Dynamic time series momentum of cryptocurrencies

This paper examines the momentum effect for twenty cryptocurrencies compared to the US stock market. For this purpose, we implement a dynamic modeling approach to define and test momentum periods that follow a formation period for interday and various intraday price levels. We find evidence that large proportions of the asset classes’ formation periods are followed by momentum periods, strongly supporting the momentum effect. In particular cryptocurrencies have significantly larger and longer momentum periods in all frequencies which we attribute to the lower derivability of their intrinsic value leading to a higher degree of noise traders in the market. A momentum trading strategy based on the identical approach outperforms a buy-hold strategy for both asset classes, while only cryptocurrencies have higher risk-adjusted returns and lower downside risks than a passive investment. We also find critical price levels during structural elements of the momentum period where the volatility shortly but intensively increases and consequently initiates a price impulse in the direction of the momentum.     

Autocorrelation,return horizons,and momentum in stock returns

In this study we examine Lewellen’s (Rev Financ Stud 15:533–563 2002) claim that momentum in stock returns is not due to positive autocorrelation as behavioral models suggest. Using portfolio-specific data, we find the autocovariance component of the momentum profit to be negative, suggesting no return continuations. However, we also find that the autocorrelations calculated from short-term (e.g., monthly) returns are quite different from long-horizon (e.g., annual) autocorrelations. While the first-order autocorrelations of 6– and 12-month returns tend to be negative, the autocorrelations across twelve lags in monthly returns of the industry, size, and B/M portfolios are in general positive. Our results show that these portfolios exhibit return continuations when returns are measured on a monthly basis. Therefore, our finding appears to be consistent with the behavioral models, which suggest positive autocorrelation in stock returns.     

Loss from the chasing of MAX stocks: Evidence from China

We evaluate the implications of the MAX effect in the Chinese financial market. First, the MAX effect prevails in China: A zero-cost MAX strategy, which goes long (short) stocks with the highest (lowest) maximum daily return in the prior month, generates significant losses over the full sample period. Second, further analysis on firm characteristics confirms that the MAX stocks exhibit lottery-like features, and the (negative) performance of the MAX strategy varies over time and is related to investor sentiment. Third, the MAX effect gets weaker after the introduction of short-selling in 2010. Finally, we document that there exists a reversed MAX effect among mutual funds, because a similarly implemented MAX strategy generates significant positive risk-adjusted returns among equity funds in China.     

基于极值分布理论的VaR与ES度量

本文应用极值分布理论对金融收益序列的尾部进行估计,计算收益序列的在险价值VaR和预期不足ES来度量市场风险。通过伪最大似然估计方法估计的GARCH模型对收益数据进行拟合,应用极值理论中的GPD对新息分布的尾部建模,得到了基于尾部估计产生收益序列的VaR和ES值。采用上证指数日对数收益数据为样本,得到了度量条件极值和无条件极值下VaR和ES的结果。实证研究表明:在置信水平很高(如99%)的条件下,采用极值方法度量风险值效果更好。而置信水平在95%下,其他方法和极值方法结合效果会很好。用ES度量风险能够使我们了解不利情况发生时风险的可能情况。     

Horse race of weekly idiosyncratic momentum strategies with respect to various risk metrics: Evidence from the Chinese stock market

This paper focuses on the horse race of weekly idiosyncratic momentum (IMOM) with respect to various idiosyncratic risk metrics. Using the A-share individual stocks in the Chinese market from January 1997 to December 2017, we first evaluate the performance of the weekly momentum based on raw returns and idiosyncratic returns, respectively. After that the univariate portfolio analysis is conducted to investigate the return predictability with respect to various idiosyncratic risk metrics. Further, we perform a comparative study on the performance of the IMOM portfolios with respect to various risk metrics. At last, we explore the possible explanations to IMOM as well as risk-based IMOM portfolios. We find that 1) there are prevailing contrarian effect and IMOM effect for the whole sample; 2) the negative relations exist between most of the idiosyncratic risk metrics and the cross-sectional stock returns, and better performance is linked to idiosyncratic volatility (IVol) and maximum drawdowns (IMDs); 3) additionally, the IVol-based and IMD-based IMOM portfolios exhibit better explanatory power to the IMOM portfolios with respect to other risk metrics; 4) finally, higher profitability of IMOM as well as IVol-based and IMD-based IMOM portfolios is found to be related to upside market states, high levels of liquidity and high levels of investor sentiment.     

中国股市的最大值效应

本文证实我国股市的投资者们长期存在对股票历史业绩的反应过度现象。我们发现历史上拥有最高收益率的股票在之后业绩都表现不佳。其主要原因是我国股市的投资者们在做投资选择时都遵循一条简单的规则:即在其他条件都相同的情况下,选择拥有最高的历史收益率的股票进行投资。集中投资使拥有最高的历史收益率的股票被过高评价,导致其后来的业绩表现要比那些拥有较低历史收益率的股票差。我们称之为"最大值效应"。通过使用Fama and Macbeth(1973)横断面回归分析方法,我们确认了"最大值效应"要比CAPM理论,Blitz and Pim van Vliet(2007)发现的"波动性效应"等更为有效地解释我国股市横断面股票收益率。     

Top performing banks: the benefits to investors

In this study, we examine whether superior accounting performance as reported in the annual ABA Banking Journal Top Performing Banks survey translates into higher investor returns. We observe that the announcement effect is more pronounced during the early years of the survey. For the entire survey period and for later sub-periods in which bank holding companies (BHCs) are ranked based on return on equity (ROE), we observe statistically-significant superior holding period returns against both the S&P 500 index and in some cases a matched sample. These results include raw and risk-adjusted returns as well as buy and hold abnormal returns (BHARs). We obtain similar results after controlling for the market return, size, book-to-market ratio, and momentum factors.     

Risk spillovers between cryptocurrencies and traditional currencies and gold under different global economic conditions

This paper applies a Diagonal BEKK model to investigate the risk spillovers of three major cryptocurrencies to ten leading traditional currencies and two gold prices (Spot Gold and Gold Futures). The daily data used are from 7 August 2015 to 15 June 2020. The dataset is analyzed in its entirety and is also subdivided into four distinct subsets in order to study and compare the patterns of spillover effects during economic turmoil, such as the 2018 cryptocurrency crash and the COVID-19 pandemic. The results reveal significant co-volatility spillover effects between cryptocurrency and traditional currency or gold markets, especially during the whole sample period and amid the uncertainty raised by COVID-19. The capabilities of cryptocurrency are time-varying and related to economic uncertainty or shocks. There are significant differences between normal and extreme markets with regard to the capabilities of cryptocurrency as a diversifier, a hedge or a safe haven. We find the significant co-volatility spillover effects are asymmetric in most cases especially during the COVID-19 pandemic period, which means the negative return shocks have larger impacts on co-volatility than positive return shocks of the same magnitude. Evidently, cryptocurrencies and traditional currencies or gold can be incorporated into financial portfolios for financial market participants who seek effective risk management and also for optimal dynamic hedging purposes against economic turmoil and downward movements.     

The cross section of Chinese commodity futures return

This paper investigates the cross-section of expected commodity futures returns in China using a large panel of 13 individual factors. We find that 6 out of 13 individual factors produce positive and significant returns. To aggregate the information among these factors, we apply not only the traditional Fama-MacBeth regression (FM), but also a set of alternative methods, including the forecast combination method (FC), principal component analysis (PCA), principle component regression (PCR) and partial least squares (PLS). It turns out that PLS outperform other methods in forecasting the cross-section of Chinese expected futures returns. The equally weighted combination of 5 methods produces an even higher annualized return and lower standard deviation compared to each single method. The investigation of factor importance reveals that the skewness (SKEW) factor is more important than other factors in predicting expected futures returns in Chinese markets.     

Technology transactions,announcement effect,and reversal: Dissecting an anomaly

We examine the short term stock price performance of firms that acquire or sell technology rights. We find significant positive announcement-period abnormal returns to the acquirers and sellers. However, the price increases reverse during the subsequent twenty trading days. These quick fortune reversals cannot be attributed to methodology; they prevail in the late 1970s through the 2000s, in bear and bull stock markets, and in both high and low technology industries. Upon splitting the sample into two subsamples comprised each of stocks with either pre-announcement price run-up or decline; we find that the abnormal return reversal is confined to the latter subsample. Stocks that witness price run-up prior to the announcement do not reverse to original prices but lose the momentum right after the announcement-period. We believe this is caused by the combination effect of the momentum prior to-and the impact of the announcement.     

Intraday return predictability in the cryptocurrency markets: Momentum,reversal, or both

This paper reports evidence of intraday return predictability, consisting of both intraday momentum and reversal, in the cryptocurrency market. Using high-frequency price data on Bitcoin from March 3, 2013, to May 31, 2020, it shows that the patterns of intraday return predictability change in the presence of large intraday price jumps, FOMC announcement release, liquidity levels, and the outbreak of the COVID-19. Intraday return predictability is also found in other actively traded cryptocurrencies such as Ethereum, Litecoin, and Ripple. Further analysis shows that the timing strategy based on the intraday predictors produces higher economic value than the benchmark strategy such as the always-long or the buy-and-hold. Evidence of intraday momentum can be explained in light of the theory of late-informed investors, whereas evidence of intraday reversal, which is unique to the cryptocurrency market, can be related to investors’ overreaction to non-fundamental information and overconfidence bias.     

Capital market reactions to the passage of the Financial Services Modernization Act of 1999

The Financial Services Modernization Act of 1999, also known as the Gramm-Leach-Bliley Act (GLBA), removed most of the remaining barriers between financial companies. Stock market reactions to the passage of GLBA vary across financial sectors and company size. Specifically, we find negative returns for foreign banks, thrifts and finance companies; insignificant returns for banks; and positive returns for investment banks and insurance companies. Additionally, larger nondepository firms have higher returns. The return variation reflects resolution of uncertainty surrounding the final provisions of GLBA, competitive pressures, and expectations of future business combinations. Potential gains from business combinations may arise from economies of scope, market power, and/or from an implicit extension of government guarantees to banking affiliates.     

Recent evidence on the short-term and long-term performance persistence of emerging-market mutual fund returns

This paper analyzes the performance persistence of US-based emerging-market mutual funds. We use a sample of 275 actively managed funds between July 1989 and December 2020 and regress their returns on emerging-market benchmark portfolios. On average, the funds had a significant negative alpha. Contrary to some earlier evidence, we document that the short-term consistency is entirely driven by losses of underperforming funds. The return spread between the short-term winners and losers generates a significant positive alpha that can be fully explained by the momentum in emerging-market stocks. We find no evidence of any long-term regularities. Our findings show that the observed funds exhibit very similar behavior to their developed-market counterparts and may contribute to resolving some inconsistencies in the earlier results.     

Happiness sentiments and the prediction of cross-border country exchange-traded fund returns

This research examines whether social media (Twitter) happiness sentiment and country-level happiness sentiment indices predict cross-border ETF returns. To account for complicated associations between happiness sentiment and ETF returns, we use a quantile regression approach and find that Twitter and trading market (U.S.) happiness sentiments are strong predictors of future ETF returns, for which both have far greater predictive power than those of their home countries. Home country happiness indices exhibit asymmetric impacts across quantiles, suggesting the importance of trading country (U.S.) and Twitter happiness sentiments. Higher U.S. and home countries’ freedom to make life choices, absence of corruption perception, and confidence in national government precede higher ETF returns, while U.S. GDP, social support, health life expectancy, positive affect, and negative affect precede lower (abnormal) returns. We find that higher return quantile country ETFs provide a safe haven for U.S. investors during a U.S. bear market.     

Anomalies in emerging markets: The case of Mexico

In this article we explore the relationship between 19 of the most common anomalies reported for the US market and the cross-section of Mexican stock returns. We find that 1-month stock returns in Mexico are robustly predicted only by 3 of the 19 anomalies: momentum, idiosyncratic volatility, and the lottery effect. Momentum has a positive relation with future 1-month returns, while idiosyncratic volatility and the lottery effect have a negative relation. For longer horizons of 3 and 6 months, only the 3 most important factors in the US market predict returns: size, book-to-market, and momentum.     

Sudden equity price declines and the flight-to-safety phenomenon: additional evidence using daily data

Using daily data we show sudden, extreme declines in the U.S. stock market for crash dates to lead to a capital preserving (as opposed to strategic or tactical) reallocation to government debt securities. In most cases we find flight-induced reallocation reverses direction within one day of a crash. However, for the 1987 world crash we find increased and persistent return volatility in both equity and bond returns lasting up to five days following this dramatic decline in world equity prices. Like previous research in this area, we find equity crashes alter long-run stock/bond return correlations and lead to increased stock and bond return volatility. Finally, we describe the somewhat unique stock and bond correlation adjustments triggered by the 9/11 attack and the impact this event had on the behavior of U.S. equity investors?? flight-to-safety reaction.     

Evolution of price effects after one-day abnormal returns in the US stock market

This paper provides a comprehensive analysis of price effects after one-day abnormal returns and their evolution in the US stock market, using Dow Jones Index over the period 1890–2018. We utilise several statistical tests and econometric methods (the modified cumulative abnormal return approach, regression analysis with dummy variables, R/S analysis (Hurst, 1951), and the trading simulation approach). The results suggest that a strong momentum effect between 1940 and 1980 after a day of positive abnormal returns was present in the US stock market, and it was exploitable for profit. However, after the 1980s this has since disappeared. Overall, price effects after one-day abnormal returns during the analysed period tend to be unstable in terms of their strength and direction (momentum or contrarian effect). Nowadays, the evidence for the price effects after one-day abnormal returns in the US stock market is weak. Our results, therefore, are consistent with the Adaptive Market Hypothesis (Lo, 2004).     

The market versus the analyst: Biases and predictive ability

Using the end of the quiet period (QPX) after an IPO as a venue for testing, we examine the long-run predictive ability of analysts and the market. Not only do we find that the analysts are reasonably good at predicting returns for at least a year, we also find that the market in general is at least as good—even after adjusting for the analysts’ recommendations. Separating the QPX market reaction into retail-dominated versus institutional-dominated – based on trade size – we find consistent evidence that only institutional-dominated reactions are positively related to longer-run return. When we examine 5-year survival prediction, we again find that only the institutional-dominated QPX reaction is positively related to survivability. There was no evidence that analysts were able to predict 5 years survival.     

欧洲股票市场的规模和动因:基于不同β系数的资本资产定价模型实证研究

我们选用在13个欧洲股市上市的证券,形成规模和动因组合。我们不仅发现规模溢价的证据,还发现8个样本市场存在重大动因收益率。这些收益率可能不构成异常现象,因为它们与不同β值的资本资产定价模型一致。我们还发现,系统风险与经济周期有关。此外,研究结果显示,虽然规模和动因收益率显著,但是难以在中、短期利用它们,因为在我们的样本中只有极少年份它们的数值为正且很大。     

Indicator selection and stock return predictability

We propose a momentum-determined indicator-switching (MDIS) strategy, simple and effective, to improve the predictability of stock returns, which can effectively select predictors. Empirical results indicate that the stock return forecasts generated by the MDIS strategy are statistically and economically significant. And we find that super long-term momentum of predictability (SMoP) exists in predictive factors. That is, in a long period of time in the past, the best predictor among a series of factors has best prediction ability in the future. We also design restricted momentum-determined indicator-switching (RMDIS) strategy when considering economic constrain. It is robust for the prediction performance of this strategy using a series of extension and robustness test. Success of the RMDIS strategy is also seen in using technical indicators to forecast stock returns.