visit the long-run post-offer performance for rights issuers in the U.K. where we find, as in other studies, differences in both the magnitude and statistical significance of abnormal performance for value-weighted and equal-weighted event firm portfolios. We then use the results from our first step to provide an economic rationale for interpreting our results. A general conclusion we draw is that it may be useful to first ascertain, in long-horizon event studies, the economic value of portfolio weighting schemes as this can then provide some guidance to the use of a specific portfolio weighting scheme and thereby to interpretation of often conflicting results.

How Profitable is Capital Structure Arbitrage?

This paper examines the risk and return of the so-called capital structure arbitrage, which exploits the mispricing between a company's debt and equity. Specifically, a structural model connects a company's equity price with its credit default swap (CDS) spread. Based on the deviation of CDS market spreads from their theoretical counterparts, a convergence-type trading strategy is proposed and analyzed using 135,759 daily CDS spreads on 261 obligors. At the level of individual trades, the risk of the strategy arises when the arbitrageur shorts CDS and the market spread subsequently skyrockets, forcing the arbitrageur into early liquidation and engendering large losses. An equally-weighted portfolio of all trades produces Sharpe ratios similar to those of other fixed-income arbitrage strategies and hedge fund industry benchmarks. However, the monthly excess returns on this portfolio are not significantly correlated with either equity or bond market factors.