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1
Kim, Soo-Hyun. "The Effect of Operation and Market Value Efficiency on the Korean Stock Market." Journal of Derivatives and Quantitative Studies 23, no. 1 (February 28, 2015): 29–40. http://dx.doi.org/10.1108/jdqs-01-2015-b0002.
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This paper investigates the relationship between output to input efficiency and stock return predictability in the Korean stock market. We measure the efficiency using Data Envelopment Analysis with independent outputs of sales and market value data. Sales efficiency measures the operational efficiency whereas market value efficiency measures the efficiency evaluated by the investors. Through our empirical analysis, it is found that low efficiency stocks in either measures tend to have higher future returns. However, if both efficiency measures are employed at the same time there exists a strong tendency that high operation efficient and low market value efficient stocks generate larger future returns. We find that DEA analysis for efficiency can process a cross-sectional stock return predictability in the Korean stock market.
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Qadri, Syed Usman, Naveed Iqbal, and Syeda Shamaila Zareen. "Stock Return Predictability and Market Efficiency in Pakistan; A Role of Asian Growing Economies of India and Malaysia." ANNALS OF SOCIAL SCIENCES AND PERSPECTIVE 2, no. 2 (November 24, 2021): 257–67. http://dx.doi.org/10.52700/assap.v2i2.95.
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The purpose of this study is to determine the predictability of the Pakistani stock market's one-day forward returns by utilizing lagged daily returns for Pakistan, India, and Malaysia from 2006 to 2016. The findings indicate that lagged Pakistani market returns significantly predict Pakistani one-day ahead market returns. However, the other two growing stock markets, India and Malaysia, show no association with one-day ahead market returns. Mostly, stock market behavior in the pre-2008 and post-2008 eras was the same, although industry return behaviour was different due to the economic crisis of 2008. However, the Pakistani stock market one-day ahead returns predict the own Pakistani lag returns due to an inefficient market and prices do not follow a random walk. As a result, investors and financial analysts can foresee and generate anomalous returns by using previous data and information.
Key words: Stock Market Returns Predictability, Stock Market crash, Market efficiency
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John Camilleri, Silvio, and Christopher J. Green. "Stock market predictability." Studies in Economics and Finance 31, no. 4 (September 30, 2014): 354–70. http://dx.doi.org/10.1108/sef-06-2012-0070.
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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.
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Limongi Concetto, Chiara, and Francesco Ravazzolo. "Optimism in Financial Markets: Stock Market Returns and Investor Sentiments." Journal of Risk and Financial Management 12, no. 2 (May 13, 2019): 85. http://dx.doi.org/10.3390/jrfm12020085.
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This paper investigates how investor sentiment affects stock market returns and evaluates the predictability power of sentiment indices on U.S. and EU stock market returns. As regards the American example, evidence shows that investor sentiment indices have an economic and statistical predictability power on stock market returns. Concerning the European market instead, investigation provides weak results. Moreover, comparing the two markets, where investor sentiment of U.S. market tries to predict the European stock market returns, and vice versa, the analyses indicate a spillover effect from the U.S. to Europe.
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Dhungana, Yub Raj. "Predictability of Stock Returns on the Dhaka Stock Exchange." Batuk 6, no. 2 (July 1, 2020): 87–96. http://dx.doi.org/10.3126/batuk.v6i2.34519.
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The study examines the predictability of index returns on the Dhaka stock market within the framework of the weak-form efficient market hypothesis using historical daily returns for a period of 1st June, 2014 to 29th May, 2020. The Jarque-Bera statistics test explored the return distribution of Dhaka Stock Exchange is non-normal. The random walk hypothesis (RWH) was tested using autocorrelation test, runs test, unit root tests(Augmented Dickey-Fuller (ADF) and, Phillip-Perron (PP) test) and variance ratio test. The results explored that all tests rejected the random walk hypothesis required by the weak-form efficient market hypothesis. This provides empirical basis to infer that the DSE is inefficient at weak-form and stock return can be predicted. The rejection of the RWH on a daily basis is possibly an indication that the weak-form inefficient characteristic of the DSE is not sensitive to return frequency.
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Shi, Huai-Long, Zhi-Qiang Jiang, and Wei-Xing Zhou. "Time-Varying Return Predictability in the Chinese Stock Market." Reports in Advances of Physical Sciences 01, no. 01 (March 2017): 1740002. http://dx.doi.org/10.1142/s2424942417400023.
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China’s stock market is the largest emerging market in the world. It is widely accepted that the Chinese stock market is far from efficiency and it possesses possible linear and nonlinear dependencies. We study the predictability of returns in the Chinese stock market by employing the wild bootstrap automatic variance ratio test and the generalized spectral test. We find that the return predictability vary over time and a significant return predictability is observed around market turmoils. Our findings are consistent with the Adaptive Markets Hypothesis (AMH) and have practical implications for market participants and policy makers. A predictability index can be constructed for each asset, which might help warn a crisis is in store, ease the development of the ongoing bubble, and stabilize the market.
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NE, Gyamfi, Kyei KA, and Gill R. "African Stock Markets and Return Predictability." Journal of Economics and Behavioral Studies 8, no. 5(J) (October 30, 2016): 91–99. http://dx.doi.org/10.22610/jebs.v8i5(j).1434.
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This article re-examines the return predictability of eight African stock markets. When returns of stocks are predictable, arbitrageurs make abnormal gains from analyzing prices. The study uses a non-parametric Generalised Spectral (GS) test in a rolling window approach. The rolling window approach tracts the periods of efficiency over time. The GS test is robust to conditional heteroscedasticity and it detects the presence of linear and nonlinear dependencies in a stationary time series. Our results support the Adaptive Market Hypothesis (AMH). This is because, indices whose returns were observed to be predictable by analyzing them in absolute form and therefore weak - form inefficient showed trends of unpredictability in a rolling window.
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Peovski, Filip, Violeta Cvetkoska, Predrag Trpeski, and Igor Ivanovski. "Monitoring Stock Market Returns." Croatian operational research review 13, no. 1 (July 12, 2022): 65–76. http://dx.doi.org/10.17535/crorr.2022.0005.
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Financial analysis plays a major role in investing the disposable income of various economic agents. Stock markets are predominantly made up of small investors with limited information and low capabilities for a suitable analysis. Researchers, as well as practitioners, are divided over the findings on the adequacy of technical analysis in investing. This paper examines the Markov chain process in the stock market to discover the essential links and probabilities for the stocks’ transition through three states of stagnation, growth, and decline (i.e., stagnant, bull, and bear markets). The subject of analysis is a randomly selected portfolio of 20 shares traded on the New York Stock Exchange. The data suggest that the portfolio relatively quickly, in four trading days, achieves equilibrium probabilities that allow a certain amount of predictability of future movements. At the same time, when analyzing the expected time intervals for the first transition, we found that the portfolio returns to a state of growth much faster than a decline. In addition, the results negate the basic habits of frequent trading, herding, and taking a short position in events of negative price fluctuations. Our research contributes towards observing regularities and stock market efficiency with a clear goal of improving expectations and technical analysis for small individual investors.
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Arfianto, Erman Denny, and Ivan Irawan. "Short Horizon Return Predictability di Pasar Modal Indonesia." Jurnal Pasar Modal dan Bisnis 1, no. 1 (September 2, 2019): 41–54. http://dx.doi.org/10.37194/jpmb.v1i1.7.
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Purpose- This study aims to examine the effect of effective spread, price impact, trading volume, stock prices, and volatility of returns on the predictability of short-term returns (short horizon return predictability).
Methods- This research offers a new approach perspective which is a market microstructure with intraday data to measure short horizon return predictability as an efficient market inversion. The sample in this study was 64 non-financial companies listed on the KOMPAS100 Index during October 2017-March 2018. Intraday data used using the 5-minute frequency obtained from Bloomberg. This study uses multiple linear regression analysis.
Finding- This study found that price impact, trading volume, stock prices, and volatility have a positive impact on the predictability of long-term returns. This study also found that effective spread does not have a significant impact on the predictability of short-term returns.
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Jacobsen, Ben, Ben R. Marshall, and Nuttawat Visaltanachoti. "Stock Market Predictability and Industrial Metal Returns." Management Science 65, no. 7 (July 2019): 3026–42. http://dx.doi.org/10.1287/mnsc.2017.2933.
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Maasoumi, Esfandiar, and Jeff Racine. "Entropy and predictability of stock market returns." Journal of Econometrics 107, no. 1-2 (March 2002): 291–312. http://dx.doi.org/10.1016/s0304-4076(01)00125-7.
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Rostagno, Luciano Martin, Gilberto De Oliveira Kloeckner, and João Luiz Becker. "Previsibilidade de Retorno das Ações na Bovespa: Um Teste Envolvendo o Modelo de Fator de Retorno Esperado." Brazilian Review of Finance 2, no. 2 (January 1, 2004): 183. http://dx.doi.org/10.12660/rbfin.v2n2.2004.1141.
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This paper examines the hypothesis of asst return predictability in the Brazilian Stock Market (Bovespa). Evidence suggests that seven factors explain most of the monthly differential returns of the stocks included in the sample. Within the factors that present statistically significant mean, two are liquidity factors (market capitalization and trading volume trend), three refer to price level of stocks (dividend to price, dividend to price trend, and cash flow to price), and two relate to price history of stocks (3 and 12 months excess return). Contradicting theoretical assumptions, risk factors present no explanatory power on cross-sectional returns. Using an expected return factor model, it is contended that stock returns are quite predictable. An investment simulation shows that the model is able to assemble portfolios with statistically significant higher returns. Additional tests indicate that the winner portfolios are not fundamentally riskier suggesting mispricing of assets in the Brazilian stock Market.
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Benjelloun, Hicham. "About stock markets predictability." Journal of Economics and Behavioral Studies 1, no. 1 (January 15, 2011): 26–31. http://dx.doi.org/10.22610/jebs.v1i1.218.
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We argue that the financial markets have a predetermined outcome. They behave deterministically but appear to follow random patterns. Stock prices have nothing to do with future expectations; they are a reflection of previous convictions coming from the confident investors. A financial crisis is the result of the lack of confidence that characterizes a market moments before the crisis. Stocks returns are perfectly correlated to each other and it is possible to obtain high gains consistently. Finally we provide a different way of assessing risk and suggest a method to sense future performances.
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Oueslati, Abdelmonem, and Yacine Hammami. "Forecasting stock returns in Saudi Arabia and Malaysia." Review of Accounting and Finance 17, no. 2 (May 14, 2018): 259–79. http://dx.doi.org/10.1108/raf-05-2017-0089.
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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.
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Hong, Harrison, and Jeremy C. Stein. "Disagreement and the Stock Market." Journal of Economic Perspectives 21, no. 2 (April 1, 2007): 109–28. http://dx.doi.org/10.1257/jep.21.2.109.
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A large catalog of variables with no apparent connection to risk has been shown to forecast stock returns, both in the time series and the cross-section. For instance, we see medium-term momentum and post-earnings drift in returns—the tendency for stocks that have had unusually high past returns or good earnings news to continue to deliver relatively strong returns over the subsequent six to twelve months (and vice-versa for stocks with low past returns or bad earnings news); we also see longer-run fundamental reversion—the tendency for “glamour” stocks with high ratios of market value to earnings, cashflows, or book value to deliver weak returns over the subsequent several years (and vice-versa for “value” stocks with low ratios of market value to fundamentals). To explain these patterns of predictability in stock returns, we advocate a particular class of heterogeneous-agent models that we call “disagreement models.” Disagreement models may incorporate work on gradual information flow, limited attention, and heterogeneous priors, but all highlight the importance of differences in the beliefs of investors. Disagreement models hold the promise of delivering a comprehensive joint account of stock prices and trading volume—and some of the most interesting empirical patterns in the stock market are linked to volume.
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Kumar, Satish, Riza Demirer, and Aviral Kumar Tiwari. "Oil and risk premia in equity markets." Studies in Economics and Finance 37, no. 4 (September 28, 2020): 697–723. http://dx.doi.org/10.1108/sef-03-2020-0059.
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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.
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Wang, Ming-Chieh, and Jin-Kui Ye. "The relationship between covariance risk and size effects in emerging equity markets." Managerial Finance 42, no. 3 (March 14, 2016): 174–90. http://dx.doi.org/10.1108/mf-10-2014-0269.
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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.
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Anandasayanan, Saradhadevi. "Stock Return Predictability with Financial Ratios: An Empirical Study of Listed Manufacturing Companies in Sri Lanka." International Journal of Accounting and Financial Reporting 8, no. 4 (October 11, 2018): 471. http://dx.doi.org/10.5296/ijafr.v8i4.14137.
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This study attempts to investigate financial ratios’ predictive power, using the yearly time series data during the period of 2012-2017 for 33 listed manufacturing companies in Colombo Stock Exchange. This study specifically identifies the financial ratios, which are acknowledged as the predictors of stock returns in the share market, to test the stock return predictability. The financial ratios include the ratio of dividend yield, earnings per share, and earnings yield which are most useful and effective on stock return predictability in order to cover a wide range of predictions which have been used by all most all the previous researches. The stock return predictability is analyzed by regressing the dividend yield, earning per share and earning yield respectively on the yearly stock returns from 2012 to 2017. The results show high predictability power, since the R2-value is high and the coefficients are very significant and autocorrelation corrected standard errors. The results reveal that the three ratios hold a somehow predictive power regarding stock returns of the Listed Manufacturing Companies in Colombo Stock Exchange.
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Heston, Steven L., and Ronnie Sadka. "Seasonality in the Cross Section of Stock Returns: The International Evidence." Journal of Financial and Quantitative Analysis 45, no. 5 (August 12, 2010): 1133–60. http://dx.doi.org/10.1017/s0022109010000451.
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AbstractThis paper studies seasonal predictability in the cross section of international stock returns. Stocks that outperform the domestic market in a particular month continue to outperform the domestic market in that same calendar month for up to 5 years. The pattern appears in Canada, Japan, and 12 European countries. Global trading strategies based on seasonal predictability outperform similar nonseasonal strategies by over 1% per month. Abnormal seasonal returns remain after controlling for size, beta, and value, using global or local risk factors. In addition, the strategies are not highly correlated across countries. This suggests they do not reflect return premiums for systematic global risk.
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Goncalves-Pinto, Luis, Bruce D. Grundy, Allaudeen Hameed, Thijs van der Heijden, and Yichao Zhu. "Why Do Option Prices Predict Stock Returns? The Role of Price Pressure in the Stock Market." Management Science 66, no. 9 (September 2020): 3903–26. http://dx.doi.org/10.1287/mnsc.2019.3398.
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Stock and options markets can disagree about a stock’s value because of informed trading in options and/or price pressure in the stock. The predictability of stock returns based on this cross-market discrepancy in values is especially strong when accompanied by stock price pressure, and it does not depend on trading in options. We argue that option-implied prices provide an anchor for fundamental stock values that helps to distinguish stock price movements resulting from pressure versus news. Overall, our results are consistent with stock price pressure being the primary driver of the option price-based stock return predictability. This paper was accepted by Tyler Shumway, finance.
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Sim, Myounghwa. "Realized Skewness and the Return Predictability." Journal of Derivatives and Quantitative Studies 24, no. 1 (February 29, 2016): 119–52. http://dx.doi.org/10.1108/jdqs-01-2016-b0005.
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We explore the cross-section of realized variance, skewness, and kurtosis for stock returns obtained from intraday data. We investigate the properties of the realized higher moments, and more importantly, examine relations between the realized moments and subsequent stock returns. We find evidence of a negative relation between realized skewness and next week’s returns. A strategy buying stocks in the lowest realized skewness quintile and selling stocks in the highest realized skewness quintile earns 0.79 percent per week a risk-adjusted basis. Our results on the realized skewness are robust to controls for various firm characteristics such as size and book-to-market. Little evidence exists that either the realized volatility or the realized kurtosis is significantly related to next week’s returns.
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McMillan, David G. "Non-linear Predictability of UK Stock Market Returns*." Oxford Bulletin of Economics and Statistics 65, no. 5 (December 2003): 557–73. http://dx.doi.org/10.1111/j.1468-0084.2003.00061.x.
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Mubashar, Ammara, Sumayya Chughtai, and Abdul Raheman. "Trade Credit and Stock Return Predictability: Evidence from Pakistan." Abasyn Journal of Social Sciences, Volume 14 issue 1 (June 30, 2021): 145–57. http://dx.doi.org/10.34091/ajss.14.1.09.
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Trade credit transfers private information about borrower�s creditworthiness and future performance to other lenders and this information can also be translated into the stock market. The purpose of this study is to analyze the informational role of trade credit in predicting future stock returns of the firms in the context of Pakistan. After controlling for market and firm-specific characteristics in our proposed five-factor model, it is found that firms depending more on trade credit as compared to bank loans have higher future stock returns. These findings suggest that trade credit supply signals the information that the supplier has about the borrower and this information is gradually and positively translated in the market Keywords: Trade Credit, Stock return Predictability, Fama & French Three-Factor Model
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Wang, Zhigang, Yong Zeng, Heping Pan, and Ping Li. "PREDICTABILITY OF MOVING AVERAGE RULES AND NONLINEAR PROPERTIES OF STOCK RETURNS: EVIDENCE FROM THE CHINA STOCK MARKET." New Mathematics and Natural Computation 07, no. 02 (May 2011): 267–79. http://dx.doi.org/10.1142/s1793005711001925.
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This paper investigates the predictability of moving average rules for the China stock market. We find that buy signals generate higher returns and less volatility, while returns following sell signals are negative and more volatile. Moreover, the bootstrapping results indicate that the asymmetrical patterns of return and volatility between buy and sell signals cannot be explained by four popular linear models of returns, especially the phenomenon of negative sell returns. We then test the nonlinear dynamic process of returns. Although the existing artificial neural network (ANN) model can replicate the negative sell returns, it fails to capture the volatility patterns of buy and sell returns. Furthermore, we introduce the conditional heteroskedasticity structure into the ANN model and find that the revised ANN model cannot only explain the predictability of returns, but can also capture the patterns of buy and sell volatility, which are never achieved by any linear model of returns tested in the related literature. Therefore, we conclude that the moving average trading rules can pick up some of the hidden nonlinear patterns in the dynamic process of stock returns, which may be the reason why they can be used to predict price changes.
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KUDRYAVTSEV, ANDREY. "SHORT-TERM HERDING EFFECT ON MARKET INDEX RETURNS." Annals of Financial Economics 14, no. 01 (February 13, 2019): 1950004. http://dx.doi.org/10.1142/s2010495219500040.
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The study analyzes the predictability of stock market returns based on the previous day’s cross-sectional market-wide herd behavior. Assuming that herding may lead to stock price overreaction and result in subsequent price reversals, I suggest that daily stock market returns may be higher (lower) following trading days characterized by negative (positive) market returns and high levels of herding. Analyzing the daily price data for S&P 500 Index and all its constituents and employing two alternative market-wide herding measures based on cross-sectional daily deviation of stock returns, I document that the days of both positive and negative market returns tend to be followed by price reversals (drifts), if the market-wide levels of herding are high (low). The herding effect on the next day’s stock market returns is found to be more pronounced following the days when the sign of the market return corresponds to the direction of the longer-term stock market tendency and the days characterized by relatively large stock market movements. The effect also remains significant after accounting for the specific numerical value of the market return.
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Kongsilp, Worawuth, and Cesario Mateus. "Volatility risk and stock return predictability on global financial crises." China Finance Review International 7, no. 1 (February 20, 2017): 33–66. http://dx.doi.org/10.1108/cfri-04-2016-0021.
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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.
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Chang, Chia-Lin, Jukka Ilomäki, Hannu Laurila, and Michael McAleer. "Long Run Returns Predictability and Volatility with Moving Averages." Risks 6, no. 4 (September 22, 2018): 105. http://dx.doi.org/10.3390/risks6040105.
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This paper examines how the size of the rolling window, and the frequency used in moving average (MA) trading strategies, affects financial performance when risk is measured. We use the MA rule for market timing, that is, for when to buy stocks and when to shift to the risk-free rate. The important issue regarding the predictability of returns is assessed. It is found that performance improves, on average, when the rolling window is expanded and the data frequency is low. However, when the size of the rolling window reaches three years, the frequency loses its significance and all frequencies considered produce similar financial performance. Therefore, the results support stock returns predictability in the long run. The procedure takes account of the issues of variable persistence as we use only returns in the analysis. Therefore, we use the performance of MA rules as an instrument for testing returns predictability in financial stock markets.
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Kim, Jun Sik, and Sung Won Seo. "The Effect of Short Sale Ban on the Relation between Disagreement and Stock Returns." Journal of Derivatives and Quantitative Studies 23, no. 2 (May 31, 2015): 155–82. http://dx.doi.org/10.1108/jdqs-02-2015-b0001.
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This paper investigates the effect of the short sale ban by the Korean government on the relationship between the disagreement among investors and the future stock returns. Short selling in Korean stock market was banned twice in 2008 and 2011. The short sale ban provides a natural experiment environment to study the effect of the short sale constraints on the relationship between the disagreement among investors and the future stock returns. Furthermore, it is an exogenous shock in the point of individual stocks. Thus, this paper focus on short sale ban periods to analyzes the stock return predictability of the disagreement among investors’ opinions about analysts’ earnings forecasts. Main results of this paper are as follows: First, the portfolio within the top 30% of the disagreement among investors experiences the significantly higher returns than that within the bottom 30% of the disagreement only during short sale ban periods. However, the two portfolio returns are not significantly different during the other periods excluding the short sale ban periods. These results are robust even after controlling for firm sizes, boot to market ratios, and the momentum effects. Second, a portfolio with higher the disagreement among investors presents significantly positive abnormal returns estimated by Fama-French’s three factor model during short sale ban periods. On the other hand, the abnormal returns of the portfolio with lower the disagreement among investors are not significantly different from zero. Furthermore, those returns of the portfolio with lower disagreement are not affected by the short sale ban. Finally, our findings show that individual stock returns are positively related to disagreement after controlling for the characteristics of individual stocks. Consequentially, the stocks with higher disagreement are overvalued during the short sale ban periods according to our robust empirical analyses with various control variables. According to our findings, we conclude that the short sale constraints are important factors to determine the predictability of disagreement on future stock returns. These are consistent with the results of short sale ban on the U.S. stock market from Autore, Billingsley, and Kovacs (2011).
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Nguyen, Khoa. "EX ANTE PREDICTABILITY OF STOCK RETURNS IN A FRONTIER MARKET." Applied Finance Letters 11 (January 23, 2023): 135–45. http://dx.doi.org/10.24135/afl.v11i.534.
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This study reports results on the ex ante predictability of stock returns using real-time stock market data in Vietnam, a frontier market, from June 2008 to June 2021. Countries classified as a frontier market are often known for currency manipulation, financial market illiquidity, and political instability. Despite the enormous risk usually posed by these inefficiencies, potential profits are large and achievable for many investors. This study provides evidence on existing a strategy to form out-of-sample long portfolios that generate statistically significant and positive mean monthly returns even in the presence of transaction costs. I also justify the magnitude of these returns by showing that they exceed those of VnIndex and MSCI Vietnam Index. The results reject the hypothesis that the stock prices in Vietnamese market follow random walks, thus oppose the stock market efficiency hypothesis. Evidence found in this study provides a better understanding of informational efficiency in a frontier equity market setting. Specifically, there are several implications on portfolio selection strategies, stock price patterns, and trading behavior bias related to Vietnamese stock market can be drawn from this study.
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Brandi, Vinicius Ratton. "Predictability of stock market indexes following large drawdowns and drawups." Brazilian Review of Finance 19, no. 1 (March 6, 2021): 1–23. http://dx.doi.org/10.12660/rbfin.v19n1.2021.81140.
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The efficient market hypothesis is one of the most popular subjects in the empirical finance literature. Previous studies of the stock markets, which are mostly based on fixed-time price variations, have inconclusive findings: evidence of short-term predictability varies according to different samples and methodologies. We propose a novel approach and use drawdowns and drawups as triggers, to investigate the existence of short-term abnormal returns in the stock markets. As these measures are not computed within a fixed time horizon, they are flexible enough to capture subordinate, time-dependent processes that could drive market under- or overreaction. Most estimates in our results support the efficient market hypothesis. The underreaction hypothesis receives stronger support than does overreaction, with higher prevalence of return continuations than reversals. Evidence for the uncertain information hypothesis is present in some markets, mainly after lower-magnitude events.
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Kayani, Sehrish, Usman Ayub, and Imran Abbas Jadoon. "Adaptive Market Hypothesis and Artificial Neural Networks: Evidence from Pakistan." Global Regional Review IV, no. II (June 30, 2019): 190–203. http://dx.doi.org/10.31703/grr.2019(iv-ii).21.
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The debate covering stock return predictability is now shifted towards the investigation of changing patterns of return predictability as suggested by the adaptive market hypothesis (AMH). The present article inspects the varying return predictability pertaining to the equity market in Pakistan under AMH framework. A nonlinear autoregressive neural network (NARNN) model is employed to investigate the nonlinear dependency of returns over a period of eighteen years. NARNN is a robust and flexible technique that is free from any restrictive assumptions. Under a rolling window framework, the repeating patterns of predictability and unpredictability are observed. This finding confirms the idea of AMH.
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Boucher, Christophe. "Stock prices–inflation puzzle and the predictability of stock market returns." Economics Letters 90, no. 2 (February 2006): 205–12. http://dx.doi.org/10.1016/j.econlet.2005.08.001.
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Rana Shahid Imdad Akash, Iqbal Mahmood, and Muhammad Mudasar Ghafoor. "Anomalous Behaviour and Volatility in Stock Returns are still Live - Efficient Markets Hypothesis? : Perspective from Pakistan Stock Exchange (PSX)." Journal of Accounting and Finance in Emerging Economies 6, no. 2 (June 14, 2020): 381–89. http://dx.doi.org/10.26710/jafee.v6i2.1182.
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Purpose: This empirical study investigates the anomalous behaviour and volatility in stock return of PSX-100 index of Pakistan Stock Exchange (PSX).
Design/Methodology/Approach: The data is taken from January, 2006 to December, 2018 to detect variability and predictability of stock returns. ARCH and GARCH models are applied to check the volatility in stock returns using dummy variable.
Findings: It is found that there exists positive and significant September effect in Pakistani equity market. The returns are high in the month of September than other months. The constant returns do not exist during the whole year so the efficient market hypothesis contradicts.
Implications/Originality/Value: The Efficient Market Hypothesis is question mark due to volatility for mispricing the securities. The mispricing may have implications for undervalue or overvalue the securities and overall economic activity of equity – stock returns.
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Auer, Benjamin R. "On time-varying predictability of emerging stock market returns." Emerging Markets Review 27 (June 2016): 1–13. http://dx.doi.org/10.1016/j.ememar.2016.02.005.
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Xu, Yanbing. "Exploring the predictability of intraday returns in China's stock market." BCP Business & Management 30 (October 24, 2022): 735–43. http://dx.doi.org/10.54691/bcpbm.v30i.2524.
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With the rapid development of high-frequency trading, intraday trading has become more and more popular due to its important role in understanding the efficiency of the intraday market and capturing more trading opportunities. This article explores whether there is momentum effect and reversal effect in China’s stock market by studying the correlation and predictability between half-hour returns. The results show that there is an intraday momentum effect between the first half-hour and full-day returns. After the investment strategy, it is found that this effect has economic significance, but after considering the transaction costs, the momentum effect cannot make investors obtain excess returns. These costs are the reason for the long-term predictability of intraday returns.
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Shahid, Muhammad Naeem, Khalid Latif, Ghulam Mujtaba Chaudhary, and Shahid Adil. "Financial Crises and Adaptive Market Hypothesis: An Evidence from International Commodities traded at New York Stock Exchange." Review of Economics and Development Studies 6, no. 1 (March 31, 2020): 67–81. http://dx.doi.org/10.47067/reads.v6i1.185.
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This study evaluates the varying degree of predictability of commodities return through empirical analysis of AMH (Adaptive Market Hypothesis). We divide daily returns data (from 1996 to 2013) of commodities indices (Gold, Metal, Oil& Silver) into different crisis periods. We subject all the subsamples to linear/nonlinear tests to reveal how market efficiency (independency of returns) has behaved over time. All the linear (except variance ratio) and nonlinear tests are evident that commodity indices returns have been predictable (dependent) in some crisis periods while unpredictable (dependence) in the others thus consistent with the implication of AMH. Therefore, commodities markets are adaptive markets. The findings suggest the behavior of commodities’ markets is best explained by AMH than conventional/traditional EMH (Efficient Market Hypothesis).
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Fiedor, Paweł, and Artur Hołda. "The Effects of Bankruptcy on the Predictability of Price Formation Processes on Warsaw’s Stock Market." e-Finanse 12, no. 1 (March 1, 2016): 32–42. http://dx.doi.org/10.1515/fiqf-2016-0134.
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AbstractIn this study we investigate how bankruptcy affects the market behaviour of prices of stocks on Warsaw’s Stock Exchange. As the behaviour of prices can be seen in a myriad of ways, we investigate a particular aspect of this behaviour, namely the predictability of these price formation processes. We approximate their predictability as the structural complexity of logarithmic returns. This method of analysing predictability of price formation processes using information theory follows closely the mathematical definition of predictability, and is equal to the degree to which redundancy is present in the time series describing stock returns. We use Shannon’s entropy rate (approximating Kolmogorov-Sinai entropy) to measure this redundancy, and estimate it using the Lempel-Ziv algorithm, computing it with a running window approach over the entire price history of 50 companies listed on the Warsaw market which have gone bankrupt in the last few years. This enables us not only to compare the differences between predictability of price formation processes before and after their filing for bankruptcy, but also to compare the changes in predictability over time, as well as divided into different categories of companies and bankruptcies. There exists a large body of research analysing the efficiency of the whole market and the predictability of price changes en large, but only a few detailed studies analysing the influence of external stimulion the efficiency of price formation processes. This study fills this gap in the knowledge of financial markets, and their response to extreme external events.
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Padungsaksawasdi, Chaiyuth. "On the dynamic relationship between gold investor sentiment index and stock market." International Journal of Managerial Finance 16, no. 3 (December 6, 2019): 372–92. http://dx.doi.org/10.1108/ijmf-11-2018-0334.
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Purpose Considering the unique data of the gold investor sentiment index in Thailand, the purpose of this paper is to investigate the bivariate dynamic relationship between the gold investor sentiment index and stock market return, as well as that between the gold investor sentiment index and stock market volatility, using the panel vector autoregression (PVAR) methodology. The author presents and discusses the findings both for the full sample and at the industry level. The results support prior literature that stocks in different industries do not react similarly to investor sentiment. Design/methodology/approach The PVAR methodology with the GMM estimation is found to be superior to other static panel methodologies due to considering both unobservable time-invariant and time-variant factors, as well as being suitable for relatively short time periods. The panel data approach improves the statistical power of the tests and ensures more reliable results. Findings In general, a negative and unidirectional association from gold investor sentiment to stock returns is observed. However, the gold sentiment-stock realized volatility relationship is negative and bidirectional, and there exists a greater impact of a stock’s realized volatility on gold investor sentiment. Importantly, evidence at the industry level is stronger than that at the aggregate level in both return and volatility cases, confirming the role of gold investor sentiment in the Thai stock market. The capital flow effect and the contagion effect explain the gold sentiment-stock return relationship and the gold sentiment-stock volatility relationship, respectively. Research limitations/implications The gold price sentiment index can be used as a factor for stock return predictability and stock realized volatility predictability in the Thai equity market. Practical implications Practitioners and traders can employ the gold price sentiment index to make a profit in the stock market in Thailand. Originality/value This is the first paper to use panel data to investigate the relationships between the gold investor sentiment and stock returns and between the gold investor sentiment and stocks’ realized volatility, respectively.
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Patel, Jayen B. "The Monthly Barometer Of The Indian Stock Market." International Business & Economics Research Journal (IBER) 13, no. 1 (December 31, 2013): 85. http://dx.doi.org/10.19030/iber.v13i1.8358.
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The January Barometer or the Other January effect suggests that January returns can predict future performance of the stock market. In this study, it is examined if any particular calendar month return can effectively be used as a monthly barometer to accurately predict future direction of the Indian stock market. The results indicate none of the calendar month returns has consistent ability to accurately predict the performance of the Indian stock market over the next twelve months. The accuracy of prediction did not substantially improve whether the predictor month had generated positive or negative returns. The results continue to remain remarkably consistent when the predictability accuracy was analyzed over time by examining the effect separately over years. The findings of this study clearly demonstrate that the Indian stock market does not possess a monthly barometer that can accurately predict future direction of the stock market.
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Kumar, Rakesh. "Risk, uncertainty and stock returns predictability – a case of emerging equity markets." Journal of Financial Economic Policy 10, no. 4 (November 5, 2018): 438–55. http://dx.doi.org/10.1108/jfep-08-2017-0075.
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Purpose This paper aims to investigate the predictability of stock returns under risk and uncertainty of a set of 11 emerging equity markets (EEMs) during the pre- and post-crash periods. Design/methodology/approach Listed indices are considered to serve the proxy of stock markets with a structural break in data for the period: 2000-2014. As preliminary results highlight the significant autocorrelations in stock returns, Threshold-GARCH (1,1) model is used to estimate the conditional volatility, which is further decomposed into expected and unexpected volatility. Findings Results highlight that the volatility has symmetric impact on stock returns during the pre-crash period and asymmetric impact during the post-crash period. While testing the relationship of stock returns, a significant positive (negative) relationship is found with expected volatility during the pre-crash (post-crash) periods. The stock returns are found positively related to unexpected volatility. Research limitations/implications Business, political and other market conditions of sample stock markets are fundamentally different. These economies were liberalized in different years, which may affect the degree of integration with international equity markets. Practical implications The findings highlight that investors consider the impact of expected volatility in forecasting of stock returns during the growth period. They realize returns in commensurate to risk of their portfolios. However, they significantly reduce their investments in response to expected volatility during the recession period. The positive relationship between stock returns and unexpected volatility highlights the fact that investors realize extra returns for exposing their portfolios to unexpected volatility. Originality/value Pioneer efforts are made by using T-GARCH (1,1) procedure to analyse the problem. Given the emergence of emerging equity markets, new insight in dynamics of stock returns provide interesting findings for portfolio diversification under risk and uncertainty.
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Vu, Ha, and Sean Turnell. "Seasonality in the Australian Stock Market." Applied Economics and Finance 6, no. 5 (August 13, 2019): 158. http://dx.doi.org/10.11114/aef.v6i5.4445.
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This paper examines the presence of day-of-the-week and month-of-the-year effects in the Australian stock market over the past several decades, and investigates whether long-standing anomalies persist following the 1987 stock market crash, and the 2008 global financial crisis. We find that before the 1987 crash the Australian stock market recorded lowest returns on Tuesday and highest returns on Thursdays. However, these daily phenomena seemed to vanish in the decades since, suggesting that Australian daily share prices are more likely to move randomly. In contrast, monthly seasonality is still in place with negative returns recorded in May and June, and high returns in July, December, and April. Seasonality and predictability in Australian equity prices, though reduced, are thus seemingly not dead just yet.
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Bannigidadmath, Deepa. "CONSUMER SENTIMENT AND INDONESIA'S STOCK RETURNS." Buletin Ekonomi Moneter dan Perbankan 23 (March 20, 2020): 1–12. http://dx.doi.org/10.21098/bemp.v23i0.1194.
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This paper examines whether consumer sentiment predicts the excess returns of theaggregate market and nine industries from the Indonesia equity market. We discoverevidence of predictability for three industries; however, the magnitude of predictabilityare heterogeneous. Some sectors are predictable during expansions, whereas others areonly predictable during recessions. There is no evidence of the reversal of the impact ofconsumer sentiment on stock returns. We conduct several robustness tests that include(i) estimating a predictive regression model with a feasible quasi-generalized leastsquares–based estimator and (ii) accounting for structural breaks. These tests confirmthe baseline results.
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Ahmed, Naeem, and Mudassira Sarfraz. "Stock Market Volatility Measure Using Non-Traditional Tool Case of Germany." Economics and Business 32, no. 1 (July 5, 2018): 126–35. http://dx.doi.org/10.2478/eb-2018-0010.
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Abstract. This study examines the stock market volatility of German bench-mark stock index DAX 30 using logarithmic extreme day return. German stock markets have been analyzed extensively in literature. We look into volatility issue from the standpoint of extreme-day changes. Our analysis indicates the non-normality of German stock market and higher probability of negative trading days. We measure the occurrences of extreme-day returns and their significance in measuring annual volatility. Our time series analysis indicates that the occurrences of extreme-days show a cyclical trend over the sample time period. Our comparison of negative and positive extreme-days indicates that negative extreme-days overweigh the positive extreme days. Standard deviation, as measure of volatility used traditionally, gives altered ranks of annual volatility to a considerable extent as compared to extreme-day returns. Lastly, existence of extreme day returns can be explained by past period occurrences, which show predictability.
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Xie, Haibin, and Shouyang Wang. "Risk-return trade-off, information diffusion, and U.S. stock market predictability." International Journal of Financial Engineering 02, no. 04 (December 2015): 1550038. http://dx.doi.org/10.1142/s2424786315500383.
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Recent academic literature in finance documents both risk-return trade-off and gradual information diffusion (ID). Motivated by these two financial theories, this paper proposes the ARCH-M model augmented by an ID indicator to forecast the U.S. stock market returns. Empirical studies performed on the monthly S&P500 index show that our approach is useful in both statistical and economic sense. Further analysis shows that the ID provides complementary information to risk-return trade-off effect. Our findings confirm that financial theories are valuable for stock return forecasting.
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Guloglu, Bülent, Sinem Guler Kangalli Uyar, and Umut Uyar. "Dynamic Quantile Panel Data Analysis of Stock Returns Predictability." International Journal of Economics and Finance 8, no. 2 (January 24, 2016): 115. http://dx.doi.org/10.5539/ijef.v8n2p115.
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<p>This paper analyses the effect of financial ratios on stock returns using quantile regression for dynamic panel data with fixed effects. Eighty three firms of manufacturing industry, which were traded on the Borsa Istanbul for 2000-2014 period, are covered in the study. The most of financial variables have heterogeneous structure so they generally include extreme values. Thus, panel quantile regression technique, suggested by Koenker (2004), is used. Since the technique yields robust estimator in the case of extreme values the Gaussian estimators will be biased and not efficient. The sensitivity of relationship, on the other hand, can be studied for different parts of the stock returns’ conditional distribution by using quantile regression technique. However, because of that the lagged of dependent variable is used as an explanatory variable in dynamic panel models, fixed effect estimators will be biased. Thereby, in this study the instrumental variable approach suggested by Chernozhukov and Hansen (2006) is used to produce unbiased and consistent estimators.</p>The results show that the stock returns respond to the changes on the financial leverage ratio, the dividend yield, the market-to-book value ratio, financial beta and the total active profitability variables differently for the different parts of the stock returns’ conditional distribution. They also indicate that, at high quantiles, return fluctuations in the current period will be more effective for investors’ transaction attitudes on stocks for the next period.
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Bali, Turan G., K. Ozgur Demirtas, and Hassan Tehranian. "Aggregate Earnings, Firm-Level Earnings, and Expected Stock Returns." Journal of Financial and Quantitative Analysis 43, no. 3 (September 2008): 657–84. http://dx.doi.org/10.1017/s0022109000004245.
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AbstractThis paper provides an analysis of the predictability of stock returns using market-, industry-, and firm-level earnings. Contrary to Lamont (1998), we find that neither dividend payout ratio nor the level of aggregate earnings can forecast the excess market return. We show that these variables do not have robust predictive power across different stock portfolios and sample periods. In contrast to the aggregate-level findings, earnings yield has significant explanatory power for the time-series and cross-sectional variation in firmlevel stock returns and the 48 industry portfolio returns. The mean reversion of stock prices as well as the earnings' correlation with expected stock returns are responsible for the forecasting power of earnings yield. These results are robust after controlling for bookto-market, size, price momentum, and post-earnings announcement drift. At the aggregate level, the information content of firm-level earnings about future cash flows is diversified away and higher aggregate earnings do not forecast higher returns.
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Eleswarapu, Venkat R., and Marc R. Reinganum. "The Predictability of Aggregate Stock Market Returns: Evidence Based on Glamour Stocks." Journal of Business 77, no. 2 (April 2004): 275–94. http://dx.doi.org/10.1086/381275.
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Emad Azhar Ali, Syed, Fong-Woon Lai, and Muhammad Kashif Shad. "Investors’ risk perception in the context of efficient market hypothesis: A conceptual framework for malaysian and indonesian stock exchange." SHS Web of Conferences 124 (2021): 03002. http://dx.doi.org/10.1051/shsconf/202112403002.
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The advocates of the Efficient Market Hypothesis (EMH) theory postulates that share prices depict all the available information concerning its intrinsic worth. EMH espouses the Random Walk Theory i.e. future stock returns cannot be predicted based on past movement patterns. Contrary to that, there are believers of the Adaptive Market Hypothesis (AMH) who have questioned the adaptability of EMH and argues that market efficiency and investor’s risk perception varies across time, thus, stock returns can be predicted through active portfolio management. Various Studies have argued on market efficiency debate for developed markets, however, limited studies have examined the same for emerging markets such as Malaysia and Indonesia, which are most volatile among ASEAN-5 indices. Therefore, the primary objective of this study is to conceptualize the manifestation of efficient market hypothesis and investors’ risk perception in volatile markets of Malaysia (Kuala Lumpur Composite Index) and Indonesia (Jakarta Composite Index) by testing the 10 years (2010-2019) of daily, weekly and monthly data for the return predictability. The findings of this study will provide insight into stock market behavior to help investors to better strategize their portfolio investment positioning to reap the most efficient risk-based return.
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Hjalmarsson, Erik. "Predicting Global Stock Returns." Journal of Financial and Quantitative Analysis 45, no. 1 (November 26, 2009): 49–80. http://dx.doi.org/10.1017/s0022109009990469.
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AbstractI test for stock return predictability in the largest and most comprehensive data set analyzed so far, using four common forecasting variables: the dividend-price (DP) and earnings-price (EP) ratios, the short interest rate, and the term spread. The data contain over 20,000 monthly observations from 40 international markets, including 24 developed and 16 emerging economies. In addition, I develop new methods for predictive regressions with panel data. Inference based on the standard fixed effects estimator is shown to suffer from severe size distortions in the typical stock return regression, and an alternative robust estimator is proposed. The empirical results indicate that the short interest rate and the term spread are fairly robust predictors of stock returns in developed markets. In contrast, no strong or consistent evidence of predictability is found when considering the EP and DP ratios as predictors.
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Masry, Mohamed. "The Impact of Technical Analysis on Stock Returns in an Emerging Capital Markets (ECM’s) Country: Theoretical and Empirical Study." International Journal of Economics and Finance 9, no. 3 (February 15, 2017): 91. http://dx.doi.org/10.5539/ijef.v9n3p91.
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Technical analysis, even if deliberated by some as purely conjecture, is still generally acknowledged as additional information to main brokerage companies. There are existent two reasons for the achievement of technical analysis and why its success is still debated: (1) stock return predictability stems from efficient markets that can be analysed by time-varying equilibrium returns, and (2) stock return predictability forms from prices wandering apart from their fundamental valuations. Fundamentally, both explanations show some kind of overall market inefficiency where investors are capable of exploiting. Therefore, technical analysis derived its importance from its ability to train investors to take investment decision based on historical trends of securities prices. To help find answers to the issues raised and to structure the study, the following general research question is set: is it possible for technical analysis to achieve abnormal returns in an Emerging Capital Markets (ECM’s) country, more specifically, the Egyptian Stock Exchange? If yes, hence it could be possibly used to help individual investors to take effective investment decision. By means of theoretical and empirical investigation, this study provides significant evidences that technical analysis achieved abnormal returns in inefficiency periods. This study suggests that simple trading rules, more specifically; the simple moving average beat the standard buy-and-hold strategy for the Egyptian stock exchange.