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Article
Publication date: 11 March 2021

Bei Chen and Quan Gan

This paper investigates how the gambling measure captures market bubble events, and how it predicts stock return and option return.

Abstract

Purpose

This paper investigates how the gambling measure captures market bubble events, and how it predicts stock return and option return.

Design/methodology/approach

This paper proposes a gambling activity measure by jointly considering open interest and moneyness of out-of-the-money (OTM) individual equity call options.

Findings

The new measure, CallMoney, captures excessive optimism during the dot-com bubble, the oil price bubble and the pre-GFC stock market bubble. CallMoney robustly and negatively predicts both OTM and at-the-money call option returns cross-sectionally. The option return predictability of CallMoney is stronger when stock price is further from its 52-weeks high, capital gains overhang is lower, and when information uncertainty of the underlying stock is higher. CallMoney also robustly and negatively predicts cross-sectional stock returns.

Originality/value

The gambling measure has the advantages of being economically intuitive, model-free, easy to measure. The measure performs more robustly than existing lottery measures with respect to option and stock return predictability and more reliably captures the overpricing of options and stocks. The work helps understanding the gambling related anomalies in equity option returns and stock returns.

Details

Review of Behavioral Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1940-5979

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Article
Publication date: 20 February 2017

Worawuth Kongsilp and Cesario Mateus

The purpose of this paper is to investigate the role of volatility risk on stock return predictability specified on two global financial crises: the dot-com bubble and…

Abstract

Purpose

The purpose of this paper is to investigate the role of volatility risk on stock return predictability specified on two global financial crises: the dot-com bubble and recent financial crisis.

Design/methodology/approach

Using a broad sample of stock options traded on the American Stock Exchange and the Chicago Board Options Exchange from January 2001 to December 2010, the effect of different idiosyncratic volatility forecasting measures are examined on future stock returns in four different periods (Bear and Bull markets).

Findings

First, the authors find clear and robust empirical evidence that the implied idiosyncratic volatility is the best stock return predictor for every sub-period both in Bear and Bull markets. Second, the cross-section firm-specific characteristics are important when it comes to stock returns forecasts, as the latter have mixed positive and negative effects on Bear and Bull markets. Third, the authors provide evidence that short selling constraints impact negatively on stock returns for only a Bull market and that liquidity is meaningless for both Bear and Bull markets after the recent financial crisis.

Practical implications

These results would be helpful to disclose more information on the best idiosyncratic volatility measure to be implemented in global financial crises.

Originality/value

This study empirically analyses the effect of different idiosyncratic volatility measures for a period that involves both the dotcom bubble and the recent financial crisis in four different periods (Bear and Bull markets) and contributes the existing literature on volatility measures, volatility risk and stock return predictability in global financial crises.

Details

China Finance Review International, vol. 7 no. 1
Type: Research Article
ISSN: 2044-1398

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Article
Publication date: 14 May 2018

Abdelmonem Oueslati and Yacine Hammami

This paper aims to investigate the performance of various return forecasting variables and methods in Saudi Arabia and Malaysia. The authors document that market excess…

Abstract

Purpose

This paper aims to investigate the performance of various return forecasting variables and methods in Saudi Arabia and Malaysia. The authors document that market excess returns in Saudi Arabia are predicted by changes in oil prices, the dividend yield and inflation, whereas the equity premium in Malaysia is predicted only by the US market excess returns. In both countries, the authors find that the diffusion index is the best forecasting method and stock return predictability is stronger in expansions than in recessions. To interpret the findings, the authors perform two tests. The empirical results suggest irrational pricing in Malaysia and rationally time-varying expected returns in Saudi Arabia.

Design/methodology/approach

The authors apply the state-of-the-art in-sample and out-of-sample forecasting techniques to predict stock returns in Saudi Arabia and Malaysia.

Findings

The Saudi equity premium is predicted by oil prices, dividend yield and inflation. The Malaysian equity premium is predicted by the US market excess returns. In both countries, the authors find that the diffusion index is the best forecasting method. In both countries, predictability is stronger in expansions than in recessions. The tests suggest irrational pricing in Malaysia and rationality in Saudi Arabia.

Practical implications

The empirical results have some practical implications. The fact that stock returns are predictable in Saudi Arabia makes it possible for policymakers to better evaluate future business conditions, and thus to take appropriate decisions regarding economic and monetary policy. In Malaysia, the results of this study have interesting implications for portfolio management. The fact that the Malaysian market seems to be inefficient suggests the presence of strong opportunities for sophisticated investors, such as hedge and mutual funds.

Originality/value

First, there are no papers that have studied the return predictability in Saudi Arabia in spite of its importance as an emerging market. Second, the methods that combine all predictive variables such as the diffusion index or the kitchen sink methods have not been implemented in emerging markets. Third, this paper is the first study to deal with time-varying short-horizon predictability in emerging countries.

Details

Review of Accounting and Finance, vol. 17 no. 2
Type: Research Article
ISSN: 1475-7702

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Article
Publication date: 1 January 2006

Kathryn A. Wilkens, Jean L. Heck and Steven J. Cochran

The purpose of this study is to investigate the relationship between predictability in return and investment strategy performance. Two measures that characterize…

Abstract

Purpose

The purpose of this study is to investigate the relationship between predictability in return and investment strategy performance. Two measures that characterize investment strategies within a mean‐variance framework, an activity measure and a style measure, are developed and the performance of alternative strategies (e.g. contrarian, momentum, etc.) is examined when risky asset returns are mean reverting.

Design/methodology/approach

Returns are assumed to follow a multivariate Ornstein‐Uhlenbeck process, where reversion to a time‐varying mean is governed by an additional variable set, similar to that proposed by Lo and Wang (1995). Depending on its parameterization, this process is capable of producing an autocorrelation pattern consistent with empirical evidence, that is, positive autocorrelation in short‐horizon returns and negative autocorrelation in long‐horizon returns.

Findings

The results, for four uninformed investment strategies and assuming that returns are generated by a simple univariate Ornstein‐Uhlenbeck process, show that the unadjusted returns from the contrarian (momentum) strategy are greater than those from the other strategies when the mean reversion parameter, α, is greater than (less than) one. The results are expected, given the relationship between α and the first‐order autocorrelation in returns. The risk level (measured by either the standard deviation of returns or beta) of the contrarian strategy is the lowest at essentially all levels of mean reversion and the risk‐adjusted returns from the contrarian strategy, measured by the both the Sharpe and Treynor ratios, dominate those from the other strategies.

Research limitations/implications

In future research, a number of issues not considered in this study may be investigated. The style measure developed here can be used to determine whether the results obtained hold when an informed, mean‐variance efficient active strategy is employed. In addition, the performance of both the informed and uninformed strategies may be examined under the assumption that the risky return process follows a multivariate Ornstein‐Uhlenbeck process. This work should provide findings that facilitate the separation of fund risk due to dynamic strategies from that due to time‐varying expected returns.

Practical implications

The methodology used here may be easily extended to consider a number of important issues, such as the frequency of portfolio rebalancing, transactions costs, and multiple asset portfolios, that are encountered in practice.

Originality/value

The approach used here provides insight into how predictability affects the relative performance of tactical investment strategies and, thus, may serve as a basis for determining the magnitude and persistence in autocorrelation required for active investment strategies to yield profits significantly different from those of passive strategies. In this sense, this study may have appeal for both academics and investment professionals.

Details

Managerial Finance, vol. 32 no. 1
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 28 September 2020

Satish Kumar, Riza Demirer and Aviral Kumar Tiwari

This study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market…

Abstract

Purpose

This study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market, size, book-to-market and momentum factors via bivariate cross-quantilograms.

Design/methodology/approach

This study makes use of the bivariate cross-quantilogram methodology recently developed by Han et al. (2016) to analyze the predictability patterns across the oil and stock markets by focusing on various quantiles that formally distinguish between normal, bull and bear as well as extreme market states.

Findings

The study analysis of systematic risk premia across the four regions shows that crude oil returns indeed capture predictive information regarding excess factor returns in stock markets, particularly those associated with market, size and momentum factors. However, the predictive power of oil return over excess factor returns is asymmetric and primarily concentrated on extreme quantiles, suggesting that large fluctuations in oil prices capture markedly different predictive information over stock market risk premia during up and down states of the oil market.

Practical implications

The findings have significant implications for the profitability of factor- or style-based active portfolio strategies and suggest that the predictive information contained in oil market fluctuations could be used to enhance returns via conditional strategies based on these predictability patterns.

Originality/value

This study contributes to the vast literature on the oil–stock market nexus from a novel perspective by exploring the effect of oil price fluctuations on the risk premia associated with the systematic risk factors including market, size, value and momentum.

Details

Studies in Economics and Finance, vol. 37 no. 4
Type: Research Article
ISSN: 1086-7376

Keywords

Content available
Article
Publication date: 13 November 2020

Silvio John Camilleri, Semiramis Vassallo and Ye Bai

This paper examines whether there are differences in the nature of the price discovery process across established versus emerging stock markets using a twenty-country sample.

Abstract

Purpose

This paper examines whether there are differences in the nature of the price discovery process across established versus emerging stock markets using a twenty-country sample.

Design/methodology/approach

The authors analyse security returns for traces of predictability or non-randomness using variance ratio tests, Granger-Causality models and runs tests.

Findings

The findings pinpoint at predictabilities which seem inconsistent with market efficiency, and they suggest that the inherent cause of predictability differs across groups.

Research limitations/implications

The authors present empirical evidence which may be used to attain a deeper understanding of the links between predictability and market efficiency, in view of the conflicting evidence in prior literature.

Practical implications

Whilst the pricing process in emerging markets may be hindered by delayed adjustments, in case of established markets it seems that there is a higher tendency for price reversals which could be due to prior over-reactions.

Originality/value

This study presents evidence of substantial differences in predictability across developed and emerging markets which was gleaned through the rigorous application of different empirical tests.

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Article
Publication date: 14 March 2016

Ming-Chieh Wang and Jin-Kui Ye

The purpose of this paper is to examine whether the conditionally expected return on size-based portfolios in an emerging market (EM) is determined by the country’s world…

Abstract

Purpose

The purpose of this paper is to examine whether the conditionally expected return on size-based portfolios in an emerging market (EM) is determined by the country’s world risk exposure. The authors analyze the degree of financial integration of 23 emerging equity markets grouped into five size portfolios using the conditional international asset pricing model with both world and domestic market risks. The authors also compare the model’s fitness on the predictability of portfolio returns by using world and EM indices.

Design/methodology/approach

This study investigates whether large-cap stocks are priced globally and whether mid- and small-cap stocks are strongly influenced by domestic risk factors. The authors first examine the predictability of large-, mid-, and small-cap stock portfolio returns by using global and local variables, and next compare the model fitness by using world and EM indices on the prediction of size-based stock returns. Finally, the authors test whether the world price of covariance risk is the same for different portfolios.

Findings

The authors find that the conditional expected returns of large-cap stocks should be priced by global variables. Mid- and small-cap stocks are influenced by domestic variables rather than global variables, and their returns are priced by local residual risks. The test of the conditional asset pricing model shows that the largest stocks have the smallest mean absolute pricing errors (MAE), and their pricing errors are lower in large markets than in small markets. Third, the EM index offers more predictability for the excess returns of mid- and small-cap stocks than the world market index, but the explanatory power of this index does not increase for large-cap stocks.

Originality/value

EMs in the past were known as segment markets, with local risk factors more important than global risk factors, suggesting significant benefits from adding EMs to global portfolios. It would be interesting to examine whether financial integration differs for various firm sizes in the markets.

Details

Managerial Finance, vol. 42 no. 3
Type: Research Article
ISSN: 0307-4358

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Article
Publication date: 29 November 2018

Satish Kumar

The purpose of this paper is to examine the significance of skewness in maximizing the investor utility using the daily data for eight sectors listed on the National Stock

Abstract

Purpose

The purpose of this paper is to examine the significance of skewness in maximizing the investor utility using the daily data for eight sectors listed on the National Stock Exchange of India.

Design/methodology/approach

The analysis is carried out in three different steps. In the first part, the author analyzes the monthly stock returns and the important financial ratios – price-to-book (PB) ratio, price-earnings (PE) ratio and dividend yield (DY). Second, the author tests the sector-wise return predictability using Westerlund and Narayan (2012) flexible generalized least squares estimator. Third, the author compares the mean–variance–skewness (MVS) utility function with the mean–variance (MV) utility function.

Findings

The author forecasts the sectoral stock returns using three financial ratios – PB ratio, PE ratio and DY – as predictors. The results indicate that sectoral stock returns are significantly predicted by these financial ratios. The author then formulates trading strategies by including skewness in the utility function and finds that the investor utility is high when the utility function includes skewness as opposed to when the skewness is excluded.

Originality/value

The author extends the MV utility function to the MVS utility function and shows that the Indian stock market is more profitable when the investor uses a MVS utility function which highlights the main contribution to the literature.

Details

International Journal of Emerging Markets, vol. 13 no. 5
Type: Research Article
ISSN: 1746-8809

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Article
Publication date: 30 September 2014

Silvio John Camilleri and Christopher J. Green

– The main objective of this study is to obtain new empirical evidence on non-synchronous trading effects through modelling the predictability of market indices.

Abstract

Purpose

The main objective of this study is to obtain new empirical evidence on non-synchronous trading effects through modelling the predictability of market indices.

Design/methodology/approach

The authors test for lead-lag effects between the Indian Nifty and Nifty Junior indices using Pesaran–Timmermann tests and Granger-Causality. Then, a simple test on overnight returns is proposed to infer whether the observed predictability is mainly attributable to non-synchronous trading or some form of inefficiency.

Findings

The evidence suggests that non-synchronous trading is a better explanation for the observed predictability in the Indian Stock Market.

Research limitations/implications

The indication that non-synchronous trading effects become more pronounced in high-frequency data suggests that prior studies using daily data may underestimate the impacts of non-synchronicity.

Originality/value

The originality of the paper rests on various important contributions: overnight returns is looked at to infer whether predictability is more attributable to non-synchronous trading or to some form of inefficiency; the impacts of non-synchronicity are investigated in terms of lead-lag effects rather than serial correlation; and high-frequency data is used which gauges the impacts of non-synchronicity during less active parts of the trading day.

Details

Studies in Economics and Finance, vol. 31 no. 4
Type: Research Article
ISSN: 1086-7376

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Article
Publication date: 4 November 2013

Saumya Ranjan Dash and Jitendra Mahakud

The purpose of this paper is to investigate the firm-specific anomaly effect and to identify market anomalies that account for the cross-sectional regularity in the Indian…

Abstract

Purpose

The purpose of this paper is to investigate the firm-specific anomaly effect and to identify market anomalies that account for the cross-sectional regularity in the Indian stock market. The paper also examines the cross-sectional return predictability of market anomalies after making the firm-specific raw return risk adjusted with respect to the systematic risk factors in the unconditional and conditional multifactor specifications.

Design/methodology/approach

The paper employs first step time series regression approach to drive the risk-adjusted return of individual firms. For examining the predictability of firm characteristics on the risk-adjusted return, the panel data estimation technique has been used.

Findings

There is a weak anomaly effect in the Indian stock market. The choice of a five-factor model (FFM) in its unconditional and conditional specifications is able to capture the book-to-market equity, liquidity and medium-term momentum effect. The size, market leverage and short-run momentum effect are found to be persistent in the Indian stock market even with the alternative conditional specifications of the FFM. The results also suggest that it is naï argue for disappearing size effect in the cross-sectional regularity.

Research limitations/implications

Constrained upon the data availability, certain market anomalies and conditioning variables cannot be included in the analysis.

Practical implications

Considering the practitioners' prospective, the results indicate that the profitable investment strategy with respect to the small size effect is still persistent and warrants close-ended mutual fund investment portfolio strategy for enhancing the long-term profitability. The short-run momentum effect can generate potential profits given a short-term investment horizon.

Originality/value

This paper provides the first-ever empirical evidence from an emerging stock market towards the use of alternative conditional multifactor models for the complete explanation of market anomalies. In an attempt to analyze the anomaly effect in the Indian stock market, this paper provides further evidence towards the long-short hedge portfolio return variations in terms of a wide set of market anomalies that have been documented in prior literature.

Details

Journal of Indian Business Research, vol. 5 no. 4
Type: Research Article
ISSN: 1755-4195

Keywords

1 – 10 of over 2000