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This paper examines the time-varying efficiency of nine major Middle East and North Africa (MENA) stock markets namely Egypt, Bahrain, UAE, Jordan, Saudi Arabia, Oman, Qatar, Morocco and Tunisia during times of COVID-19 pandemic outbreak and vaccines.

The authors use two econometric approaches: (1) autocorrelation tests including the wild bootstrap automatic variance ratio test, the automatic portmanteau test and the Generalized spectral test, and (2) a non-Bayesian generalized least squares-based time-varying model with statistical inferences.

The results show that the degree of stock market efficiency of Egyptian, Bahraini, Saudi, Moroccan and Tunisian stock markets is influenced by the COVID-19 pandemic crisis. Furthermore, the authors find a tendency toward efficiency in most of the MENA markets after the announcement of the COVID-19's vaccine approval. Finally, the Jordanian, Omani, Qatari and UAE stock markets remain globally efficient during the three sub-periods of the COVID-19 pandemic outbreak.

The results have important implications for asset allocations and financial risk management. Portfolio managers may maximize the benefit of arbitrage opportunities by taking strategic long and short positions in these markets during downward trend periods. Policymakers should implement the action plans and reforms to protect the stock markets from global shocks and ensure the stability of the stock markets.

The purpose of this paper is to discuss the relevance and evolution of adaptive markets hypothesis (AMH) that has gained traction in the recent years, as it provides a dynamic perspective to the concept of informational efficiency.

This paper discusses several issues related to the concept of informationally efficient markets that have indicated efficient market hypothesis to be an incomplete portrayal of stock market behavior.

The authors find that a strict and perpetual adherence to informational efficiency is highly unlikely, and AMH provides a much more plausible description of the behavior of stock markets.

The authors provide a description of studies that examine the testable implications of AMH.

Design/Methodology/Approach: This chapter applies tests associated with the adaptive market hypothesis (AMH) and Johansen cointegration test. AMH acknowledges the views of the efficient market hypothesis and behavioural finance approach.

Purpose: Cryptocurrencies are considered a new asset class by multiasset portfolio managers. Hence, we examine the AMH and cointegration in the cryptocurrency market to know whether select cryptocurrencies can be diversified.

Findings: We find that cryptocurrencies are efficient and there is a long-run relationship among constituent series, and there is no short-run causality derived from bitcoin, Ethereum and litecoin to bitcoin, while stellar and Dogecoin have short-run causality to bitcoin.

Originality/Value: This chapter is different from the existing one as this is the first study in which the AMH and Johansen cointegration test are applied to check the efficiency and relationship of Bitcoin, Ethereum, and Monero, Stellar, litecoin and Dogecoin.

The purpose of this paper is to boost the existing literature on adaptive market hypothesis (AMH) as it first time links predictability of gold, silver and metal returns with AMH which permits the predictability of returns to vary over time.

To know whether commodity (gold, silver and metal) market is efficient or not, the commodity returns are observed by using appropriate linear time series tests (variance ratio test, runs test and auto-correlation test). To capture the varying efficiency of three commodities, the study employs subsamples of five years and all sub-samples are exposed to linear econometric tests to reveal how market efficiency (independency of returns) has behaved over time.

It is found that the commodity market (gold, silver and metal) is adaptive because fluctuation is observed in the market efficiency. Returns of all three commodities go under the periods of efficiency and inefficiency. Thus, AMH is the better description of behavior of commodity markets than traditional efficient market hypothesis.

Choice of sub-sample in the study is the first limitation as the authors employ a sub-sample comprising five years. Second, commission, fee and taxes (transection cost) are ignored in the study. Finally, the results are reported on the basis of linear econometric tests. In future, longer time period sub-sample analysis is suggested by the study to explore the varying nature of the commodities. Moreover, rolling window analysis may be a more appropriate method to elucidate the idea of AMH in further research. It is further suggested that the method used in the study could be helpful and adapted to examine other commodities (metal and agriculture), bonds and equity markets around the world.

The study will provide a better investment model which can enable the investors to seek more returns in future. Moreover, this research can be extended to explore multiple issues like adaptive behavior of returns from crypto currencies, bonds, stocks and real estate investment trusts.

As all the linear tests reveal that almost all the commodities show inefficient behavior in full sample period, it is clear that past prices widely would be helpful to predict the future prices at NYSE; furthermore, investors can use the time-varying information to reduce the risk of investment at NYSE. The study is helpful for individual investors as well as portfolio managers and brokers to forecast the prices on the bases of findings.

The paper identifies the need to study why behavior of commodity returns varies over time.

This paper aims to examine the weak form of efficiency for price series of four precious metals, i.e. gold, silver, platinum and palladium, using a generalized spectral method.

The method has the advantage of detecting both linear and non-linear serial dependence in the conditional mean, and it is robust to various forms of conditional heteroscedasticity. The authors use three different rolling windows for the purpose of robustness.

The authors report weak form of efficiency across metals series for almost all rolling windows. The optimum efficiency for Gold and Palladium is achieved through 250 days rolling window estimates whereas it is 500 days rolling window for silver. Platinum has similar efficiency levels across rolling windows. The degree of efficiency for metal prices is observed to be varying over time with silver market possessing highest levels of efficiency. The efficiency synchronization also varies across rolling windows and metals.

The results reveal that metal markets are efficient for most times implying the low predictability and the low likelihood of earning abnormal returns by speculating in these markets.

The study uses a relatively new statistical technique, the generalized spectral test, to capture linear and non-linear serial dependence. Therefore, the results possess adequate power against departure from market efficiency.

The main aim of this paper is to empirically test at market level, the investors' differential reaction to information, contribution of their confidence level and adaptive behaviour to excessive market volatility in Indian stock market.

The Bivariate Vector Autoregression and Impulse Response Analysis are used to study whether investors over/under-react to private and public information. EGARCH models are used to study the contribution of investors' over/under-confidence and adaptive behaviour to excessive market volatility.

The investors over-react to private information and under-react to public information during pre-crash period, become overconfident and contribute to excessive volatility. They under-react to both private and public information during after-crash period, become under-confident and also conform to adaptive market hypothesis (AMH).

The empirical results of the study can help investors to minimize the negative impact of over/under-confidence on their expected utility.

The investors shall perform a post-analysis of investment, become aware of their past behavioural mistakes and start adapting to changing market conditions. This shall move the markets towards a new equilibrium in long run thus conforming AMH. However, the investors sometimes display an apparently irrational behaviour during this process.

To the best of the author's knowledge, this is the first study at market level data examining investors' over/under-reaction, over/under-confidence and adaptive behaviour in the context of stock market crash.

This study aims to provide one of the first empirical investigations of market efficiency for developed markets during the recent global financial crisis.

Using the Morgan Stanley Capital International (MSCI) country indices as proxies for national stock markets, the study conducts a battery of econometric tests in assessing weak-form market efficiency for the developed markets.

The inferential outcomes are consistent among the different tests. Specifically, the study finds that the majority of developed markets are weak-form efficient while the USA is the sole equity market to be commonly diagnosed as weak-form inefficient across the different tests when using full period data spanning the January 2008-November 2011 period. However, when basing the analysis on one-year subsamples over the identical time period, this study fails to reject weak-form market efficiency for all of the developed markets and presents evidence consistent with the Adaptive Market Hypothesis as described by Urquhart and Hudson (2013). When applying technical analysis for the case of the USA over the full study period, the results indicate that the return predictabilities can be exploited for some horizon of variable length moving average (VMA) trading rules.

This study provides one of the first empirical investigations of market efficiency for developed markets during the recent global financial crisis using an extended set of econometric tests. The study contributes to the existing body of empirical research that formally assesses the impact of a financial crisis on stock market efficiency and underlines the significance and relevance of examining market efficiency through subsample analysis.

The purpose of this study to evaluate the evolving market efficiency of the housing market under the framework of adaptive market hypothesis and martingale difference hypothesis taking a case of India.

The study used a wild bootstrap version of the generalized spectral (GS) test in the rolling window framework to measure possible time-varying linear and non-linear dependence in the housing market.

The study finds that the Indian housing market, in general, is not efficient, and this efficiency is dynamic, which changes with time lending support to the adaptive market hypothesis. The study confirms that the evolutionary model of individuals adapting to a changing environment via behavioural biases affects the efficiency of the housing market, which leads to the evolving efficiency of the housing market prices.

The study believes that the potential implications go beyond evolutionary forces and the adaptive market hypothesis , which, does not only depend on an individual's decision-making process but also on social psychology. Thus, a further attempt in this line, taking into account the social psychology and quantitative rigour towards drivers of evolving efficiency is suggested for future research.

The study suggests that there is a possibility of extra returns for market players, but not always. The Indian housing market has witnessed several landmark reforms in recent years, so it is believed that these reforms would decrease the inefficiency level of this market. Contrary to this, the study’s findings reveal an increase in the inefficiency level in recent years. As the Indian housing market shows evolving efficiency, it is believed that the increased inefficiency is temporary. The increased inefficiency can be regarded as the settlement stage of the various policy and technical reforms.

Confirming the presence or absence of adaptive efficiency in the housing market under possible non-linear dependence will be a significant addition to the existing literature.

The purpose of this study is to investigate the adaptive market hypothesis (AMH) for 21 major global market indices for the period 1998–2018. These market indices cover the 16 largest global financial markets.

Quantile-regression methodology is employed to examine the market efficiency of a large number of financial markets from America, Europe and the Asia–Pacific region.

The results show that the returns in higher quantiles are negatively autocorrelated, and those in lower quantiles are positively autocorrelated. This evidence is stronger for the tails of return distribution. The positive autocorrelation (momentum effect) suggests market underreaction, and the negative autocorrelation (reversal effect) suggests overreaction. Overall, market efficiency appears to be time-varying and conditioned to the state of the market.

This study offers considerable evidence in favor of the AMH, for a large number of financial markets. These markets are substantially different from each other in terms of geography, nature of operation and size of the economy. The results from this study would be helpful to the academics, regulators and practitioners interested in financial markets.