Quintile Portfolios Research Articles

The low-volatility effect in African frontier equity markets

ABSTRACT This study investigated the extent to which the low-risk anomaly is present in a pooled sample of nine African frontier equity markets from March 2004 to July 2023. Portfolio-level analysis was used to investigate the total stock returns of equally weighted quintile portfolios sorted on historical volatility. The presence of a monotonic relationship between historical volatility and subsequent returns was evaluated using monotonicity tests, controlling for possible mediating variables. The results revealed evidence of a statistically significant low-volatility premium, except during bull markets. These findings imply that investors can expect to earn higher returns by allocating to stocks with lower historical volatility, but only during bear markets. These results hold for realistic portfolio construction constraints, such as (il)liquidity and high transaction costs.

Salience theory, investor sentiment, and commonality in sentiment: Evidence from the Chinese stock market

Investors pay more attention to a stock when the absolute return difference between the stock and the market is substantial, and consequently investors overweight this salience attribute when assessing the expected payoff from the stock. We demonstrate that the salience theory measure, which reflects this phenomenon, serves as a reliable proxy for firm-level investor sentiment and that the aggregate salience theory measure effectively represents market investor sentiment in the Chinese stock market. Furthermore, our findings reveal that the quintile portfolio with salient upsides underperforms the one with salient downsides by 1.26% (1.19% after risk adjustment) per month from 2002 to 2021. Moreover, we illustrate that the investor sentiment component of the salience theory measure significantly contributes to the negative salience premium. Finally, we provide evidence that the commonality in sentiment is priced significantly and positively, even after we control for the salience theory measure, firm risk characteristics, and lottery characteristics.

Mutual fund value creation: Insights from the residual income model

Inspired by the residual income model used to assess firms’ value creation in the accounting field, we provide a new estimation approach to infer a fund's skills, value creation, and whether the value created by funds can predict future performance. Using a sample of 2069 active equity funds in China from 2011 to 2022, as predicted by this model, we find that the residual earnings of funds, which represent the value created through fund trading activities, are persistent. Additionally, we observe a strong and positive relationship between residual earnings and semi-year-ahead mutual fund abnormal returns. Specifically, the top quintile portfolio based on residual earnings outperforms the bottom quintile by 2.16 % abnormal returns per year. Furthermore, we note that Chinese mutual funds with higher residual earnings tend to be younger, smaller, and have substantial turnover. These findings are valuable for fund investors seeking to identify high-value funds.

Predicting returns using moving averages: the role of investor inattention

PurposeInvestors are inattentive to continuous information as opposed to discrete information, resulting in underreaction to continuous information. This paper aims to examine if the well-documented return predictability of the strategies based on the ratio of short-term to long-term moving averages can be enhanced by conditioning on information discreteness. Anchoring bias has been the popular explanation for the source of underreaction in the context of moving averages-based strategies. This paper proposes and studies another possible source based on investor inattention that can potentially result in superior performance of these strategies.Design/methodology/approachThe paper uses portfolio sorting as well as Fama-MacBeth cross-sectional regressions. For examining the role of information discreteness in the return predictability of the moving average ratio, the sample stocks are double-sorted based on the moving average ratio and information discreteness measure. The returns to these portfolios are computed using standard approaches in the literature. The regression approach controls for various well-known return predictors.FindingsThis study finds that the equally-weighted monthly returns to the long-short moving average ratio quintile portfolios increase monotonically from 0.54% for the discrete information portfolio to 1.37% for the continuous information portfolio over the 3-month holding period. This study observes a similar pattern in risk-adjusted returns, value-weighted portfolios, non-January returns, large and small stocks, for alternative holding periods and the ratio of 50-day to 200-day moving average. The results are robust to control for well-known return predictors in cross-sectional regressions.Research limitations/implicationsTo the best of the authors’ knowledge, this is the first paper to document the significant role of investor inattention to continuous information in the return predictability of strategies based on the moving average ratios. There are many underreaction anomalies that have been reported in the literature, and the paper's results can be extended to those anomalies in subsequent research.Practical implicationsThe findings of this paper have important practical implications. Strategies based on moving averages are an extremely popular component of a technical analyst's toolkit. Their profitability has been well-documented in the prior literature that attributes the performance to investors' anchoring bias. This paper offers a readily implementable approach to enhancing the performance of these strategies by conditioning on a straightforward measure of information discreteness. In doing so, this study extends the literature on the role of investor inattention to continuous information in anomaly profits.Originality/valueWhile there is considerable literature on technical analysis, and especially on the performance of moving averages-based strategies, the novelty of this paper is the analysis of the role of information discreteness in strategy performance. Not only does the paper document robust evidence, but the findings suggest that the investor’s inattention to continuous information is a more dominant source of underreaction compared to anchoring. This is an important result, given that anchoring has so far been considered the source of return predictability in the literature.

Activity of informed traders and stock returns

PurposeRecent studies suggested the ratio of option to stock volume reflected the private information. Informed traders were drawn to the options market for its leverage effect and relatively low transaction costs. Informed traders use different intervals of option moneyness to execute their strategies. The question is which types of option moneyness were traded by informed traders and what information was reflected in the market. In this study, the authors focused on this question and constructed a method for capturing the activity of informed traders in the options and stock markets.Design/methodology/approachThe authors constructed the daily measure, moneyness option trading volume to stock trading volume ratio (MOS), to capture the activity of informed traders in the market. The authors formed quintile portfolios sorted with respect to the moneyness option to stock trading volume ratio and provided the capital asset pricing model and Fama–French five-factor alphas. To determine whether MOS had predictive ability on future stock returns after controlling for company characteristic effects, the authors formed double-sorted portfolios and performed Fama–Macbeth regressions.FindingsThe authors found that the firms in the lowest moneyness option trading volume to stock trading volume ratio for put quintile outperform the highest quintile by 0.698% per week (approximately 36% per year). The firms in the highest moneyness option trading volume to stock trading volume ratio for call quintile outperform the lowest quintile by 0.575% per week (approximately 30% per year).Originality/valueThe authors first propose the measures, moneyness option trading volume to stock trading volume ratio, that combined with the trading volume and option moneyness. The authors provide evidence that the measures have the predictive ability to the future stock returns.

Investor Sentiment, Cross-sectional Stock Returns, and Short-Sales: Evidence From Korea

Purpose: This study investigates the return co-movements associated with investor sentiment shifts in the cross-sections under a setting where market-wide sentiment interacts with short-sale impediments.
 Design/methodology/approach: This study estimates the return sensitivity to market sentiment changes (sentiment beta) for each characteristic's portfolio by regressing the return of each quintile portfolio and various high-minus-low portfolios on the sentiment changes index. It examines whether these cross-sectionally different return co-movement patterns is more prevalent during good- than bad-sentiment periods by performing the same regression separately for the good- and bad-sentiment periods.
 Findings: The result shows that the returns of speculative stocks tend to co-move more strongly with sentiment changes than those of stable stocks, in the sense that speculative stocks have higher sentiment betas than stable stocks. The cross-sectional pattern in return co-movements becomes more pronounced during the good-sentiment period but disappears during the bad-sentiment periods.
 Research limitations/implications: This study elucidates the return co-movement behavior associated with investor sentiment changes under a setting where market-wide sentiment interacts with short-sale impediments. However, analyzing the relationship between the investment sentiment index and the short-selling activities is reserved for future research.
 Originality/value: The results provide important implications for investment strategies using investor sentiment in practice, and several suggestions for establishing investor protection policies in the highly individual-crowded market. This study will contribute to enhancing the stock market efficiency and price discovery.

Evidence of the Impact of Coskewness on the Low Risk Anomaly in European Stocks

This paper investigates the low risk anomaly, which suggests that less risky stocks outperform riskier ones. Focusing on the European stock market, the present study examines the influence of coskewness, a measure of asymmetry in stock returns with respect to the market return. Stocks are sorted into 2x5 quintile portfolios based on coskewness and beta volatility. Regression analysis using Fama-French three and five factor models reveals a significant low risk anomaly in the low coskewness category, where less risky portfolios consistently outperform riskier ones. However, as coskewness increases, the low risk anomaly weakens and loses significance. In the high coskewness category, less risky portfolios no longer consistently outperform riskier ones. In other words, accounting for coskewness significantly lowers the profitability of low risk and betting-against-beta strategies in Europe. These findings enhance the understanding of the relationship between risk and returns in the European market.

거래량과 가격정보에 따른 모멘텀과 주식수익률의 관계에 관한 연구

According to behavioral finance, investors make investment decisions by recognizing past information as useful information. Investment decisions based on past information cause an overreaction to stock prices. According to previous studies on the Korean stock market, momentum based on trading volume and price information has a significant positive influence on stock returns. In this study, the Korean stock market is divided into the securities stock market and the KOSDAQ market to investigate which market the existing results are due to. Furthermore, an empirical analysis is conducted on the irrational behavior of investors based on transaction volume and price information. The research method uses univariate portfolio analysis and multivariate portfolio analysis and divides the decile portfolio and the conditional 5th quintile portfolio based on the momentum substitution considering the transaction volume. It is checked whether the momentum based on past transaction volume and price information lasts for the next six months. As a result, in the securities market, it is confirmed that the momentum according to transaction volume and price information has a significant positive effect on stock returns, and these results are maintained even after considering firm characteristics. On the other hand, it is stated that momentum according to transaction volume and price information does not occur in the KOSDAQ market. It shows that the existing results are due to the securities stock market rather than the KOSDAQ market.

Is tail risk priced in the cross-section of Chinese mutual fund returns?

We investigate the pricing of tail risk in the cross-section of Chinese mutual fund returns using a sample of 2563 funds from 2007 to 2021. We document a strong and positive relationship between the time-varying tail risk beta and one-month-ahead mutual fund return, which is robust to various considerations. Specifically, the top tail risk quintile portfolio outperforms the bottom one by 1.85% per month. We also note that Chinese mutual funds with high tail risk loadings tend to be young, have high management fees, low fund flows, and substantial return volatility. However, unlike the U.S. market, fund size and managerial ownership do not directly relate to tail risk exposure in China.

A better model? Testing of Fama and French six-factor model in Pakistan

This study examines the performance of the Fama and French six factor model and the alternative six-factor model in explaining anomalous return patterns using a broad sample of the Pakistani stock market from 2000 to 2017. This study is the first to test the applicability of these models in Pakistan and their performance in explaining anomalous returns. There are 11 anomalies taken, which proved to be significant in the Pakistani market. The GRS test is used with other time-series measures to check the power of the given models in explaining one-way sorted quintile portfolios. The results reveal that both models provide an incomplete description of anomalous returns. However, the six-factor model seems to be dominant with no major exception as it can explain 5 out of 11 anomalous portfolios returns, while the alternative model can explain four anomalies. The findings recommend that investors use the six-factor model because of its dominancy. It further recommends the investors about how they can maximize their returns by taking a long and short position in anomalous portfolios. Lastly, it is suggested to search for a better model to explain Pakistani stocks returns and capture anomalous patterns

Stock Price Synchronicity and Technical Trading Effectiveness

This study investigates how stock price synchronicity, as a measure of how stock prices reflect market-wide information relative to firm-specific information, explains the profitability of moving-average (MA) technical trading. The stocks of firms with less synchronicity have more information uncertainty (IU) (i.e., they reflect less firm-specific information), which amplifies investors’ underreaction bias and the price momentum effect, and are therefore more profitable. Testing a sample of stocks listed on the Taiwan and the Taipei stock exchanges over July 1997-June 2021, we provide evidence consistent with the synchronicity-related IU hypothesis. For a low-synchronicity stock price quintile portfolio, the abnormal returns of an MA strategy relative to a buy-and-hold strategy as estimated by the Fama-French 5-factor model are high at 18.05% per annum and even higher for a high-synchronicity stock price quintile portfolio (9.22% per annum). The MA strategy for low-synchronicity stock price portfolio remains more effective even when considering equally and value-weighted portfolios, testing various sub-periods, considering alternative MA lag lengths and controlling for market variables such as liquidity, sentiment, economic policy uncertainty, and economic cycle.

Variance risk and the idiosyncratic volatility puzzle

We decompose the CBOE's VIX index into the variance risk premium (to proxy for risk aversion) and conditional variance of stock returns (to proxy for economic uncertainty). We show that the variance risk premium has relatively strong predictive power for the return spread between high and low idiosyncratic volatility (IVOL) quintile portfolios. Thus, investors demand a premium for variance risk, which reflects the uncertainty of the asset's return variance itself. The findings also indicate that higher levels of risk aversion and tense economic conditions help minimize the IVOL-return puzzle. Our results are robust using value-weighted and equal-weighted returns.

The pricing of skewness: Evidence from the Johannesburg Stock Exchange

ABSTRACT The historical skewness of stock return distributions could potentially affect future stock returns. Previous studies in developed markets have shown that investors prefer shares exhibiting positively skewed or ‘lottery-like’ payoff profiles. The higher demand for these shares results in a negative relationship between skewness and expected stock returns. This study investigates the extent to which asymmetrical returns are priced on the Johannesburg Stock Exchange over the period August 2002 to December 2019. Using portfolio-level analysis, this study analyses the returns of quintile portfolios sorted on past self-skewness. Risk-adjusted returns are evaluated against an equally weighted benchmark. In addition, the presence of a monotonic relationship between past self-skewness and future returns is tested with the monotonic relation test of Patton and Timmermann (2010), as well as the Wolak (1987, 1989) test. Unlike the developed market evidence, this study finds evidence of a positive relationship between past self-skewness and future returns on the JSE. This effect remains even after controlling for size and industry effects. The results suggest that positive skewness is rewarded on a risk-adjusted basis. Overall, the study provides insights for investors regarding the importance of considering the past asymmetry of stock return distributions in investment decision-making processes.

The Relationship Between Changes in Analyst Consensus Earnings Forecasts and Subsequent Share Returns on the Johannesburg Stock Exchange

Sell-side company analysts are most likely to be closest to a company’s financial health, will be privy to new information, and run models that process new information into meaningful expected changes to future earnings per share. Importantly, data vendors collate analyst’s individual Eps forecasts and publish consensus median Eps forecasts for the next three financial year-ends. A change in a median consensus forecast should be followed directly by a commensurate change in share price. We run a style analysis over 16 years, ranking quintile portfolios by the year-on-year change to Eps forecasts three months after portfolio formation. We find strong and consistent evidence that subsequent return is highly positively correlated with Eps upgrade. We vary both look-back and look-forward periods from one month to 12 months, confirming that three months forward, and 12 months backward, are optimal settings to maximise alpha. The effect is concentrated in the outer quintiles, with significant alpha generated when we move to decile portfolios.

Equity return anomalies in Turkish markets

Purpose- The purpose of this study is to investigate the predictive power of various anomalies in the cross-section of equity returns in Borsa Istanbul. Methodology- Covering a sample period between 1988 and 2018, this study implements univariate portfolio analyses. Specifically, each month, stocks are sorted into quintile portfolios based on one anomaly at a time. Next, the one-month-ahead equal- and value-weighted portfolio returns are calculated for each quintile to test whether the return spread between the extreme anomaly portfolios is economically and statistically significant. Findings- The findings using the whole sample document that market beta, firm size, lagged return and lottery demand have a significant and negative relation with future stock returns. In contrast, book-to-market ratio, investment and profitability have a strong positive relation with expected equity returns. Conclusion- All anomalies that are shown to predict U.S. equity returns are not documented in Turkey. Except for the investment anomaly, the directions of these anomalies are in line with the existing literature in the U.S.

Cash management and performance of index mutual funds

ObjetivoEl objetivo de este estudio es analizar la relación existente entre la gestión de efectivo y el desempeño consiguiente en las carteras de fondos de inversión indexados.Diseño/metodología/perspectivaUtilizando una muestra de 104 fondos que replican el índice bursátil Standard and Poor's 500 desde enero de 1999 hasta diciembre de 2016, se emplean carteras hipotéticas que invierten en fondos similares y diferentes análisis de regresión para analizar las diferencias en las rentabilidades ajustadas mensuales entre fondos indexados que gestionan diferentes niveles de efectivo en sus carteras. Por motivos de robustez, se tienen en cuenta diversos subperiodos y estados de mercado, así como otros factores exógenos y características de los fondos que afectan tanto al nivel de efectivo mantenido en la cartera indexada como al desempeño de la misma.ResultadosLos resultados muestran que los fondos indexados que gestionan niveles de efectivo más elevados experimentan un desempeño significativamente menor que otros fondos comparables que mantienen menores porcentajes de efectivo en sus carteras de inversión. Se obtiene una evidencia similar tras considerar diferentes subperiodos y momentos alcistas y bajistas de mercado, así como al considerar los gastos propios de cada fondo y otras variables que podrían afectar esta relación entre el rendimiento y el efectivo gestionado.Originalidad/contribuciónEste estudio contribuye a la literatura existente que analiza la gestión de efectivo en la industria de fondos de inversión. Más específicamente, los análisis se centran en carteras de fondos que replican un índice bursátil específico, dado que las diferencias en sus rendimientos en este tipo de fondos no deberían originarse por la evolución del mercado, sino a causa de factores relacionados con la gestión de sus carteras y otros componentes exógenos al índice bursátil. Estos hallazgos son de interés para gestores e inversores que pretendan mejorar sus rentabilidades ajustadas al invertir mediante una estrategia tan diversificada como un índice bursátil.

An Explainable Machine Learning Framework for Cross-Sectional Forecast-Based Fund Selection

Since the 1990’s the global hedge fund industry has seen a rapid expansion. Its growing presence in financial markets ranging from equity, fixed income and derivative markets has inextricably linked it to the broader financial industry, with larger funds effectively acting as a market makers and liquidity providers in many markets. For both academics and practitioners, the space has established itself as a key area of research given the vast heterogeneity of investment styles and the high mutability of the industry. In this thesis, a cross sectional fund selection approach which builds upon the paradigm of explainable machine learning is proposed in a fully systematic setting. Four fund performance metrics, Sharpe and Sortino ratios, fund alpha and its t-statistic, are used as the ranking and selection metric, at investable inter-regime forecast horizons of 24 and 36 months. We find that quintile portfolios constructed from machine learning and deep learning approaches outperform linear models and benchmark portfolios constructed exclusively based on historical realizations of the forecast metric, in terms of absolute and risk-adjusted performance. We find that the extreme quintile portfolios realize a high (resp. low) value of the performance metric employed as forecast metric in model training. We find forecasting on the Sortino ratio to yield the most consistent overall performance, and find particular benefit in employing machine learning methods for bottom quintile fund selection (consistent identification of under-performers) in the case of forecasting on fund alpha. Explainability, achieved via the use of SHAP values further serves the purpose of outlining feature importance both at the aggregate and the individual fund level. At the aggregate level, all methods agree on a subset of statistically consistent predictors across investment style and forecast horizon; with discernible relevance of predictors constructed from interactions of fund returns with nowcasters, and management quality indicators. This consistency enables a discretionary fund selection process to be complemented by model forecasts and SHAP value-based feature importance delineations. There is thus evidence that proposed approach may be valuable for a discretionary fund manager looking to incorporate machine learning based signals into their selection process.

Lottery mindset, mispricing and idiosyncratic volatility puzzle: Evidence from the Chinese stock market

This study investigates the MAX effect regarding lottery mindset in the Chinese stock market. The MAX effect significantly affects stock returns through quintile portfolio and cross-sectional regression analyses. The most-overpriced stock groups, as categorized by mispricing index, show more support for the MAX effect. However, the idiosyncratic volatility (IVOL) effect continues regardless of consideration for the MAX effect, indicating that the MAX effect is not a source of the IVOL effect. Our results suggest that the MAX effect, which is highly relevant for overpriced stocks, might have information for determining stock price, and appears to be independent from information of the IVOL effect in the Chinese stock market.

The information content of the term structure of risk-neutral skewness

Abstract We seek to reconcile the debate about the price effect of risk-neutral skewness (RNS) on stocks. We document positive predictability from short-term skewness, consistent with informed-trading demand, and negative predictability from long-term skewness, consistent with skewness preference. A term spread on RNS captures different information from long- and short-term contracts, resulting in stronger predictability. The quintile portfolio with the lowest spread outperforms that with highest spread by 14.64% annually. The term structure of RNS predicts earnings surprises and price crashes. We extract the slope factor from RNS term structure, estimate its risk premium, and explore its relation with several macroeconomic variables.

Meet Me in the Middle – Central Clearing and Netting Efficiency in the Credit Default Swap Market

We study the effect of central clearing on netting efficiency in the CDS market. We examine the development of position data and netting efficiency using aggregate data from the Depository Trust and Clearing Corporation (DTCC). Our main finding is that gross outstanding positions in cleared contracts increase, whereas net outstanding positions increase only at a marginally significant level. Hence, central clearing decreases netting efficiency to a considerable extent. Furthermore, we analyze different quintile portfolios of CDS contracts according to pre-clearing netting efficiency. We find that only those contracts that were most efficiently netted bilaterally, decrease in netting efficiency after the introduction of central clearing. The negative effect of central clearing on netting efficiency is more pronounced for the first contracts that have been made clearing eligible.