A note on the turn of the month and year effects in international stock returns

This examination of the turn of the month (TOM) and turn of the year (TOY) effects in 50 international stock indices, for the period 1994–2006, characterises the degree that the effects are influenced by: (i) the gross domestic product of the economy, (ii) the sign of the return on the prior day (called the prior day effect), (iii) a temporal indicator and (iv) the Monday effect. These effects are assessed by the use of an estimated generalised least squares (EGLS) panel regression model incorporating panel-corrected standard errors. Three important results relating to the TOM and TOY effects are observed. When the prior day effect on control days is used as the reference and controls are made for market development and year, we find that: (i) there is a relatively enhanced return on all TOM days, (ii) there is a relatively enhanced return on good TOY days and (iii) returns of bad TOY days are not remarkable.     

Interaction of size,book‐to‐market and momentum effects in Australia

This study seeks to disentangle the effects of size, book‐to‐market and momentum on returns. Initial results show that each characteristic has a role in explaining returns, but that there is interaction between size and momentum, as well as between size and book‐to‐market. Three key findings emerge. First, the size premium is the strongest, particularly in the loser portfolios. Second, the value premium is generally limited to the smallest portfolios. Third, the momentum premium is evident for the large‐ and middle‐sized portfolios, but loser stocks significantly outperform winner stocks in the smallest size portfolio. When these interactions are controlled with multivariate regression, we find a significant negative average relation between size and returns, a significant positive average relation between book‐to‐market and returns, and a significant positive average relation between momentum and returns.     

Can tail risk explain size,book‐to‐market,momentum, and idiosyncratic volatility anomalies?

We examine the impact of tail risk on the return dynamics of size, book‐to‐market ratio, momentum and idiosyncratic volatility sorted portfolios. Our time‐series analyses document significant portfolio return exposures to aggregate tail risk. In particular, portfolios that contain small, value, high idiosyncratic volatility and low momentum stocks exhibit negative and statistically significant tail risk betas. Our cross‐sectional analyses at the individual stock level suggest that tail risk helps in explaining the four pricing anomalies, particularly size and idiosyncratic volatility anomalies.     

LOW PRICE, PRICE-EARNINGS RATIO, MARKET VALUE, AND ABNORMAL STOCK RETURNS

In this research, the individual and net effects of low price, low price/earnings (P/E) ratio, and small size on the risk-adjusted excess returns are investigated for the fourth quarter of 1975 to the fourth quarter of 1985. The entire sample is divided into quintiles, and the resulting portfolios are rebalanced at the end of each quarter. Low price, low P/E ratio, and small value portfolios did experience greater excess returns. By applying the experimental control technique, the net effect of stock price is significant after controlling the size. Similarly, the net effect of the market value is significant after the stock price is controlled. The net effect of the P/E ratio is insignificant after controlling either the stock price or the market value.     

Volume- and size-related lead-lag effects in stock returns and volatility: An empirical investigation of the Warsaw Stock Exchange

We analyze the autocorrelation structure of returns and volatility of stocks listed in the single auction system on the Warsaw Stock Exchange during the period January 1996 - October 2000. First, we find that size- and volume-related cross-autocorrelation in portfolio returns exists even after accounting for the portfolio's own-autocorrelation. Second, we find that size and volume leadership are independent from each other. Third, our results indicate slower adjustment of the small (low volume) portfolios to market-wide information that differs for up and down markets. We also find evidence for volatility spillovers between portfolio returns.     

Risk‐Adjusted Long‐Term Contrarian Profits: Evidence from Non‐S&P 500 High‐Volume Stocks

Can trading volume help unravel the long‐term overreaction puzzle? With portfolios of non‐S&P 500 NYSE stocks, we show that (1) both the high‐ and low‐volume (abnormal volume) contrarian portfolios earn a much higher market‐adjusted excess return than the normal‐volume contrarian portfolio, (2) however, when leverage‐induced risk is factored in, excess returns from contrarian portfolios with normal‐ and low‐volume stocks are insignificant, (3) only excess returns from high‐volume contrarian stocks are significant and cannot be explained by the time‐varying risk and return framework, and (4) such high‐volume, risk‐adjusted excess returns arise mainly from winner (glamour) stocks.     

Seasonality in outliers of daily stock returns: A tail that wags the dog?

We document significant intra-year seasonality in outliers of S&P500 daily rates of return. Controlling for outliers in dummy regressions reveals that both the January and Monday effects turn from insignificant to highly significant. Mean daily return on January doubles and becomes significantly higher than all other months of the year, and Monday's mean return turns significantly positive and higher than other days of the week. The recently documented Halloween effect turns significant only after controlling for outliers as June, August, and September turn out to be months with remarkably low rates of returns. Being random, outliers cannot serve as instrumental variables for designing trading rules, yet, their impact on options pricing through the increase in volatility, may be applied for profitable options strategies.     

The Weekend Effect, 'Reverse' Weekend Effect, and Firm Size

In this paper, we find a 'reverse%rsquo; weekend effect — whereby returns for Monday are positive and significantly greater than returns for the preceding Friday — in recent data for major stock indexes. We also find that, while a weak weekend effect exists in portfolios of smaller firms, the effect begins to diminish and weak 'reverse' weekend effect begins to appear in medium size firms. The 'reverse' weekend effect becomes strong and statistically significant in portfolios of large firms. The detection of a 'reverse' weekend effect in portfolios of large firms is a new finding in the literature.     

The impact of share price on seasonality and size anomalies in Australian equity returns

Given the high correlation between a firm's stock price and market capitalisation, it is possible that the well-documented size anomaly is masking a share-price effect. Using a seemingly unrelated regression model to accommodate contemporaneous correlation between portfolios, we estimate the separate effects of firm size and share price on returns to Australian equity portfolios. The analysis is also extended to estimate seasonal components of size and price effects. Our major findings are: (i) firm size and share price have significant and independent effects on portfolio returns averaged over all months, (ii) the familiar negative relation between size and returns is confirmed across all months, and (iii) the relation between share price and returns is negative in July and positive in all other months (with the exception of January where no price effect occurs). These findings, which are consistent across sub-periods and robust to method variations, highlight the need for future research to provide an economic foundation for the relation between average returns, size and price.     

Tracking down distress risk

This paper shows that exposure to aggregate distress risk is the underlying source of the premiums for the Fama-French size (SMB) and value (HML) factors. Using a unique data set of aggregate business failures of both private and public firms from 1926 to 1997, I build portfolios that track news about future firm failures. These tracking portfolios optimally hedge aggregate distress risk and earn a Capital Asset Pricing Model (CAPM) alpha of approximately −4% a year. Both HML and SMB predict changes in future failure rates. Small stocks have lower returns than large stocks and value stocks have lower returns than growth stocks when the market expects an increase in future failure rates. Finally, a two-factor model with the market and the tracking portfolio for aggregate distress as factors does as well as the Fama-French three-factor model in pricing the 25 size and book-to-market sorted portfolios.     

Conditional performance, portfolio rebalancing, and momentum of small-cap mutual funds

To assess the performance of small-cap stocks net of transaction costs, we analyze 165 actively managed small-cap oriented portfolios. Our analysis addresses three areas of interest: (i) performance net of transaction costs, (ii) the magnitude of trading costs incurred when rebalancing an actively managed portfolio, and (iii) the potential for momentum strategy profits when investing in small-cap stocks.Using conditional estimation, we find that small-cap funds have earned a significantly positive abnormal return of about 2% per year in the period January 1986 to December 2000. We also estimate the cost of January rebalancing to be 0.4% of portfolio value, a value that is significant for over 20% of the portfolios under study.Finally, after trading frictions are taken into account, we find evidence that small-cap portfolios exhibit significant return patterns, similar in nature to momentum patterns initially documented in a frictionless setting by [J. Finance 48 (1993) 65; J. Finance 56 (2001) 699]. Our findings support recent behavioral models, which attempt to explain these patterns. Consistent with the findings of Jegadeesh and Titman, we find that past “winners” continue to outperform in the next 12 months, followed by a performance reversal.     

Performance of technical analysis in growth and small cap segments of the US equity market

A large universe of technical trading rules applied to a set of technology industry and small cap sector portfolios over the 1995-2010 period yields superior predictability after adjusting for data snooping bias in the first half of the sample period and delivers statistically significant profits for a number of portfolios when the transaction cost is assumed to be of small to moderate size. Technical analysis is not able to outperform the buy-and-hold approach for any portfolio in the set in the second half of the sample period. The finding that the short-term return predictability becomes much weaker in the more recent period suggests that the underlying segments of the equity market have become more efficient over time. The fact that mechanical trading strategies have been futile after adjusting for data snooping bias for two samples of portfolios where technical analysis is most anticipated to succeed suggests that it is unlikely to have delivered abnormal returns in any other segment of the domestic equity market in the last decade.     

Australian evidence on the implementation of the size and value premia

This 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.     

Liquidity risk and stock returns around the world

The recent global financial crisis demonstrates that market liquidity is a prominent systematic risk globally. We find that local liquidity risk, in addition to the local market, value and size factors, demands a systematic premium across stocks in 11 developed markets. This local pricing premium is smaller in countries where the country-level corporate boards are more effective and where there are less insider trading activities. We also discover that global liquidity risk is a significant pricing factor across all developed country market portfolios after controlling for global market, value, and size factors. The contribution of this risk to the return on a country market portfolio is economically and statistically significant within and across regions.     

The Post-Reform Bid-Ask Spread Disparity between Nasdaq and the NYSE

We report further evidence of the difference in execution costs between Nasdaq and the NYSE before and after the 1997 market reforms. We find that informed trading costs are consistently higher on Nasdaq both before and after the reforms. In the pre‐reform period the Nasdaq‐NYSE disparity in bid‐ask spreads cannot be completely attributed to the difference in informed trading costs. However, in the post‐reform period the spread difference between these two markets becomes insignificant with the effect of informed trading costs controlled. Our findings are consistent with the contention that the reforms have largely reduced noninformation trading costs and dealers' rents.     

A conditional asset-pricing model with the optimal orthogonal portfolio

This paper employs a conditional asset-pricing model based on the optimal orthogonal portfolio approach to construct a factor portfolio that embodies all the latent factors important for pricing a given set of test assets. The advantage of this portfolio to the anomaly related mimicking portfolios is its ability to separate out the components of average return that are not related to the return covariation. The performance of this portfolio is evaluated against several conventional factors, using both cross-sectional and time-series regression approaches, as well as the Hansen and Jagannathan (1997) distance measure. Its strong out-of-sample results indicate that our suggested methodology may have important applications in risk management, portfolio selection and performance evaluation.     

REGULAR(IZED) HEDGE FUND CLONES

This article addresses the problem of portfolio construction in the context of efficient hedge fund investments replication. We propose a modification to the standard Sharpe “style analysis” by introducing a constraint on the asset weights 1‐norm and 2‐norm. This constraint regularizes the optimization problem, allows efficient selection of relevant factor's and has significant effects on the stability of the resulting asset mix and the risk–return characteristics of the replicating portfolio. The empirical results suggest that the norm‐constrained replicating portfolios exhibit significant correlations with their benchmarks, often higher than 0.9; have a fraction, which is about half to two‐thirds, of active positions relative to those determined through the standard method; and are obtained with turnover, which is in some instances about one‐fourth of that for the standard method.     

Long-run stock performance of German initial public offerings and seasoned equity issues

We estimate the long-run stock performance after initial public offerings (IPOs) in the German capital market with a larger sample than prior studies and alternative benchmarks (the equally and the value-weighted market portfolio, size portfolios and matching stocks). In addition we present the first results on the long-run performance after seasoned equity issues (SEOs) in Germany. We conclude that size portfolios and matching stocks are better benchmarks than market portfolios. Using buy‐and-hold abnormal returns, we estimate that German stocks involved in an IPO or in a SEO, on average, underperform a portfolio consisting of stocks with a similar market capitalization by 6% in three years. This is considerably less than the underperformance after IPOs and SEOs in the US market reported by Loughran and Ritter (1995) and the underperformance after IPOs in Germany reported by Ljungqvist (1997). We also show that the apparent underperformance of the 1988–1990 IPO cohort discussed by Ljungqvist (1997) disappears when the abnormal performance estimate is based on size instead of market portfolios.     

Using Four‐Moment Tail Risk to Examine Financial and Commodity Instrument Diversification

We consider the effect of higher moments on diversification, since most assets possess a potential for tail losses. In particular, we examine higher‐moment Value‐at‐Risk measures for individual instruments and diversified portfolios. We find that a naïve futures portfolio is consistently superior to common stock indexes. As few as ten randomly chosen instruments diversify away 85% of the unsystematic four‐moment tail risk. We also compare the two‐ and four‐moment tail risks for different size portfolios. Finally, the tail risk for naïve portfolios varies much less over time than other portfolios.     

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.