Return Spread Research Articles

Adding Value to Value: Is There a Value Premium Among Large Stocks?

According to Fama and French's (2012) price-to-book sorts, there is no global value premium among large stocks. Two simple departures from their methodology restore such premium: sorting stocks based on price-to-earnings rather than price-to-book ratios, and using global rather than regional value breakpoints. The resulting global value premium among large stocks, measured as the return spread between top 30% and bottom 30% stocks, increases from 17 (t-stat=1.09) to 64 (t-stat=2.61) basis points per month. Using price-to-earnings computed from earnings estimates rather than historical earnings further sharpens the value effect among large stocks. Not confined to small stocks, the value premium remains a key topic in Finance. Because valuation ratios are not interchangeable, researchers should look beyond price-to-book when studying, or controlling for, the value effect.

Earnings Quality Measures and Excess Returns.

This paper examines how commonly used earnings quality measures fulfill a key objective of financial reporting, i.e., improving decision usefulness for investors. We propose a stock-price-based measure for assessing the quality of earnings quality measures. We predict that firms with higher earnings quality will be less mispriced than other firms. Mispricing is measured by the difference of the mean absolute excess returns of portfolios formed on high and low values of a measure. We examine persistence, predictability, two measures of smoothness, abnormal accruals, accruals quality, earnings response coefficient and value relevance. For a large sample of US non-financial firms over the period 1988–2007, we show that all measures except for smoothness are negatively associated with absolute excess returns, suggesting that smoothness is generally a favorable attribute of earnings. Accruals measures generate the largest spread in absolute excess returns, followed by smoothness and market-based measures. These results lend support to the widespread use of accruals measures as overall measures of earnings quality in the literature.

Persistence of ex-ante volatility and the cross-section of stock returns

We suggest a new measure of total ex-ante volatility (EAV) in stock returns, which includes traditional non-market (or idiosyncratic) risk and the unexpected component of market return. We find that the portfolio-level EAV measure exhibits strong predictive power for the cross-section of average returns during the post-1963 period. We demonstrate that (1) the persistence of EAV gives rise to economically significant spread in returns between value and growth stocks, and (2) the cross-sectional dispersion in stock returns is positively related to the estimated value of EAV. The benefit of the EAV measure is that it is countercyclical and contains relevant information about the time-variation in value premium.

Extreme Returns in Emerging Stock Markets: Evidence of a Max Effect in South Korea

We investigate the significance of extreme positive returns (MAX) in the cross-sectional pricing of stocks in South Korea. Our results provide important out-of-sample evidence of a strong negative MAX effect similar to that documented by Bali et al. (2011) in the US stock market. For equal-weighted portfolios, the difference between returns on the portfolios with the highest and lowest maximum daily returns is −1.87% per month. The corresponding difference in alpha is −1.41% per month. The results are robust to controls for size, value, skewness, momentum, short-term reversal and idiosyncratic volatility. We also sort the portfolios by the average of the five highest daily returns within the month and report return and alpha spreads of −2.21% and −2.01% per month, respectively. However, unlike in Bali et al. (2011), the MAX effect cannot reverse the idiosyncratic volatility effect in the South Korean stock market. Our results imply investor preference for high-MAX stocks, consistent with cumulative prospe...

A Market-Based Funding Liquidity Measure

In this paper, we construct a traded funding liquidity measure from stock returns. Using a stylized model, we show that the expected return of a beta-neutral portfolio, which exploits investors' borrowing constraints (Black (1972)), depends on both the market-wide funding liquidity and stocks' margin requirements. We extract the funding liquidity shock as the return spread between two beta-neutral portfolios constructed using stocks with high and low margin. Our return-based measure is correlated with other funding liquidity proxies derived from various markets. It delivers a positive risk premium, which cannot be explained by existing risk factors. Positive correlation also exists between the funding liquidity measure and market liquidity measures. Using our measure, we find that while hedge funds in general are inversely affected by funding liquidity shocks, some funds exhibit funding liquidity management skill and thus earn higher returns.

ELW pricing kernel and empirical risk aversion

This study examines the pricing kernel and empirical risk aversion implied by Korea’s equity-linked warrants (ELWs). The estimated pricing kernel is clearly time-varying and exhibits a monotonic decrease with the underlying return state, which is consistent with mainstream economic theories on marginal utility. The movement of empirical risk aversion captures the economic conditions reflecting the recent global and liquidity crises. Particularly, empirical risk aversion has a highly significant relationship with the overall stock market return and credit spread change.

When is Distress Risk Priced? Evidence from Recessionary Failure Prediction

Using firm fundamentals, we develop a forward-looking measure of systematic risk associated with corporate failure. Our measure is consistent with standard asset pricing theory and is equal to the ratio of probabilities of failure in recession to failure in expansion. We validate the measure using two predictions from a stylized model. First, for a given probability of failure, expected returns should increase in our measure. Second, the resulting spread in returns should be larger for more distressed stocks. We find support for both predictions. For stocks in the top quintile of distress, a median hedge portfolio based on our measure generates 10%-12% per annum, suggesting that our approach successfully extracts risk information from accounting data. Our findings have important implications for the literature on distress risk that, despite compelling theoretical arguments, finds little evidence of a distress risk premium. Instead, it documents the distress anomaly — a negative correlation between the probability of failure and future stock returns. Our results suggest that distress risk is priced. However, a firm’s risk exposure depends on the phase of the business cycle in which a firm is more likely to fail.

The Cost of Private Equity

Private equity (PE) has developed into a well-established asset class with strong growth in capital commitments over the last decades. Consequently, fund returns have decreased over time and investors have become more cost conscious. Based on a unique data set of 358 PE buyout funds with vintage years between 1983 and 2007, we analyze whether the maturing PE asset class has become less costly over time. We define costs as the difference between gross and net returns (return spread) and provide a spread benchmark useful for investors to evaluate a fund’s costliness. Next, we show that, in line with our expectations, return spreads have decreased over time. However, when we control for falling gross returns causing lower performance-based fees, surprisingly, the cost of PE investing has increased. We relate the higher costs to increased levels of dry powder due to swelling capital flows into the industry. We conclude that the PE industry is a victim of its own success, suggesting that investors in the asset class should consider a more anti-cyclical investment approach.

Estimation of future levels and changes in profitability: The effect of the relative position of the firm in its industry and the operating-financing disaggregation

In this paper we examine how the relative position of a firm's Return on Equity (ROE) in industries affects the predictability of the next-year ROE levels, and the ROE changes from year to year. Using Nissim and Penman breakdown into operating and financing drivers, the significant role of the industry factor is established, although changes in signs suggest subtle non-linear relations in the drivers. Our study avoids problems originating from negative signs by analyzing sorts and by making new regressions with disaggregated second-order drivers by signs. This way, our results provide evidence of some different patterns in the influence of the first-level drivers of ROE (the operating factor and the financing factor), and the second-level drivers (profit margin, asset turnover, leverage and return spread) on future profitability, depending on the industry spread. The results on the role of contextual factors to improve the estimation of future profitability remain consistent for small and large firms, although adding some nuances.

Media Coverage and Hedge Fund Returns

The authors classified news items about equity hedge funds over 1999–2008 into three source groups—general newspapers, specialized magazines, and corporate communications—and found that corporate-covered funds outperformed general-covered funds by about 11 percentage points annually. Investor fund flows, however, were not related to information sources, which suggests that the return spread is not fully understood by investors. The magnitude of this return spread reflects the extensive costs of processing information to generate alpha.

Labor Intensity, Risk and Return

I analyze the relationship between labor intensity -- the wages to revenue ratio -- and a firm's risk and book-to-market ratio in a production model. Under plausible parameters, labor intensive firms are riskier and exhibit higher book-to-market ratios than capital intensive firms. Covariance with the stochastic discount factor grows with labor intensity so the return spread between labor and capital intensive firms should explain the cross-section of stock returns. I provide evidence that labor intensive firms do appear riskier than capital intensive firms and that the spread between labor and capital intensive firms helps explain the cross-section of stock returns.

A Study to Examine Time-Varying Effectiveness of Stock Returns on Tehran Stock Exchange

The present study aims to examine the presence of various anomalies or 'calendar effects' in stock index returns by using the Tehran Stock Exchange (TSE) index during the period 2004-2010. The findings show that the weekend effect, the weekend effect within the monthly effect, the monthly effect, and seasonal effect are present in the return equations of GARCH(1,1), GARCH-M, and Modified GARCH(1,1) models. Analyzes the weekend effect, and also the weekend effect in the first half and the second half of the month; this study finds a weekend effect: Wednesday's returns are significantly greater than Saturday's returns. However, the spread of returns on Wednesday and Saturday will be vary between the first half and the second half of the month. There are also monthly effects on excessive returns in Farvardin (March 20- April 19), Mordad (July 22- August 21) and Shahrivar (August 22- September 21), and on negative returns in Mehr (September 22- October 21) and Esfand (February 19- March 19) in the Tehran Stock Exchange. In terms of the seasonal effect, the study reveals that the highest rate of return can be achieved in the summer, while the lowest rate is appeared in the winter.

An Impact of Illiquidity Risk for the Cross-Section of Nordic Markets

A new measure of illiquidity is proposed in this study and its pricing implication is tested for the four Nordic markets. To measure illiquidity we average across all stocks, a monthly frequency of those days, when the incidences of zero return and of no change in $/local exchange rate occur simultaneously. The advantages of estimating market-wide illiquidity in this manner are twofold. First, in comparison with other measures of illiquidity commonly proposed in the literature, this approach yields the maximum return spread between the most illiquid and liquid stocks. Second, this method establishes a link between returns and market-wide illiquidity risk, which is not found, when either illiquidity risk is estimated using other measures of illiquidity or when the market model is used.

Firm Characteristics and Empirical Factor Models: A Data-Mining Experiment

A three-factor model using the standardized-unexpected-earnings and cashflow-to-price factors explains 15 well-known asset pricing anomalies. Our data-mining experiment provides a backdrop against which such claims can be evaluated. We construct three-factor linear pricing models that match return spreads associated with as many as 15 out of 27 commonly used firm characteristics over the 1971-2011 sample. We form target assets by sorting firms into ten portfolios on each of the chosen characteristics and form candidate pricing factors as long-short positions in the extreme decile portfolios. Our analysis exhausts all possible 351 three-factor models, consisting of two characteristic-based factors in addition to the market portfolio. 65% of the examined factor models match a larger fraction of the target return cross-sections than the CAPM or the Fama-French three-factor model. We find that the relative performance of the complete set of three-factor models is highly sensitive to the sample choice and the factor construction methodology. Our results highlight the challenges of evaluating empirical factor models.

The Volatility Factor Structure

We show that firms' idiosyncratic volatility obeys a strong factor structure and that shocks to the common factor in idiosyncratic volatility (CIV) are priced. Stocks in the lowest CIV-beta quintile earn average returns 5.4% per year higher than those in the highest quintile. The CIV factor helps to explain a number of asset pricing anomalies. We provide new evidence linking the CIV factor to income risk faced by households. These three facts are consistent with an incomplete markets heterogeneous-agent model. In the model, CIV is a priced state variable because an increase in idiosyncratic firm volatility raises the average household's marginal utility. The calibrated model matches the high degree of comovement in idiosyncratic volatilities, the CIV-beta return spread, and several other asset price moments.

An Analysis of Temporal Relation between Monetary Conditions and Illiquidity Premium in Indonesia

The objective of this research is to find evidence of a systematic relation between monetary conditions and temporal variation in the price of liquidity in Indonesia. Specifically, following an expansive monetary policy shift, funding conditions improve and market-wide liquidity increases, which is especially beneficial for illiquid securities. The improved liquidity and funding conditions reduce the returns required for holding illiquid securities. Consequently, illiquid stocks experience relatively large price increases when monetary conditions become expansive; hence, the measured return spread between illiquid and liquid stocks expands substantially. Overall, the evidence supports the claim that the price of asset liquidity is dependent on monetary conditions.

Currency momentum strategies

We provide a broad empirical investigation of momentum strategies in the foreign exchange market. We find a significant cross-sectional spread in excess returns of up to 10% per annum (p.a.) between past winner and loser currencies. This spread in excess returns is not explained by traditional risk factors, it is partially explained by transaction costs and shows behavior consistent with investor under- and overreaction. Moreover, cross-sectional currency momentum has very different properties from the widely studied carry trade and is not highly correlated with returns of benchmark technical trading rules. However, there seem to be very effective limits to arbitrage that prevent momentum returns from being easily exploitable in currency markets.

Call Warrant Listing and the Behavior of its Underlying Spot Market: Some Evidence from Bursa Malaysia

This study investigates the call warrant listing impact on its underlying stock based on Malaysian stock market. The study indicates that call warrant listing has no significant impact on the return, volatility, and bid-ask spread of its underlying stock. However, its trading volume tends to be higher in the post event period. The results suggest that (1) the diversion of trade from spot to warrant market is nonexistent, (2) call warrant does not expand the opportunity set for investors, (3) it is fair to use historical data in volatility estimation for the purpose of asset pricing based on Malaysian context.

Empirical Asset Pricing for Tactical Asset Allocation

Tactical Asset Allocation is short-term deviation from a long-term portfolio allocation. Portfolio managers typically combine tactical asset allocation with their period rebalancing in order to add additional return that can justify management fees. Unfortunately, the frequency of tactical asset allocation prohibits the manager from using fundamental values since these characteristics change little from month to month. This paper proposes and tests a methodology for determining a pair of asset classes to overweight and underweight that will produce a positive return spread in the next period. The model utilizes investors’ preferences for certain return distribution characteristics and the short-term persistence of these characteristics to select the best spread. Twenty years of monthly return data from five asset classes (domestic equity, international equity, fixed income, REITs, and alternative investments) were selected to represent the asset allocation opportunities of midsize institutional investors.

Equity Issues and Return Volatility*

We show that the repurchaser–issuer return spread is stronger among stocks with high return volatility. Rational and behavioral theories predict that this finding is the product of risk volatility and sentiment volatility, respectively. However, our results are inconsistent with these theories as they currently stand. Loadings on standard risk factors do not follow the dynamics that would explain the return predictability related to issuance decisions. If we sort on a stock's beta with respect to the aggregate sentiment index of Baker and Wurgler (2006, J. Finance, 61, 1645–1680), which proxies for sentiment volatility, the results are weaker—economically and statistically—than when sorting on return volatility.