Combining value and momentum: evidence from the Nordic equity market

This is the first article that explores the recently proposed average ranking approach for the value and momentum strategy in the Nordic equity market offering an exceptional experimental environment. Our results indicate that in the Nordic stock markets, the value anomaly offered excess returns in the 1993–2017 sample period only when small stocks were a part of the portfolio, whereas the momentum effect is strong and significant, irrespective of size. Interestingly, our findings also indicate that the negative correlation between value and momentum seems to be driven by growth stocks: Winner stocks that are value stocks generated 1.66% per month on average, whereas winner stocks that are growth stocks exhibit virtually the same average payoff. On the other hand, the spread between value and growth stocks that are loser stocks is on average 0.97% per month.     

Cross-sectional and time-series momentum returns: are Islamic stocks different?

We search for differences in both unconditional and conditional momentum returns of Islamic and Non-Islamic stocks and test implications of competing behavioural theories that aim to explain momentum returns. Our results show that there is no significant difference in momentum returns between Islamic versus Non-Islamic stocks with respect to both cross-sectional (CS) and time-series (TS) momentum strategies even when we condition momentum returns on market dynamics, information uncertainty and idiosyncratic volatility. We also find that the TS strategy outperforms (underperforms) the CS strategy in market continuations (transitions) consistent with the recent evidence in the U.S. market.

Furthermore, we find that CS and TS strategies of both Islamic and Non-Islamic stocks are profitable only when the market continues in the same state consistent with overconfidence driving momentum returns of both Islamic and Non-Islamic stocks.     

The relation between asset growth and the cross-section of stock returns: Evidence from the Chinese stock market

This study examines the effect of firm investment on stock returns by using data on the Chinese stock market. We find that stocks with higher investment experience lower future returns and there is an obvious investment effect in the Chinese stock market. The investment effect is stronger for firms that have higher cash flows, lower debt or for state-owned firms. We further explore the relation between investment and returns over the 3 years around portfolio formation. The results show that the high investment firms earn higher returns than low investment firms before portfolio formation; however the high investment firms earn lower returns than low investment firms after portfolio formation, such evidence is supportive of investor's overreaction explanation. Additionally, the stock returns don't necessarily decrease after investment, and the stock returns don't significantly positively correlate with firm profitability or book-to-market, so the result don't support risk-based explanation. Overall, both our portfolio sort and two-stage cross-sectional regression analysis show that behavioral finance theories are better than risk-based theories in explaining the investment anomaly. Evidence from the Chinese stock market provides a useful perspective to understand the debate on the investment anomaly.     

Investor Overreaction: Evidence That Its Basis Is Psychological

Probably no subject in recent financial literature has generated more controversy than whether investors behave rationally in pricing stocks, or whether they overreact to market information, resulting in prices being too high or too low. Although the efficient market hypothesis states that, with minor exceptions, securities are rationally priced, repeated evidence has been presented of predictable over- and underreactions. This evidence is based primarily on consistently higher returns for out-of-favor stocks and below-average returns for favored issues. The existence of overreaction in the marketplace, if it can be proven, is important to both investment decision-making and theory, and in more acute cases can be the major cause of financial bubbles and panics.

We present evidence of overreaction by showing that important fundamentals upon which securities prices depend demonstrate little movement in the face of major changes to the returns of favored and unfavored stocks. We can find no explanation other than psychological influences to account for this finding. The paper also provides evidence that over- and underreaction may be a part of the same process.     

Asset pricing with time-varying betas for stocks traded on S&P 500

This study uses a novel approach for capturing time variation in betas whose pattern is treated as a function of market returns. A two-factor model (TFM) is constructed using estimated coefficients of a nonlinear regression. The model is tested against the CAPM and the Fama and French three-factor model in the context of time series regressions. The used stocks are traded on S&P 500. The period spans from 1993 to 2011. The time series regression results depict the superiority of the TFM in explaining portfolio returns including momentum ones. We also provide evidence that the particular portfolios employed at the construction of the new model accommodate different fundamental characteristics and different risk levels.     

Investment horizon effect on asset allocation between value and growth strategies

How does the optimal risk exposure of assets change as their investment horizons increase? Does this impact investment portfolio decision-making, in particular, optimal asset allocation between value and growth strategies over various investment horizons? This paper adopts a new approach to address these questions by examining portfolio allocation between value and growth stocks over various investment horizons. This new approach is based on wavelet analysis, which decomposes the returns of a particular investment strategy across multiple investment horizons. The key empirical results show that the success of pursuing the value strategy (short-selling growth stocks and going long on value stocks) is impacted by the approach used to classify value and growth stock returns. We explore two common alternatives: Fama-French versus Standard & Poor's (S&P) 500/Barra portfolios. The results using Fama-French portfolios show that as the investment horizon increases, the optimal mean allocation of investors tilts heavily away from growth stocks, particularly for lower and moderate levels of risk aversion. Interestingly, for S&P 500/Barra portfolios the allocation weights between value and growth do not vary much.     

Momentum meets value investing in a small European market

In this paper, we investigate two prominent market anomalies documented in the finance literature – the momentum effect and value-growth effect. We conduct an out-of-sample test to the link between these two anomalies recurring to a sample of Portuguese stocks during the period 1988–2015. We find that the momentum of value and growth stocks is significantly different: growth stocks exhibit a much larger momentum than value stocks. A combined value and momentum strategy can generate statistically significant excess annual returns of 10.8%. These findings persist across several holding periods up to a year. Moreover, we show that macroeconomic variables fail to explain value and momentum of individual and combined returns. Collectively, our results contradict market efficiency at the weak form and pose a challenge to existing asset pricing theories.     

Liquidity and equity returns in Borsa Istanbul

We investigate the relationship between expected returns and liquidity measures in Borsa Istanbul. To do so, we gather a wide range of illiquidity measures that can be applied to the market. Firm-level cross-sectional regressions indicate that there is a positive relationship between various illiquidity measures and one- to six-month ahead stock returns. Findings of the article are robust after using different sample periods and controlling for well-known priced factors, such as market beta, size, book-to-market ratio and momentum. The portfolio analysis reveals that stocks that are in the highest illiquidity quintile earn 7.2%–19.2% higher risk-adjusted annual returns than those in the lowest illiquidity quintile. The illiquidity premium is stronger for small stocks and stocks with higher return volatility and it increases (decreases) during periods of extremely low (high) market returns.     

On Characteristics Momentum

This article investigates whether investors can benefit from information about equity style evolution. The study shows that portfolios formed by firm characteristics such as size, book-to-market, and/or dividend yield can be used to determine investment style dominance. Characteristics momentum, buying stocks with persistent in-favor characteristics and selling stocks with persistent out-of-favor characteristics, conveys valuable information about future stock returns. It is distinct and has longer-lasting effects than price or industry momentum in predicting future returns. In explaining the existence of characteristics momentum profits, this study highlights the importance of slow evolution of changes in firm characteristics. The lifecycle of investment styles can thus have predictive power for trend-chasing investors, who can potentially push up the price of stocks with an in-favor style, and depress the price of stocks with an out-of-favor style.     

Portfolio style: Return-based attribution using quantile regression

Return-based classification identifies a portfolio's style signature in the time series of its returns. Detection is based on a regression of portfolio returns on returns of factor mimicking indices. The method is easy to apply and does not require information about portfolio composition. Classification using least squares means that style is determined by the way factor exposure influences expected returns. We introduce regression quantiles as a complement to the standard analysis. The regression quantiles extract additional information from the time series of returns by identifying the way style affects returns at places other than the expected value. This allows discrimination among portfolios that would be otherwise judged equivalent based on conditional expectations. It also provides direct information about the impact of style on the tails of the conditional return distribution. Simple examples are presented to illustrate regression quantile classification.     

Riding the Wave of Sentiment: An Analysis of Return Consistency as a Predictor of Future Returns

This article analyzes the degree to which return consistency in the past predicts future returns. I show that consistency is a strong predictive measure for future stock returns. In a portfolio context, positively consistent stocks exhibit positive future risk-adjusted returns, and negatively consistent stocks exhibit negative future risk-adjusted returns. The results are economically and statistically significant over multiple subperiods. Also, odd return behavior persists for nearly two years after portfolio formation. Stocks that have been consistently positive (negative) for longer time horizons have higher (lower) risk-adjusted returns during the followingmonththan those thathavebeenconsistent for shorter time periods. Finally, high consistency enhances momentum when the two factors are allowed to interact. Thus, there appears to be strong path dependence in the momentum effect, and consistency in stock returns appears to be an important component of return predictability.     

Industry Herding and the Profitability of Momentum Strategies During Market Crises

The degree of industry herding is significantly related to the subsequent performance of winner and loser industries. While the herding effect on losers is not inconsistent with investors’ tendency to herd on negative information, the herding effect on winners reflects institutional demand for overpriced securities. An alternative momentum strategy based on the degree of herding within an industry significantly outperforms the conventional industry momentum strategy over the subsequent 1, 3, 6, and 12 months. The findings suggest that behavioral patterns could be utilized to generate enhanced momentum profits, even during market stress periods when the conventional momentum strategy performs poorly.     

Fuzzy possibilistic portfolio selection model with VaR constraint and risk-free investment

We propose a possibilistic portfolio model with VaR constraint and risk-free investment based on the possibilistic mean and variance, while assuming that the expected rate of returns is a fuzzy number. The model shows more clearly that, in the financial market affected by several non-probabilistic factors, risk-averse investors wish not only to reach the expected rate of returns in their actual investment, but also to assure that the maximum of their possible future risk is lower than an expected loss. Under the condition that the expected rate of returns is a normal distribution fuzzy variable, we proposed a theorem as the solution, and derive a crisp equivalent form of the possibilistic portfolio under constraints of VaR and risk-free investment. This model is an expansion of the fuzzy possibilistic mean–variance model by Zhang (2007). Finally, an empirical study is carried out using the data concerning some stocks of various industries listed at the Shanghai Stock Exchange. A conclusion is reached that the investors are able to choose a portfolio more suitable to them under the VaR constraint.     

Two-period trading sentiment asset pricing model with information

We present a dynamic asset pricing model with investor sentiment and information, which shows that the investor sentiment plays a systematic and important role in the asset prices and the information is gradually incorporated into prices. The model has an analytical solution to the sentiment equilibrium price. We find that sentiment trading quantity not only increases the market liquidity, but also causes the asset prices' overreaction if the intensity of sentiment demand is more than a constant value. Therefore, the continuing overreactions result in a short-term momentum and a long-term reversal. The model could offer a partial explanation to some financial anomalies such as price bubbles, high volatility, asset prices' overreaction and so on.     

Momentum in Taiwan: seasonality matters!

Previous studies suggest that momentum exists in international stock markets with the exception of Asia. Using a large data set of Taiwanese stocks, we show that momentum does exist, but it is restricted to the months following the deadline for annual statements. During the remaining months, a reverse momentum, or contrarian, strategy produces significant returns. These contrarian returns are particularly high during the national holidays linked to the Lunar New Year and the Lunar Moon Festival.     

投资者情绪、异质性与市场非理性反应

许多研究表明,我国证券市场反向策略在短期内获利性较为显著,而动量策略在长期内可以获得超额收益,即中国股市具有短期反应过度和长期反应不足的双重特征。这一现象不仅动摇了有效市场假说的理论基础,而且对现有的行为定价理论模型构成了强有力的挑战。本文尝试从投资者情绪和投资者异质性两个角度对这一异象进行解释。研究发现,在投资者情绪高涨(或低落)阶段,市场更容易反应过度(或反应不足);对于不同类型的投资者,他们的信息反应模式也不尽相同,各自主导了市场在短期内和在长期内的整体表现。这一发现为中国股市在市场非理性反应上所呈现的独有特征提供了很好的阐释。     

Idiosyncratic volatility and the cross-section of anomaly returns: is risk your Ally?

Due to arbitrage risk asymmetries, the relationship between idiosyncratic risk and expected returns is positive (negative) among overpriced (underpriced) stocks. We offer a new active anomaly-selection strategy that capitalizes on this effect. To this end, we consider 11 equity anomalies in the U.S. market for years 1963–2016. Buying (selling) long (short) legs of the anomaly portfolios with the highest idiosyncratic volatility produces monthly abnormal returns ranging from 0.97% to 1.14% per month, outperforming a naive benchmark that equally weights all the anomalies by 45–70%. The effect cannot be subsumed by any other established anomaly-return predictor, such as momentum or seasonality. The results are robust to many considerations, including different numbers of anomalies in the portfolios, subperiod analysis, as well as estimation of idiosyncratic risk from the alternative models and throughout different periods.     

The importance of fear: investor sentiment and stock market returns

The presence of investor sentiment pushes asset prices away from the equilibrium level justified by underlying fundamentals. While sentiment is not directly observable, identifying appropriate proxies and, quantifying the impact of sentiment on asset prices is an important topic. Asset prices that do not appropriately reflect fundamental values may result in inefficient allocation of capital – impacting portfolio allocation decisions and the cost of capital. Utilizing a number of sentiment proxies, over the period 1990–2015, we demonstrate a strong relationship between investor sentiment and stock returns that is consistent with theoretical explanations of sentiment. We determine that implied volatility index (VIX) is the preferred measure of sentiment in terms of improving model fit and adding explanatory power. Causality tests suggest that investor fear (VIX) drives returns across firm-size and value, and also across industry. We also illustrate that firms that are more subjective to value, or face limits to arbitrage, such as small-cap stocks, or those in the business equipment (technology) or telecoms industry, are most responsive to changes investor sentiment. Finally, we demonstrate that sentiment has a greater influence on market returns during recession, when sentiment is at its lowest ebb, and this is particularly true for those stocks most susceptible to speculative demand.     

The profitability of financial analysts’ recommendations: evidence from an emerging market

This article aims at measuring recommendation value on the Tunisian market and uses a hand-collected database of 6646 recommendations (2005–2009). We apply the methodology of calendar–time portfolio analysis. This consists of simulating a portfolio that would include stocks depending on the recommendations issued by financial analysts. In order to measure abnormal (or ‘excess’) returns, the raw return of the portfolio is then compared to the evolution of the stock index and to the prediction of the Capital Asset-Pricing Model. Some of the portfolios we build earn a positive significant excess risk-adjusted return of 1.19% per month. Beyond the results that are in line with the literature, we provide two original results. First, ‘sell’ signals are informative, whereas ‘buy’ signals are not. We suggest that it is related to large (small) firms having more ‘buy’ (‘sell’) recommendations and to the direction of the market trend over the period. Second, the fact that recommendation levels have more impact than recommendation changes is explained by the specific informational context on that market, which is that recommendations are systematically disclosed each month, whereas on other markets, recommendations are produced only when the analyst has some new information to disclose.     

Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach

We use regular vine (r-vine), canonical vine (c-vine) and drawable vine (d-vine) copulas to examine the dependence risk characteristics of three 20-stock portfolios from the retail, manufacturing and gold-mining equity sectors of the Australian market in periods before, during and after the 2008–2009 global financial crisis (GFC). Our results indicate that the retail portfolio is less risky than the manufacturing counterpart in the crisis period, while the gold-mining portfolio is less risky than both the retail and manufacturing sector portfolios. Both the retail and gold stocks display a higher propensity to yield positively skewed returns in the crisis periods, contrary to the manufacturing stocks. The r-vine is found to best capture the multivariate dependence structure of the stocks in the retail and gold-mining portfolios, while the d-vine does it for the manufacturing stock portfolio. These findings could be used to develop dependence risk- and investment risk-adjusted strategies for investment, rebalancing and hedging which more adequately account for the downside risk in various market conditions.