Financial integration and the price of world covariance risk: Large- vs. small-cap stocks

We investigate whether recent country-level evidence of global pricing is particular to large-cap stocks. Specifically, we examine cross-country return correlations and conduct asset pricing tests on three size-based stock portfolios for nine developed countries over the period from 1980 to 2004. We find that large-cap stocks realize significant comovements across countries, whereas small-cap stocks realize smaller average correlations (relative to both large-cap stocks and small-cap stocks across countries). More important, asset pricing tests suggest that while large-cap stocks are priced globally, global pricing is rejected for most small-cap stocks. Finally, the evidence indicates that financial integration deepened in recent years primarily for large-cap stocks. Overall, the results suggest that the global pricing pertains chiefly to large-cap stocks.     

Is presidential cycle in security returns merely a reflection of business conditions?

We confirm previous findings that both large-cap and small-cap stock returns in the US exhibit a presidential cycle pattern, i.e. returns are significantly higher in the last 2 years than in the first 2 years of the presidential term. We attempt to examine if this presidential cycle pattern can be explained away by the traditional business cycle proxies, namely the term spread (TERM), dividend yield (D/P), and default spread (DEF). Our motivation arises from the political business cycle theory that monetary and fiscal measures undertaken by presidents are usually translated into the business cycle. We find that the presidential cycle has explanatory power beyond business conditions proxies shown to be important in explaining stock returns. Tests of slope parameters show that stock returns are less sensitive to only the D/P during the last 2 years of the presidential term. The presidential cycle effect prevails even after controlling for the party in power and the incumbent versus nonincumbent presidents.     

A New Look at the Monday Effect

It is well documented that expected stock returns vary with the day-of-the-week (the Monday or weekend effect). In this article we show that the well-known Monday effect occurs primarily in the last two weeks (fourth and fifth weeks) of the month. In addition, the mean Monday return of the first three weeks of the month is not significantly different from zero. This result holds for most of the subperiods during the 1962–1993 sampling period and for various stock return indexes. The monthly effect reported by Ariel (1987) and Lakonishok and Smidt (1988) cannot fully explain this phenomenon.     

Are there Monday effects in stock returns: A stochastic dominance approach

We provide a test of the Monday effect in daily stock index returns. Unlike previous studies we define the Monday effect based on the stochastic dominance criterion. This is a stronger criterion than those based on comparing means used in previous work and has a well defined economic meaning. We apply our test to a number of stock indexes including US large caps and small caps as well as UK and Japanese indexes. We find strong evidence of a Monday effect in many cases under this stronger criterion. The effect has reversed or weakened in the Dow Jones and S&P 500 indexes post 1987, but is still strong in more broadly based indexes like the NASDAQ, the Russell 2000 and the CRSP.     

Style drift: Evidence from small-cap mutual funds

This paper documents that small-cap mutual funds allocate on average 27% of their portfolio to mid- and large-cap stocks. We find that larger and older small-cap funds are more likely to hold mid- and large-cap stocks, consistent with funds straying from their objective over time. Funds that invest heavily in mid- and large-cap stocks expose their investors to unanticipated risks but investors do not experience higher abnormal returns or performance persistence overall. These funds did outperform their peers by 3% annually in the most recent period between January 2003 and March 2010.     

A closer look at return predictability of the US stock market: evidence from new panel variance ratio tests

This paper examines the return predictability of the US stock market using portfolios sorted by size, book-to-market ratio and industry. We use novel panel variance ratio tests, based on the wild bootstrap proposed in this paper, which exhibit desirable size and power properties in small samples. We have found evidence that stock returns have been highly predictable from 1964 to 1996, except for a period leading to the 1987 crash and its aftermath. After 1997, stock returns have been unpredictable overall. At a disaggregated level, we find evidence that large-cap portfolios have been priced more efficiently than small- or medium-cap portfolios; and that the stock returns from high-tech industries are far less predictable than those from non-high-tech industries.     

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.     

Reversal of Monday returns

This paper elaborates an interesting aspect of the Monday anomaly: Monday returns are relatively more likely to reverse over the subsequent days. We document that, although the Monday low-return anomaly disappeared, the subsequent reversal of Monday returns remains robust to date. The reversals, measured over a five-day horizon, are pervasive across international stock markets, reasonably stable over time, significant following both positive and negative Monday returns, and not confined to extreme Monday returns. Trading strategies designed to exploit these reversals earn economic profits. We examine potential explanations for the reversal of Monday returns using trading flows data of investor types from Korea. All predictions of the Foster and Viswanathan [J. Finance, 1993, 48, 187–211] model are confirmed: volatility is higher, trading volume is lower, market depth is lower and price impact costs are higher on Mondays. The model implies lower price quality on Mondays, but does not specifically predict reversal of Monday returns. We show that the trading intensity of international/institutional investors is lower on Mondays. This appears to make the market relatively more susceptible to individual investors’ trading, which is negatively correlated with international/institutional investors. Thus, Monday returns are relatively more likely to reverse during the subsequent days of the week when institutional investors trade more aggressively.     

Short-term residual reversal

Conventional short-term reversal strategies exhibit dynamic exposures to the Fama and French (1993) factors. We develop a novel reversal strategy based on residual stock returns that does not exhibit these exposures and consequently earns risk-adjusted returns that are twice as large as those of a conventional reversal strategy. Residual reversal strategies generate statistically and economically significant profits net of trading costs, even when we restrict our sample to large-cap stocks over the post-1990 period. Our results are inconsistent with the notion that reversal effects are the result of trading frictions or non-synchronous trading of stocks and pose a serious challenge to rational asset pricing models.     

GOOD NEWS, BAD NEWS, VOLUME, AND THE MONDAY EFFECT

New evidence is presented on the nature of the Monday effect in stock market returns. Using stock returns for the years 1962-1986, the Monday effect is found to be confined to periods of negative market returns. Monday's returns are no different from other weekday returns in periods of positive returns. In addition, trading volume and the Monday effect are related. Monday's volume is lower than the other weekdays. When returns are compared controlling for trading volume, we find that the Monday effect is confined to negative return periods with above normal volume, which represent only two per cent of the sample period.     

New Findings Regarding Day-of-the-Week Returns over Trading and Non-Trading Periods: A Note

This paper decomposes daily close to close returns into trading day and non-trading day returns. We discover that all of the average negative returns from Friday close to Monday close documented in the literature for stock market indexes occurs during the non-trading period from Friday close to Monday open. In addition, average trading day returns (open to close) are identical for all days of the week. January/firm size/turn-of-the-year anomalies are shown to be interrelated with day-of-the-week returns.     

On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation

Recent studies in the empirical finance literature have reportedevidence of two types of asymmetries in the joint distributionof stock returns. The first is skewness in the distributionof individual stock returns. The second is an asymmetry in thedependence between stocks: stock returns appear to be more highlycorrelated during market downturns than during market upturns.In this article we examine the economic and statistical significanceof these asymmetries for asset allocation decisions in an out-of-samplesetting. We consider the problem of a constant relative riskaversion (CRRA) investor allocating wealth between the risk-freeasset, a small-cap portfolio, and a large-cap portfolio. Weuse models that can capture time-varying moments up to the fourthorder, and we use copula theory to construct models of the time-varyingdependence structure that allow for different dependence duringbear markets than bull markets. The importance of these twoasymmetries for asset allocation is assessed by comparing theperformance of a portfolio based on a normal distribution modelwith a portfolio based on a more flexible distribution model.For investors with no short-sales constraints, we find thatknowledge of higher moments and asymmetric dependence leadsto gains that are economically significant and statisticallysignificant in some cases. For short sales-constrained investorsthe gains are limited.     

Explaining Monday Returns

The Monday effect is reexamined using two stock indexes and a sample of 452 individual stocks that trade on the London Stock Exchange. The results based on conventional test methods reveal a negative average return on Monday. Extending the analysis to examine the effects of various possible influences simultaneously, the average Monday return becomes positive and does not differ significantly from the average returns of most other days of the week. Fortnight, ex‐dividend day, account period, (bad) news flow, trading activity, and bid‐ask spread effects are all controlled for. The results broadly support the trading time hypothesis.     

The Monday effect revisited: An alternative testing approach

This paper questions traditional approaches for testing the Monday effect of stock returns. We propose an alternative, multiple hypothesis testing approach based on the closure test principle which controls the multiple type I error. We consider the US, the UK and the German stock markets and test Monday related pairwise comparisons of daily expected stock returns, while the probability of committing any type I error is always kept smaller than a prespecified level α, for each combination of true null hypotheses. Overall, the new testing approach supports previous findings of a Monday effect for the 1970s and 1980s, in particular for the US and Germany, while it suggests that the Monday effect has vanished in the 1990s and 2000s in all three markets. The comparison of the closure test procedure, the traditional multiple t-test and the Bonferroni test, a classical multiple test procedure, shows that traditional testing may result in spurious significance while the Bonferroni test may sometimes be too conservative.     

Do large-cap exchange-traded funds perform better than their small-cap counterparts in extreme market conditions?

This study proposes a new threshold model that differentiates between the size and sign-dependent responses of large- and small-cap exchange-traded funds (ETFs) to changes in extreme market conditions. The asymmetric returns in extreme upsides, extreme downsides, and “in-between” markets are estimated using three sets of betas. Findings support the notion that small-cap ETFs in all seven countries fall more in extreme downturns than they rise in extreme upturns. By contrast, six out of nine large-cap ETFs climb up in upside more than they fall in downswing. Therefore, investors should be cautious when assigning excessive weights to small-cap ETFs in their portfolio.     

Financial Integration of Large- and Small-Cap Stocks in Emerging Markets

This study examines the financial integration of large- and small-cap stocks in twenty-three emerging markets to determine their degree of market integration with the world market. The international asset pricing model cannot be rejected for most large-cap stock portfolios, but it is rejected for small-cap stock portfolios. The findings also demonstrate that super-large-cap stocks have the fewest pricing errors and their global financial integration has increased in recent years. In sum, the empirical results indicate that global market integration is primarily associated with the super-large-cap stocks of large emerging markets.     

Is There a Size Effect in the Pricing of Stocks in the Chinese Stock Markets?: The Case of Bull Versus Bear Markets

Size effect studies generally suggest that a return premium exists for small firms. While the size effect has mostly disappeared in recent years in mature markets (e.g., US and UK), it remains mostly strong in developing markets. The purpose of this paper is to examine the relationship between firm size and excess stock returns in the Chinese stock markets, and to examine this effect in both a bull and bear market. No studies have previously examined these relationships in the Chinese markets. The results of the study indicate that a size effect exists in the Chinese stock markets over the 6-year period from 1998 to 2003. We find small firms have significantly greater excess returns than large firms. Moreover, small firms are found to have a stronger reaction to the direction of the market than large firms. Small firms have significantly greater positive excess returns than large firms during the bull market. However, small firms have significantly greater negative returns (using total market value), or no significant difference in returns (using float market value) during the bear market period.     

Is the Value Spread a Good Predictor of Stock Returns? UK Evidence

Abstract:  This paper explores the predictive ability of the value spread in the UK. I replicate the US analysis of Liu and Zhang (2007) using UK data. In addition, I extend their work by exploring the predictive ability of the book-to-market, market-to-book and value spread on other size and value investment strategies, namely: large-caps only; small-caps minus large-caps (SML); value stocks only; growth stocks only; value stocks minus growth stocks (VMG) and a market portfolio that includes all stocks. The results are consistent with Liu and Zhang (2007) on the value spread. The value spread shows no predictive power for portfolio returns. Therefore, I show that the predictive power of book-to-market and market-to-book spreads depend on the portfolio formation strategies and the relative proportion of small-cap, large-cap, value and growth stocks in the portfolio.     

The impact of Saturday trading on stock returns: Evidence from the Tokyo stock exchange January 1976 to January 1989

This paper examines the impact of TSE Saturday trading on daily TOPIX returns and TSE trading volume over the January 1976 to January 1989 period. Saturday trading is shown to have no significant impact on mean stock returns for the other days of the week. However, a significant shift in the pattern of Monday and Tuesday TOPIX returns is documented in the post-August 1986 period. This shift does not appear to be related to Saturday trading. TSE Saturday trading is found to have a significant impact on the variance of stock returns on surrounding days. In addition, trading volume is significantly lower on trading days surrounding Saturday trading. These findings are relevant to the timing of portfolio adjustment decisions.     

Weekend Effect, 'Reverse' Weekend Effect, and Investor Trading Activities

Abstract:   In this study, we document evidence of a 'reverse' weekend effect – whereby Monday returns are significantly positive and they are higher than the returns on other days of the week – over an extended period of eleven years (from 1988 to 1998). We also find that the 'traditional' weekend effect and the 'reverse' effect are related to firm size in that the 'traditional' weekend effect tends to be associated with small firms while the 'reverse' weekend effect tends to be associated with large firms. In addition, we find that during the period in which the 'reverse' weekend effect is observed, Monday returns for large firms tend to follow previous Friday returns when previous Friday returns are positive , but they do not follow the previous Friday returns when Friday returns are negative . Furthermore, we find that during the period in which the 'reverse' weekend effect is observed, Monday returns are positively related to the volume of medium‐size and block transactions, but negatively related to the volume of odd‐lot transactions.