THE CROSS-AUTOCORRELATION OF SIZE-BASED PORTFOLIO RETURNS IS NOT AN ARTIFACT OF PORTFOLIO AUTOCORRELATION

Prior studies find evidence of asymmetric size-based portfolio return cross-autocorrelations where lagged large firm returns lead current small firm returns. However, some studies question whether this economic relation is independent of the effect of portfolio return autocorrelation. We formally test for this independence using size-based portfolios of New York Stock Exchange and American Stock Exchange securities and, separately, portfolios of Nasdaq securities. Results from causality regressions indicate that, across all markets, lagged large firm returns predict current small firm returns, even after controlling for autocorrelation in small firm returns. These cross-autocorrelation patterns are stronger for Nasdaq securities.     

AN EMPIRICAL INVESTIGATION OF BETA STABILITY: PORTFOLIOS VS. INDIVIDUAL SECURITIES

The concept that portfolio betas are more stable than betas for individual securities has become the 'conventional wisdom' in finance; statements to this effect may be found in many popular finance textbooks. The objective of this paper is to challenge the conventional wisdom. A random sample of individual stock returns and portfolio returns is used to compare the empirical distribution of beta shifts for individual firms and portfolios. The number of statistically significant changes in beta are no greater for individual securities than for portfolios.     

Differences in Perstistence in Aggregated and Disaggregated UK Stock Returns: A Reconciliation

Studies of the persistence in the returns series of UK stocks, using inter alia variance ratios, have documented clear differences between the relatively low levels of persistence in individual security returns and the relatively high levels of persistence in the returns of portfolios composed of these same securities. In this paper, I reconcile this contrast by showing that portfolio return variance ratios should not be expected to reflect (own) persistence levels in the component security returns, but instead should reflect a 'cross-persistence' between the securities. I calculate synthetic portfolio variance ratios from measures of security return 'cross-persistence' and find that they replicate closely the observed portfolio return variance ratios, which provides empirical support for the theoretical results.     

Does Order Flow Commonality Extend Across Trade Sizes and Securities?

We examine commonality in order imbalances across different types of securities and find that the extent of commonality is greater than previously documented. Order imbalances in portfolios of small stocks, large stocks, and closed-end funds have explanatory power for other portfolio returns even in the presence of own order flow. Our analysis of order flow composition reveals commonality in small and medium trades, but not in large trades, across portfolios. The activity from small-size trades is systemic, but not generally associated with returns on other securities. Order imbalances from larger size trades provide more information relevant to stock prices.     

Orthogonal Frontiers and Alternative Mean-Variance Efficiency Tests

This paper catalogues properties of minimum norm orthogonal portfolios: portfolios which minimize a quadratic objective function and have returns uncorrelated with those of a candidate portfolio that is not mean-variance efficient. The analysis shows that the dollar versions of these portfolios correspond to estimators of zero beta rates based on alternative statistical criteria and grouping procedures while costless orthogonal portfolios represent candidate mean-variance efficiency tests. It also develops inference procedures for zero and unit net investment portfolios of individual securities (instead of grouped portfolios) that have zero expected betas. The resulting mean-variance efficiency tests are reasonably insensitive to the underlying statistical assumptions.     

Analysis of REIT IPOs Using a Market Microstructure Approach: Anomalous Behavior or Asset Structure

In this research, we examine and present new evidence on the market activity following the initial public offering (IPO) of a real estate investment trust (REIT) using microstructure data. We analyze the bid-ask spread differences for REIT securities compared to common stocks and closed-end funds for all IPOs between 1985 and 1988. Our results show that REITs, as a whole sample, experience significantly greater bid-ask spreads immediately following the IPO compared to common stocks and funds. However, this outcome is driven by the equity REIT sample, with the mortgage REIT sample having significantly smaller bid-ask spreads. This is in contrast to the evidence documented by Nelling, Mahoney, Hildebrand, and Goldstein (1995). We attribute our result to the underlying asset structure (such as equity, hybrid, and mortgage portfolios) of the various REITs. Overall, however, we find that bid-ask spreads for REITs are similar to those of common stock when both asset structure and the traditional determinants of the spread (share price, trade volume, and returns variance) are considered.     

Government Bond Returns,Measurement of Interest Rate Risk,and the Arbitrage Pricing Theory

Empirical tests are reported for Ross' arbitrage pricing theory using monthly data for U.S. Treasury securities during the 1960–1979 period. We find that mean returns on bond portfolios are linearly related to at least two factor loadings. Multivariate test results, however, are not consistent with the APT. Our sample data in the U.S. Treasury securities market are also not consistent with either version of the CAPM. One-month-ahead forecasts of excess returns using factor-generating models are compared with corresponding naive predictions or predictions using the “market model” with various market portfolios.     

Deciphering robust portfolios

Robust portfolio optimization has been developed to resolve the high sensitivity to inputs of the Markowitz mean–variance model. Although much effort has been put into forming robust portfolios, there have not been many attempts to analyze the characteristics of portfolios formed from robust optimization. We investigate the behavior of robust portfolios by analytically describing how robustness leads to higher dependency on factor movements. Focusing on the robust formulation with an ellipsoidal uncertainty set for expected returns, we show that as the robustness of a portfolio increases, its optimal weights approach the portfolio with variance that is maximally explained by factors.     

Funding conditions and insurance stock returns: Do insurance stocks really benefit from rising interest rate regimes?

We examine funding conditions and U.S. insurance company stock returns. Although constrained funding conditions, signaled by restrictive Federal Reserve monetary policy, correspond with increases in the future payouts of fixed‐income securities held by insurance firms and potentially provide value through the liability side of insurer balance sheets, they also decrease the values of securities currently held in insurer portfolios. Prior research finds that restrictive policy has a negative effect on equity returns in general. Our results suggest the negative impacts of constrained funding environments outweigh the potential positives, as insurance company stock returns are significantly lower during periods of constrained funding. This effect varies within a given funding state and also across insurer type. The effect is strongest during the first 3 months of a constrained funding environment and for life and health insurers—insurer types with longer portfolio durations. For property and liability (P&L) insurers, lower stock return performance only exists in the first 3 months of a constrained funding environment. In the subsequent months, P&L insurers actually have higher stock returns during constrained periods, consistent with their typically shorter duration asset portfolios, which are more quickly rolled over into new higher‐yielding securities.     

A relaxation algorithm for building undominated portfolios

Stochastic dominance methods which have been developed in recent years are generally more valid than mean-variance (EV) and higher moment methods for selecting a portfolio from a given finite set of possible portfolios. One of the limitations of these methods is the lack of procedures for building portfolios from a given set of securities and the probability distribution of their returns. Markowitz has developed an algorithm based on the restriction method in linear programming to build undominated portfolios. In this paper a more efficient method based on the relaxation method of linear programming is developed and tested for efficiency. Computational results justify its use as a practical tool for portfolio building.     

INTERNATIONAL DIVERSIFICATION OF EQUITIES AND FIXED-INCOME SECURITIES

Portfolio selection models have been applied principally to common stocks traded in the United States and in foreign stock markets. This study examines the efficient set of portfolios selected from a choice set that includes returns derived from domestic and international corporate bond and government bond indices as well as domestic and international stock indices. To assess the benefits of international multi-asset diversification, the authors examine the following issues: (1) the extent to which international and domestic fixed-income securities are included in efficient portfolios; (2) the effect on efficient set composition of using the Sharpe portfolio selection model as compared to the Markowitz portfolio selection model; (3) the sensitivity of efficient set characteristics produced from a single-index based portfolio selection model to alternative world market indices; and (4) the correspondence between expected and realized portfolio risk and return for the different portfolio selection models.     

Liquidity costs,idiosyncratic volatility and expected stock returns

This paper considers liquidity as an explanation for the positive association between expected idiosyncratic volatility (IV) and expected stock returns. Liquidity costs may affect the stock returns, through bid-ask bounce and other microstructure-induced noise, which will affect the estimation of IV. We use a novel method (developed by Weaver, 1991) to eliminate microstructure influences from stock closing price-based returns and then estimate IV. We show that there is a premium for IV in value-weighted portfolios, but this premium is less strong after correcting returns for microstructure bias. We further show that this premium is driven by liquidity in the prior month after correcting returns for microstructure noise. The pricing results from equally-weighted portfolios indicate that IV does not predict returns either before or after controlling for liquidity costs. These findings are robust after controlling for common risk factors as well as analysing double-sorted portfolios based on IV and liquidity.     

Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas

We propose to model the joint distribution of bid-ask spreads and log returns of a stock portfolio by using Autoregressive Conditional Double Poisson and GARCH processes for the marginals and vine copulas for the dependence structure. By estimating the joint multivariate distribution of both returns and bid-ask spreads from intraday data, we incorporate the measurement of commonalities in liquidity and comovements of stocks and bid-ask spreads into the forecasting of three types of liquidity-adjusted intraday Value-at-Risk (L-IVaR). In a preliminary analysis, we document strong extreme comovements in liquidity and strong tail dependence between bid-ask spreads and log returns across the firms in our sample thus motivating our use of a vine copula model. Furthermore, the backtesting results for the L-IVaR of a portfolio consisting of five stocks listed on the NASDAQ show that the proposed models perform well in forecasting liquidity-adjusted intraday portfolio profits and losses.     

The price adjustment and lead-lag relations between stock returns: microstructure evidence from the Taiwan stock market

This paper investigates the price adjustment and lead-lag relations between returns on five size-based portfolios in the Taiwan stock market. It finds evidence that the price adjustment of small-stock portfolios is not slower than that of large-stock portfolios. Additionally, limited evidence supports a positive leading role of large-stock portfolio returns over small-stock portfolio returns. These two findings are substantially different from the results of previous research on developed markets.     

PORTFOLIO PERFORMANCE IN RELATION TO QUALITY,EARNINGS, DIVIDENDS,FIRM SIZE,LEVERAGE, AND RETURN ON EQUITY

This paper examines the risk-return performance of portfolios formed from S&P quality rankings over the time period 1970–1979. In addition, the risk-return characteristics of the portfolios are compared with performance as measured by fundamental data regarding earnings, dividends, firm size, leverage, and return on equity. The results suggest that the S&P quality rankings are closely correlated to risk as measured by the variability of returns and earnings changes, but the rankings are not correlated with the variability of dividend changes. The quality rankings are not uniformly correlated with mean portfolio returns or mean dividend changes, nor is the relationship between quality and mean earnings changes strong. Finally, quality rankings are related to firm size and return on equity. However, relationships between quality and leverage are discernible only at the extremes.     

Industry momentum strategies and autocorrelations in stock returns

In this study, we examine the sources of profits to momentum strategies of buying past winner industry portfolios and selling short past loser industry portfolios. We decompose the profit into (1) own-autocovariances in industry portfolio returns, (2) cross-autocovariances among industry portfolio returns, and (3) cross-sectional dispersion in mean portfolio returns. Our empirical results show that the industry momentum effect is mainly driven by the own-autocorrelation in industry portfolio returns, not by return cross-autocorrelations or by cross-sectional differences in mean returns. Indeed, the industry momentum strategy generates statistically significant profits only when own-autocorrelations are positive and statistically significant. The evidence is consistent with several behavioral models (e.g. Journal of Financial Economics 45 (1998) 307; Journal of Finance 53 (1998) 1839; Journal of Finance 54 (1999) 2143) that suggest positive own-autocorrelations in stock returns and hence the price momentum.     

Information Uncertainty and Post-Earnings-Announcement-Drift

Abstract:  We examine whether rational investor responses to information uncertainty (IU) explain properties of and returns to the post-earnings-announcement-drift (PEAD) trading anomaly. Consistent with a rational learning explanation, we find that: (1) unexpected earnings (UE) signals that are characterized as having greater IU have more muted initial market reactions; (2) extreme UE portfolios are characterized by securities with higher IU than non-extreme UE portfolios; and (3) within the extreme UE portfolios, high IU securities are more prevalent and earn larger abnormal returns than low IU securities. Further tests show that prior evidence of greater PEAD profitability for higher idiosyncratic volatility securities is explained by the greater information uncertainty associated with these securities.     

Are Investors Rational? Choices among Index Funds

S&P 500 index funds represent one of the simplest vehicles for examining rational behavior. They hold virtually the same securities, yet their returns differ by more than 2 percent per year. Although the relative returns of alternative S&P 500 funds are easily predictable, the relationship between cash flows and performance is weaker than rational behavior would lead us to expect. We show that selecting funds based on low expenses or high past returns outperforms the portfolio of index funds selected by investors. Our results exemplify the fact that, in a market where arbitrage is not possible, dominated products can prosper.     

EMPIRICAL EVIDENCE ON THE IMPACT OF THE BID-ASK SPREAD ON THE CHARACTERISTICS OF CRSP DAILY RETURNS

It is widely recognized that Center for Research in Security Prices (CRSP) returns may differ from “true” returns because of the bid-ask effect. Using a large sample of New York Stock Exchange and American Stock Exchange securities, I confirm a discernible bid-ask effect, the magnitude and importance of which decrease with the security's price level (increase with the spread). I find volatility estimates using CRSP returns to be greater than those based on quote returns. However, market model properties, such as β and R², are generally unaffected. Bid-ask effects are clearly apparent in event studies, but because of certain offsetting effects commonly used test statistics remain unaffected. Low-priced stocks (below $2.00) do not conform to these patterns. Finally, the evidence raises the possibility that the existing literature on filter rule tests may underestimate the bid-ask spread component of transaction costs.     

Can exchange traded funds be used to exploit industry and country momentum?

There is overwhelming empirical evidence on the existence of country and industry momentum effects. This line of research suggests that investors who buy country and industry portfolios with relatively high past returns and sell countries and industries with relatively low past returns will earn positive risk-adjusted returns. These studies focus on country and industry indexes that cannot be traded directly by investors. This raises the question of whether country and industry momentum effects really can be exploited by investors or whether they are illusionary in nature because they exist only on non-tradable assets. We analyze the profitability of country and industry momentum strategies using actual price data on exchange traded funds (ETFs). We find that over the sample periods during which these ETFs were traded, an investor would have been able to exploit country and industry momentum strategies with an excess return of about 5 % per annum. These returns cannot be explained by unconditional exposures to the Fama–French factors. The daily average bid-ask spreads on ETFs are substantially below the implied break-even transaction cost levels. Hence, we conclude that investors who are not willing or able to trade individual stocks may use ETFs to benefit from momentum effects in country and industry portfolios.