A Tale of Two Anomalies: Higher Returns of Low‐Risk Stocks and Return Seasonality

Prior studies have shown that low beta and low volatility stocks earn higher average returns than high beta and high volatility stocks, contradicting the prediction of the capital asset pricing model and the fundamental relationship between risk and return. In this paper, we demonstrate that this phenomenon is driven by the seasonality of stock returns. We show that the risk‐return tradeoff does hold in the nonsummer months, and that switching to a portfolio of low‐risk stocks in summer outperforms—both in terms of absolute and in risk‐adjusted returns—buy and hold strategies as well as the Sell in May strategy of switching to treasury bills in summer.     

Should investors include Bitcoin in their portfolios? A portfolio theory approach

Many papers in recent years have examined the benefits of adding alternative assets to traditional portfolios containing stocks and bonds. Bitcoin has emerged as a new alternative investment for investors which has attracted much attention from the media and investors alike. However relatively little is known about the investment benefits of Bitcoin and therefore this paper examines the benefit of including Bitcoin in a traditional benchmark portfolio of stocks and bonds. Specially, we employ data up to June 2018 and analyse the potential out-of-sample portfolio benefits resulting from including Bitcoin in a stock-bond portfolio for a range of eight popular asset allocation strategies. The out-of-sample analysis shows that, across all different asset allocation strategies and risk aversions, the benefits of Bitcoin are quite considerable with substantially higher risk-adjusted returns. Our results are robust to rolling estimation windows, the incorporation of transaction costs, the inclusion of a commodity portfolio, alternative indices, short-selling as well as two additional optimization techniques including higher moments with (and without) variance-based constraints (VBCs). Therefore, our results suggest that investors should include Bitcoin in their portfolio as it generates substantial higher risk-adjusted returns.     

Nonlinearity and Flight‐to‐Safety in the Risk‐Return Trade‐Off for Stocks and Bonds

We document a highly significant, strongly nonlinear dependence of stock and bond returns on past equity market volatility as measured by the VIX. We propose a new estimator for the shape of the nonlinear forecasting relationship that exploits variation in the cross‐section of returns. The nonlinearities are mirror images for stocks and bonds, revealing flight‐to‐safety: expected returns increase for stocks when volatility increases from moderate to high levels while they decline for Treasuries. These findings provide support for dynamic asset pricing theories in which the price of risk is a nonlinear function of market volatility.     

Asymmetric mean reversion of Bitcoin price returns

Non-linearity is characterised by an asymmetric mean-reverting property, which has been found to be inherent in the short-term return dynamics of stocks. In this paper, we explore as to whether cryptocurrency returns, as represented by Bitcoin, exhibit similar asymmetric reverting patterns for minutely, hourly, daily and weekly returns between June 2010 and February 2018. We identify several differences in the behaviour of Bitcoin price returns in the pre- and post-$1000 sub-periods and evidence of asymmetric reverting patterns in the Bitcoin price returns under all the ANAR models employed, regardless of the data frequency considered. We also present evidence indicating stronger reverting behaviour of negative price returns in terms of both reverting speed and magnitude compared to positive returns and evidence of positive serial correlation with prior positive price returns. Finally, we also investigated asymmetries in Bitcoin price return series' persistence by employing higher order ANAR models, finding evidence of a higher persistence of positive returns than negative returns, a result that further supports the existence of asymmetric reverting behaviour in the Bitcoin price returns.     

Trend‐Following Trading Strategies in U.S. Stocks: A Revisit

We show that previous findings regarding the profitability of trend‐following trading rules over intermediate horizons in futures markets also extend to individual U.S. stocks. Portfolios formed using technical indicators such as moving average or channel ratios, without employing cross‐sectional rankings of any kind, tend to perform about as well as the more commonly examined momentum strategies. The profitability of these strategies appears significant, both statistically and economically, through 2007, but evidence of profitability vanishes after 2007. Market‐state dependence, while clearly present, does not explain the post‐2007 reduction in returns to these strategies.     

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.     

Profitability of the CRISMA System: From World Indices to the Hong Kong Stock Market

Many studies show that the use of technical analysis can generate excess returns. We test the “CRISMA” technical trading rule introduced by [Pruitt and White J. Portfolio Managt. Spring, 1988, 55–58] on global equity indices and common stocks in Hong Kong. Out study shows that no excess returns could be found in indices except those in Asia. This validates the claims that the Asian stock markets are not as efficient as other stock markets and hence can be exploited by technical analysis. How does CRISMA perform on common stocks in Hong Kong? Generally speaking, CRISMA does not fair better than the buy and hold strategy. Further analysis reveals excess returns for stocks with very large turnover. This is consistent with other recent research on CRISMA conducted on US and UK stock markets. We also amend part of the original CRISMA rules to yield better performance: shrinking the moving average window sizes can increase both the number of trade signals and the excess returns. Therefore CRISMA can be made to work with some judicious choice of parameters, depending on the turnover.     

Risk,return and mean‐variance efficiency of Islamic and non‐Islamic stocks: evidence from a unique Malaysian data set

We find that Islamic stocks are more mean–variance efficient than non‐Islamic stocks and the market because they reduce risk of the same level of returns. We combine a unique Malaysian data set of individual Islamic stocks (as opposed to aggregate stock indices) since 1997 with a new method where we apply Islamic business activity and financial ratio screens to the universe of Malaysian stocks. Both data sets show that Islamic stocks have an annualised standard deviation that is on average 3.43–3.78 percent points lower compared to non‐Islamic stocks. This lower variance of Islamic stocks is exclusively driven by financial ratio screens.     

Downside beta and the cross section of equity returns: A decade later

This study reexamines the relation between downside beta and equity returns in the United States. First, we replicate the 2006 work of Ang, Chen, and Xing who find a positive relation between downside beta and future equity returns for equal‐weighted portfolios of NYSE stocks. We show that this relation doesn't hold after using value‐weighted returns or controlling for various return determinants. We also extend the original sample, add AMEX/NASDAQ stocks or utilize alternative downside beta measures and still find no downside risk premium. We focus on factor analysis results, persistence of downside beta, and various subsamples to understand the economic reasons behind the findings.     

On the Stability of the Cross‐Section of Expected Stock Returns in the Cross‐Section: Understanding the Curious Role of Share Turnover

In this paper, we shed further light on cross‐sectional predictors of stock return performance. Specifically, we explore whether the cross‐section of expected stock returns is robust within stock groups sorted by past monthly return. We find that the book/market and momentum effects are remarkably robust to sorting on past returns. However, share turnover is negatively related to future returns for stocks with abnormally low stock price performance in the recent past, but postively related to returns for well‐performing stocks. This casts doubt on the use of turnover as a liquidity proxy, but is consistent with turnover being a proxy for momentum trading which pushes prices in the direction of past price movements. Our results are robust to both NYSE/AMEX and Nasdaq stocks, and also robust to stratifying the sample by time period.     

Capital Structure and the Ex‐Dividend Day Return

We apply an option‐pricing framework to the ex‐dividend behavior of common stocks. The framework explains the observed behavior of positive returns on the ex‐dividend day and predicts that ex‐dividend day returns will be higher for firms with greater financial leverage. Empirical testing supports the prediction. In contrast to prior studies, we find that dividend‐capture activity has no significant impact on ex‐dividend behavior, and we offer an explanation based on the importance of tick intervals.     

Institutional Trade Persistence and Long‐Term Equity Returns

Recent studies show that single‐quarter institutional herding positively predicts short‐term returns. Motivated by the theoretical herding literature, which emphasizes endogenous persistence in decisions over time, we estimate the effect of multiquarter institutional buying and selling on stock returns. Using both regression and portfolio tests, we find that persistent institutional trading negatively predicts long‐term returns: persistently sold stocks outperform persistently bought stocks at long horizons. The negative association between returns and institutional trade persistence is not subsumed by past returns or other stock characteristics, is concentrated among smaller stocks, and is stronger for stocks with higher institutional ownership.     

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.     

Optimal Number of Stock Holdings in Mutual Fund Portfolios Based on Market Performance

Among the decisions that most mutual fund portfolio managers make is the number of stocks to hold. We posit that there is an optimal number of stocks for each mutual fund, reflecting the trade‐off between diversification benefits versus transactions and monitoring costs. We find a significant quadratic relation between number of stock holdings and risk‐adjusted returns for U.S. equity mutual fund portfolios during 1992–2000. Moreover, we find that changes in the number of stocks held over time are more highly correlated with mutual fund flows than with funds' investment returns.     

Sell‐Side Analyst Research and Stock Comovement

We document that a stock's price around a recommendation or forecast covaries with prices of other stocks the issuing analyst covers. The effect of shared analyst coverage on stock price comovement extends beyond analyst activity days. A stock's daily returns covary with the returns of other stocks with which it shares analyst coverage. These links between stock price comovement and shared analyst coverage are consistent with the coverage‐specific information we find in earnings forecasts; analysts who cover both stocks in a pair expect future earnings of the stocks to be more highly correlated than do analysts who cover only one stock from the pair. Collectively, our evidence indicates that analyst research produces coverage‐specific spillovers that raise price comovement among stocks that share analyst coverage. The strength of these spillovers is comparable to spillovers from broad industry and market information in analyst research.     

ROBUSTNESS OF THE HEADQUARTERS‐CITY EFFECT ON STOCK RETURNS

Recent studies report that U.S. firms headquartered near each other experience positive comovement in their stock returns, a finding suggestive of local biases in equity trading activity. We investigate the robustness of these findings and find that including additional pricing factors in models for monthly stock returns materially reduces the magnitude of the headquarters‐city effect in stock returns. Additionally, we find that an implicit null hypothesis of zero local return comovement is inappropriate as there is positive comovement between a stock's return and returns on portfolios of stocks from nonheadquarters cities, on average. Nevertheless, results benchmarked against estimates based on resampling methods indicate a significant and robust headquarters‐city effect in stock returns.     

News sentiment in the cryptocurrency market: An empirical comparison with Forex

We use high frequency intra-day data to investigate the influence of unscheduled currency and Bitcoin news on the returns, volume and volatility of the cryptocurrency Bitcoin and traditional currencies over the period from January 2012 to November 2018. Results show that Bitcoin behaves differently to traditional currencies. Traditional currencies typically experience a decrease in returns after negative news arrivals and an increase in returns following positive news whereas Bitcoin reacts positively to both positive and negative news. This suggests investor enthusiasm for Bitcoin irrespective of the sentiment of the news. This phenomenon is exacerbated during bubble periods. Conversely, cryptocurrency cyber-attack news and fraud news dampen this effect, decreasing Bitcoin returns and volatility. Our results contribute to the discussion on the nature of Bitcoin as a currency or an asset. They further inform practitioners about the characteristics of cryptocurrencies as a financial asset and inform regulators about the influence of news on Bitcoin volatility, particularly during bubble periods.     

Exchange‐Traded Fund Introductions and Closed‐End Fund Discounts and Volume

Exchange‐traded funds (ETFs), like closed‐end funds (CEFs), are managed portfolios traded like individual stocks. We hypothesize that the introduction of an ETF in an asset class similar to an existing CEF results in a substitution effect that reduces the value of the CEF's shares relative to that of its underlying assets. Our event studies show that upon the introduction of a similar ETF, CEF discounts widen significantly and relative volume declines significantly. Single‐equation and systems estimation models show that the widening in discounts and reduction in volume are related to returns‐based measures of the substitutability of ETFs for CEFs.     

Does Idiosyncratic Risk Really Matter?

Goyal and Santa‐Clara (2003) find a significantly positive relation between the equal‐weighted average stock volatility and the value‐weighted portfolio returns on the NYSE/AMEX/Nasdaq stocks for the period of 1963:08 to 1999:12. We show that this result is driven by small stocks traded on the Nasdaq, and is in part due to a liquidity premium. In addition, their result does not hold for the extended sample of 1963:08 to 2001:12 and for the NYSE/AMEX and NYSE stocks. More importantly, we find no evidence of a significant link between the value‐weighted portfolio returns and the median and value‐weighted average stock volatility.     

Analyst Forecasts and the Cross Section of European Stock Returns

We examine revisions to earnings forecasts by equity analysts and their role in predicting stock returns. We provide evidence that European stocks with net upward revised forecasts earn higher future returns than otherwise similar stocks. This effect is not concentrated in small stocks, stocks with low analyst coverage, or stocks with low book‐to‐market ratios. We find differences in the return continuation patterns of stocks with upward versus downward revisions, namely, bad news travels quickly, but good news travels slowly. This result is consistent with investors' attaching greater significance to poor earnings forecasts, but adopting a wait‐and‐see approach to good news.