Tests Of Market Efficiency Research Articles

Weak form market efficiency test of Bangladesh Stock Exchange: an empirical evidence from Dhaka Stock Exchange and Chittagong Stock Exchange

Investors need to have an idea about stock market before making investment whether the stock markets are efficient or not to take investment decision in stock market. For that reason, measurement of market efficiency of stock market bears significance to investors. Bearing it in mind, the study is undertaken to find out the existence of weak form efficiency prevails in largest stock market of Bangladesh. In order to get perfect result Parametric and Non Parametric tests were conducted of DSE & CSE for 2013 to 2017. It was found from all tests that Dhaka and Chittagong Stock exchange are not weak form efficient. Therefore, the result of the study will act as a helping hand to researchers to find out the reason of Bangladesh stock market not being weak form efficient as well as providing measurement to make the stock market weak form efficient.

Testing market efficiency with the pricing kernel

ABSTRACTMarket efficiency and the pricing kernel are closely related. A non-monotonic decreasing pricing kernel implies the existence of a trading strategy in contingent claims that stochastically dominates a direct investment in the market. Moreover, a market is assumed to be efficient only if no dominating strategies exist. Empirically, many studies of the pricing kernel find non-monotonicity, apparently ruling out market efficiency. However, these results are often unreliable, because the pricing measures of the pricing kernel are estimated using differing filtration sets. We show this effect both theoretically and empirically, and we discuss recent approaches in the literature for achieving more reliable estimates of the pricing kernel, potentially leading to better tests of market efficiency.

Random Walks and Market Efficiency in Chinese and Indian Equity Markets

Hypothesis of Market Efficiency is an important concept for the investors across the globe holding diversified portfolios. With the world economy getting more integrated day by day, more people are investing in global emerging markets. This means that it is pertinent to understand the efficiency of these markets. This paper tests for market efficiency by studying the impact of global financial crisis of 2008 and the recent Chinese crisis of 2015 on stock market efficiency in emerging stock markets of China and India. The data for last 20 years was collected from both Bombay Stock Exchange (BSE200) and the Shanghai Stock Exchange Composite Index and divided into four sub-periods, i.e. before financial crisis period (period-I), during recession (period-II), after recession and before Chinese Crisis (periodIII) and from the start of Chinese crisis till date (period- IV). Daily returns for the SSE and BSE were examined and tested for randomness using a combination of auto correlation tests, runs tests and unit root tests (Augmented Dickey-Fuller) for the entire sample period and the four sub-periods. The evidence from all these tests supports that both the Indian and Chinese stock markets do not exhibit weak form of market efficiency. They do not follow random walk overall and in the first three periods (1996 till the 2015) implying that recession did not impact the markets to a great extent, although the efficiency in percentage terms seems to be increasing after the global financial crisis of 2008.

Investment Behaviour of Analysts: A Case Study of Pakistan Stock Exchange

Security prices in efficient markets reflect all relevant information. Past price formations and even fundamental analysis cannot guarantee abnormal returns consistently to any pre-identified strategy or market participant, be they novice or expert traders. There have been various studies conducted with the aim to test market efficiency in emerging markets. However, in this study, we have surveyed the professional investment community and have studied their stated actions in making investments. Our results indicate the prevalence of herding and overconfidence in professional analysts. We also found that analysts extrapolate the past into future forecasts. We also discovered an association between demographic characteristics and the choice of security valuation methods that the analysts use. In line with Chevalier and Ellison (1998), we found that younger analysts herd less than the older ones.

A Test for Joint Market Efficiency from an Investor’s Perspective

This paper investigates the cross-country correlation between stock markets and its implications. It does so by introducing a new measure called the Scaled Covariance Difference (SCD), which captures the difference between the covariance of short term returns and longer term returns. This measure has practical implications for portfolio optimization, as well as in testing for the joint efficiency of markets. Our focus in this paper is on including the off-diagonal terms of the variance-covariance matrix in the analysis so as to develop a test for joint market efficiency, unlike the univariate tests for market efficiency which only make use of information along the main diagonal of the variance-covariance matrix. We also demonstrate how to implement the test for joint market efficiency using data on weekly stock returns from the Nifty and S&P 500 indices.

A test of market efficiency using stock market anomalies: a behavioural approach

A test of market efficiency using stock market anomalies: a behavioural approach

A Simple Return Generating Model in Discrete Time: Implications and Potential Applications for Market Efficiency Testing and Technical Analysis

A linear return generating model is introduced. This model is a generalization in discrete time of the differential equation describing dynamical systems in continuous time. The model is useful in its own right, as it provides a simplified, yet credible, quantitative description of the reality. Further, the model is used as a tool for a theoretical study of market efficiency testing. This is obtained by modelling certain market conditions under which new information is released and reflected in asset prices on the one hand, and, on the other hand, by recording what established econometric testing approaches conclude, about the hypothesis of market efficiency. Amongst others it is argued that, contrary to the general belief, theoretically a random walk in asset prices, under certain conditions, could be associated with profoundly inefficient markets. Furthermore, an enhancement of the battery of statistical tests for market efficiency is proposed by the potential application of specific forms of the suggested linear dynamic model and the possible advantages over the existing techniques are explained. Finally, market efficiency is discussed in its relation to Technical Analysis.

A Simple Return Generating Model in Discrete Time; Implications for Market Efficiency Testing

A linear return generating model is introduced. This model is a generalization in discrete time of the differential equation describing dynamical systems in continuous time. The model is useful in its own right, as it provides a simplified, yet credible, quantitative description of the reality. Further, the model is used as a tool for a theoretical study of market efficiency testing. This is obtained by modelling certain market conditions under which new information is released and reflected in asset prices on the one hand, and, on the other hand, by recording what established econometric testing approaches conclude, about the hypothesis of market efficiency. Amongst others it is argued that, contrary to the general belief, theoretically a random walk in asset prices, under certain conditions, could be associated with profoundly inefficient markets. Furthermore, an enhancement of the battery of statistical tests for market efficiency is proposed by the potential application of specific forms of the suggested linear dynamic model and the possible advantages over the existing techniques are discussed.

The Impact of "Jet Lag" on the AFL Point Spread Wagering Market

This paper examines the presence of "jet-lag" effects in the Australian Football League point spread betting market. Fodor and Krieger’s (2014) findings that bookmakers, in NFL betting markets, do not consider efficiently the possible impact of jet lag on team performance, and are unable to take into account the possible existence of a potentially confounding home team bias since in virtually all games in the NFL, one of the teams has an a priori home ground advantage. Schnytzer and Weinberg (2008) took advantage of the distinctive feature of the Australian Football League (AFL), that many fixtures take place on neutral grounds, to demonstrate the apparent existence of a home team bias and the absence of a favorite-longshot bias. We conduct standard econometric tests of market efficiency over games where the home team bias cannot, by definition, exist. We used the 2001-2016 AFL seasons including the final series matches, venues, and betting information data and found no statistically significant line inefficiency in the games played on neutral grounds, regardless of whether the visiting team travels across multiple time zones in either direction or whether neither team requires a flight to reach the relevant stadium. However, line inefficiencies were found in overall games in which the home team enjoys an a priori home ground advantage. Such inefficiencies occur both in games where the visiting team experiences time zone changes when traveling to the game, and in games where the visiting team experiences no such changes. The amalgamated results for both neutral games and home bias games makes clear that jet lag cannot serve as a sole factor leading to inefficiencies but merely if combined with the home team bias. We show that betting on games in various inefficient sub-groups yields returns between 1.26 and 8.07 percent.

Technology, Adaptation and the Efficient Market Hypothesis

Tests of the efficient market hypothesis (EMH) suffer from a known flaw that has nevertheless received insufficient attention in the literature. Just as in Zeno’s famous paradox of Achilles and the tortoise, while we are testing market efficiency the measure of efficiency has already moved on. Prediction technology and data availability perpetually improve beyond the level that was available to market participants during the sample period. This introduces a bias into the tests. If one believes in the existence of deterministic patterns and of technological progress, one has to expect to discover inefficiencies in historical data. We can only expect prices to reflect all available in- formation to the degree that current technology enables. From this argument follows a necessity to adjust the EMH. This article discusses possible adjustments and develops the concept of technological efficiency. Based on a review of empirical evidence, this concept is shown to resolve many anomalies and to help bridge the gap between the financial economics literature and the rapidly advancing machine learning literature.

Innovated Power Enhancement for Testing Multi-factor Asset Pricing Models

Testing multi-factor asset pricing models is instrumental for the asset pricing theory and practice. Due to the accumulation of errors in estimating high-dimensional parameters, traditional quadratic-form tests such as the Wald test perform poorly against the sparse alternative hypothesis in the presence of a few mispriced assets. Fan et al. (2015) introduced a powerful testing procedure by adding a power enhancement component to the Wald test statistic and proved the power enhancement properties. To provide a promising alternative to Fan et al. (2015), we first introduce a new maximum-form test statistic and then study the asymptotic joint distribution of the Wald test statistic and the maximum test statistic. We prove that these two test statistics are asymptotically independent. Given their asymptotic independence, we propose an innovative power-enhanced testing procedure to combine their respective power based on Fisher’s method (Fisher, 1925). Theoretically, we prove that the innovated power enhancement retains the desired nominal significance level and achieves the asymptotically consistent power against the more general alternative. Furthermore, we demonstrate the finite-sample performance of our proposed innovated power enhancement test in simulation studies and an empirical study for testing market efficiency using asset returns of the Russel-2000 portfolio.

Brexit Announcement: A Test of Market Efficiency

This study tests market efficiency theory by examining the effect of the Brexit announcement on the risk adjusted stock price returns of a sample of firms with strong economic ties to the EU using the standard event study methodology in the finance literature. How did the market react to UK leaving the European Union? We hypothesize that the June 24, 2016 Brexit announcement would negatively affect the risk adjusted returns of the sample of firms analyzed. The purpose of this study is to test market efficiency by analyzing the effect of Brexit’s announcement on the market. Specifically, we analyze the semi-strong market efficiency hypothesis predicting that stock price returns react so fast to all public information that no investor can earn an above normal return by acting on such news. Consistent with market efficiency and behavioral finance theories, we observe an overreaction to the bad news up to 14 days following the announcement followed by a return to equilibrium. Overall, results support semi-strong form market efficiency for the Brexit announcement. Implications of this study suggest that efforts to determine the “right” value of stock are useless since the market is semi-strong form efficient. The “right” price is themarket price that instantly impounds all available and relevant information.

Does the introduction of futures improve the efficiency of Bitcoin?

The introduction of futures on Bitcoin eases the access of institutional investors to the market and offers an efficient way to short the cryptocurrency. We investigate the effect of this event on the market’s price efficiency and find the Bitcoin market to turn efficient. We conduct commonly used tests for market efficiency and check the robustness of our results by investigating Bitcoin Cash, a hard fork of Bitcoin, where we do not find a change in market’s efficiency.

Testing Random Walk and Market Efficiency: A Cross-Stock Market Analysis

The study seeks to examine the Random Walk Hypothesis (RWH) and market efficiency of the selected stock market indices particularly London Stock Exchange, EuroStoxx 50, Nihon Keizai Shimbum (NIKKI), Shanghai Composite Stock Exchange and Bombay Stock Exchange. Daily closing index value is considered and transformed into logarithm return. Various tests like serial independence test, unit root test and multiple variance tests are applied. It is observed that the null hypotheses (presence of random walks) of the daily returns of the indices are rejected and in few cases are accepted based on various test statistics. JEL Classification: G00, G01, G02

A Test of Market Efficiency When Short Selling Is Prohibited: A Case of the Dhaka Stock Exchange

A ban on short selling exists on several exchanges, especially in emerging markets. In most cases, short selling has always been prohibited, thus making it difficult to examine the ban’s effect on price discovery. In this paper, we consider data from the Dhaka Stock Exchange (DSE) to test for a short selling ban on market efficiency. The analysis examines runs in daily stock returns and then forms a distribution of return clusters according to their duration. Using Monte Carlo simulation, we find that runs of longer duration appear more frequently in the DSE data than we would expect in efficient markets. We compare these results to stocks in the Dow Jones Industrial Average (DJIA). We find that the same runs tests accord with market efficiency for liquid and easily shorted DJIA stocks.

A novel market efficiency index for energy futures and their term structure risk premiums

This paper proposes a novel futures market efficiency index which aggregates the efficiencies of futures contracts across their term structure spanning from one month to 12 months. The index measures the ability for price discovery of a long-term futures contract on its nearby short-term contract consistently across its terms. The index uses a recently developed futures market efficiency test which accounts for heteroscedastic prices and time-varying risk premiums. It simultaneously estimates the term premiums of futures, providing valuable information for the investor. The proposed index is employed to investigate the efficiencies of four major energy commodities, namely, crude oil, natural gas, heating oil, and gasoil during the sample period 1990–2016. Numerical results indicate that the market efficiencies vary across terms and across energy commodities. Gasoil futures traded on the Intercontinental Exchange (ICE) are the most efficient and natural gas futures are the least efficient in prices. The spillover dynamics of market risk information across futures markets are investigated using conditionally heteroscedastic common factors (CHCFs) extracted for each commodity using the estimated term premiums. There exist significant delayed, contemporaneous, and potential information spillovers among term premiums of the energy commodities in our sample. Our findings are robust and they can help investors to optimally diversify their portfolios.

Are Markets Truly Efficient? Experiments Using Deep Learning Algorithms for Market Movement Prediction

We examine the use of deep learning (neural networks) to predict the movement of the S&P 500 Index using past returns of all the stocks in the index. Our analysis finds that the future direction of the S&P 500 index can be weakly predicted by the prior movements of the underlying stocks in the index, but not strongly enough to reject market efficiency. Decomposition of the prediction error indicates that most of the lack of predictability comes from randomness and only a little from nonstationarity. We believe this is the first test of S&P 500 market efficiency that uses a very large information set, and it extends the domain of weak-form market efficiency tests.

Evidence for and Against the Validity of Efficient Market Hypothesis

Abstract The concept of an efficient financial market, in literature known as efficient market hypothesis (EMH), has had a long and difficult development path from the idea itself to its final conception, as one of the central paradigms in modern finance. It has been tested and critically reviewed for decades, and the two basic types of problems it has encountered are theoretical paradoxes and market anomalies. The aim of the paper is to examine the validity of EMH through various financial market efficiency tests and the results of previous research. The intention is to answer the question of whether, despite theoretical paradoxes and market anomalies, the notion of validity can be attributed to the concept of an efficient financial market. In this regard, the paper presents plenty of evidence for and against the validity of weak, semi-strong, and strong form of EMH, to conclude that, even after more than half a century of research, financial literature has not reached a consensus on the presence or absence of the validity of this hypothesis.

Jensen’s Alpha Estimation Models in Capital Asset Pricing Model

This research examined the alternatives of Jensen’s alpha (α) estimation models in the Capital Asset Pricing Model, discussed by Treynor (1961), Sharpe (1964), and Lintner (1965), using the robust maximum likelihood type m-estimator (MM estimator) and Bayes estimator with conjugate prior. According to finance literature and practices, alpha has often been estimated using ordinary least square (OLS) regression method and monthly return data set. A sample of 50 securities is randomly selected from the list of the S&P 500 index. Their daily and monthly returns were collected over a period of the last five years. This research showed that the robust MM estimator performed well better than the OLS and Bayes estimators in terms of efficiency. The Bayes estimator did not perform better than the OLS estimator as expected. Interestingly, we also found that daily return data set would give more accurate alpha estimation than monthly return data set in all three MM, OLS, and Bayes estimators. We also proposed an alternative market efficiency test with the hypothesis testing Ho: α = 0 and was able to prove the S&P 500 index is efficient, but not perfect. More important, those findings above are checked with and validated by Jackknife resampling results.

Liquidity and the convergence to market efficiency

ABSTRACTThe aim of this study is to investigate the relationship between market liquidity changes on the Johannesburg Stock Exchange (JSE) and the market’s degree of efficiency. Market efficiency is characterised in terms of two philosophies: Fama’s (1970) Efficient Markets Hypothesis (EMH), and Shiller’s (1981; 2003) informational efficiency designation. Efficiency was tested using measures of return predictability, a random walk benchmark and price volatility; liquidity was measured using market turnover. The tests were conducted on JSE Top 40 shares across three regimes, spanning January 2012–June 2016. The regimes are demarcated by two structural breaks in the JSE’s microstructure: the 2012 trading platform upgrade and the 2014 colocation centre launch. The results show that past order imbalances are a significant predictor of daily returns, although the significance of this predictability has dissipated over time. Return predictability is not influenced by liquidity. In fact, there is evidence that illiquidity weakens return predictability. Prices were closer to random walk benchmarks during the third regime. In consideration of informational efficiency, during the latter two regimes price volatility is greater during trading versus non-trading hours. This is coupled with an emergence of nonlinear return dependence, which is indicative of greater mispricing. Thus, over the three regimes, market efficiency improved in the sense of the EMH, but informational efficiency deteriorated. This study contributes to the field by: introducing an inverse measure of market efficiency; providing insight into the measure’s time variation and relation to liquidity; and demonstrating that market efficiency tests should incorporate the dual meanings of the term, enabling richer understanding of how such meanings intersect.