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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.

Corporate treasurers manage the currency risk of their organization by hedging through futures contracts. The purpose of this paper is to evaluate the effectiveness of hedging by US currency futures contracts by taking into account the efficiency of the currency market.

The static models for calculating hedge ratio are as popular as dynamic models. But the main disadvantage with the static models is that they do not consider important properties of time series like autocorrelation and heteroskedasticity of the residuals and also ignore the cointegration of the market variables which indicate short-run market disequilibrium. The present study, therefore, measures the hedging effectiveness in the US currency futures market using two dynamic models – constant conditional correlation multivariate generalized ARCH (CCC-MGARCH) and dynamic conditional correlation multivariate GARCH (DCC-MGARCH).

The study finds that both the dynamic models used in the study provide similar results. The relative comparison of CCC-MGARCH and DCC-MGARCH models shows that CCC-MGARCH provides better hedging effectiveness result, and thus, should be preferred over the other model.

The findings of the study are important for the company treasurers since the new updated Indian accounting standards (Ind-AS), applicable from the financial year 2016–2017, make it mandatory for the companies to evaluate the effectiveness of hedges. These standards do not specify a quantitative method of evaluation but provide the flexibility to the companies in choosing an appropriate method which justifies their risk management objective. These results are also useful for the policy makers as they can specify and list the appropriate methods for evaluating the hedge effectiveness in the currency market.

Majorly, the studies on Indian financial market limit themselves to either examining the efficiency of that market or to evaluate the effectiveness of the hedges undertaken. Moreover, most of such works focus on the stock market or the commodity market in India. This is one of the first studies which bring together the concepts of efficiency of the market and effectiveness of the hedges in the Indian currency futures market.

The purpose of this paper is to study the lead-lag relationship between the futures and spot foreign exchange (FX) market in India to understand the price discovery mechanism and the relationship between these two markets.

The estimation of lead-lag relationship is realized in three steps. First unit root and stationarity tests (Augmented Dickey-Fuller, Phillips-Perron, and Kwiatkowski-Phillips-Schmidt-Shin) are applied to check the stationarity of the data. Second, cointegration tests (Engle and Granger’s residual based approach and Johansen’s cointegration test) are applied to determine long run relationship between the markets. Third, error correction estimation is carried out by applying Vector Error Correction Model (VECM) to determine the leading market.

The study finds that there is a long run relationship between the futures and spot market where the futures market has emerged as the leading market for the four currencies studied in the paper.

Majorly, the studies on Indian FX market limit themselves to identifying the efficiency of the market and the studies which talk about the lead-lag relationship focus on the Indian stock market. This paper enhances the existing literature on Indian FX market by exploring the less explored subject of the lead-lag relationship between futures and spot FX market in India.

This study aims to provide a comparative insight into the level of informational efficiency and irregularities of Shariah-compliant stocks and conventional stocks in three emerging markets, namely, China, Malaysia and Pakistan. The empirical evidence is provided for pre-crisis and crisis periods caused by the Covid-19 pandemic.

Informational efficiency is measured using the variance ratio (VR) Test developed by Kim (2006). The Approximate Entropy (ApEn) Metrics is used to investigate the level of irregularities in stock prices caused by the pandemic.

All the three emerging markets in the sample are not immune to the crisis caused by Covid-19 pandemic. The level of informational efficiency of both the Shariah-compliant and conventional stock is affected by the crisis. However, the former exhibits relatively high level of informational efficiency and stability in returns as compared to more volatility of conventional stocks.

This study provides market agents and policy makers with a robust assessment of the impact of the Covid-19 pandemic on informational efficiency of Shariah-compliant and conventional stocks. Relatively high informational efficiency of Shariah-compliant stocks indicates that they are more transparent and that investors can trust the Shariah-compliant stocks more. This higher level of transparency and trust leads to more steady returns and lower levels of risk even during turbulent time like Covid-19. Investors can gain superior returns by conducting fundamental analysis and investing in index funds.

To the best of the authors’ knowledge, this is the first study that highlights the difference in informational efficiency of conventional stocks and Shariah-compliant stocks in the crisis period caused by Covid-19. Unlike previous studies, this study uses firm level data which enables firm-wise assessment of informational efficiency.

Informational efficiency is a fundamental aspect of capital market quality, and therefore, regulators, managers and practitioners attempt to find ways to improve the informational efficiency. Since prior studies primarily focus on the numerical attributes of corporate reporting, it is not yet adequately known whether or not the linguistic attributes of corporate reporting affect informational efficiency. Thus, the purpose of this paper is to examine whether corporate reporting readability (readability), as an important linguistic attribute of corporate reporting, affects informational efficiency.

To measure readability, this paper uses Fog index. Moreover, to measure informational efficiency, the paper uses stock return variance ratios.

The findings reveal a positive and significant association between readability and informational efficiency. Moreover, the findings show that the association of readability and informational efficiency is stronger for firms facing higher information asymmetry. The findings further document the spillover effect of readability, in the sense that the readability of economically related public firms affects a firm’s informational efficiency. Overall, the results support the arguments that readability enhances informational efficiency.

This study contributes to the literature by providing evidence on the internalities and externalities of readability in the context of informational efficiency. Thus, the study will be of interest to regulators, managers and practitioners, especially in emerging capital markets, who tend to find practical and easy ways to improve informational efficiency.

The purpose of this paper is to assess the informational efficiency of S&P CNX Nifty index options in Indian securities market. The S&P CNX Nifty index is a leading stock index of India, consists of 50 most frequently traded securities listed on NSE. For the purpose, the study covers a period of six years from 4 June 2001 (the starting date for index options in India) to 30 June 2007.

The informational efficiency of implied volatilities (IVs) has been tested vis‐à‐vis select conditional volatilities models, namely, GARCH(1,1) and EGARCH(1,1). The tests have been carried out for “in‐the‐sample” as well as “out‐of‐the‐sample” forecast efficiency of implied volatilities.

The results of the study reveal that implied volatilities do not impound all the information available in the past returns; therefore, these are indicative of the violation of efficient market hypothesis in the case of S&P CNX Nifty index options market in India.

The finance managers, in Indian context, should rely on conditional volatility models (especially the EGARCH(1,1) model) compared to IV‐based forecasts to predict volatility for the horizon of one week. The stock exchanges and market regulator (SEBI) need to take certain initiatives in terms of extending the short‐selling facility and start trading of volatility index (VIX) to enhance the accuracy of IV‐based forecasts.

The paper addresses an issue which is still unexplored in the context of Indian securities market and in that sense makes an important contribution to literature on microstructure studies.

The author examine the performance of a number of high short interest stocks along with the prices of the GameStop stock and three major stock exchange indices, particularly for the period after the eruption of the Covid-19 crisis.

With the employment of the complexity–entropy causality plane approach, the author categorize the stock prices in terms of the level of informational efficiency.

The author reported that the efficiency level for the index of the high short interest stocks falls considerably, not only at the onset of the Covid-19 crisis but during the health crisis period at hand. This is translated into proof of less uncertainty in predicting the stock prices of these specific stocks. On the other hand, the GameStop prices exhibit the same behavior as those with the high short interest firms, but change considerably in the middle of the crisis. The reversal of the behavior, by obtaining higher informational efficiency levels, is attributed to the short squeeze frenzy that increased the price of the stock many times over. Among the stock market indices, the Dow Jones Industrial Average and the S&P 500 decreased their efficiency levels marginally, after the surge of the crisis, while the Russell 2000 index kept the level intact. The high and stable degree of randomness could be attributed to the measures taken concurrently by the Federal Reserve and the government immediately after the outbreak of the crisis.

This is one of the few studies that examine the impact of short selling behavior on the efficiency level of certain stocks' prices, particularly during the health public crisis. It provides an alternative approach to measuring quantitatively the degree of inefficiency and randomness.

The purpose of this paper is to investigate whether Islamic stock indexes outperform conventional stock indexes, in terms of informational efficiency and risk, during the recent financial instability period.

The paper uses a state space model combined with a standard GARCH(1,1) specification while taking into account structural breakpoints. The authors allow for efficiency and volatility spillovers to be time-varying and consider break dates to locate periods of financial instability.

Empirical results show that Islamic stock indexes are more volatile than their conventional counterparts and are not totally immune to the global financial crisis. As regards of the informational efficiency, the results show that the Islamic stock indexes are more efficient than the conventional stock indexes.

Resulting evidence of this paper has several implications for international investors who wish to invest in Islamic and/or conventional stock markets. Policy makers and even academics and Sharias researchers should as well take preventive measures in order to ensure the stability of Islamic stock markets during turmoil periods. Overall, prudent risk management and precocious financial practices are relevant and crucial for both Islamic and conventional financial markets.

The originality of this study is performed by the use of time-varying models for volatility spillovers and informational efficiency. It considers structural break dates that think about the dynamic effect of informational flows on stock markets. The study was developed in a global framework using international data. The global analysis allows avoiding country specific effects.

The aim of this paper is to examine the informational efficiency of prices of all exchange traded funds (ETFs) that are actively traded on the NYSE Arca, based on methodology developed by Chordia et al.

The authors estimate the speed of convergence to market efficiency based on short‐horizon return predictability from past order flows of 273 ETFs that were traded every day on the NYSE Arca during the first six months of 2008, and compare the resulting price formation process to that of shares traded on the NYSE and NYSE Arca.

Despite the significant differences in trading costs, volatility, and informational effects between ETFs and regular stocks, the paper documents that price adjustments to new information for ETFs occur in about 30 minutes, which is comparable to price adjustments for traditional stocks traded on Arca. In multivariate setting, the paper further shows that the speed of convergence to market efficiency of ETFs is not only significantly driven by volume, but also by the probability of informed trading.

The findings provide direct answers and insights to questions posed in a recent SEC concept release document. The analysis of the speed of convergence provides a feasible measure to assess how efficiently prices of ETFs respond to new information.

The authors are first to utilize the short‐horizon return predictability from historical order flow approach to evaluate the price formation process of ETFs and to provide evidence on the determinants of its efficiency.

The aim of this study is to examine the impact of mandatory International Financial Reporting Standards (IFRS) adoption on the informational efficiency, market stability, and price adjustment of underlying stocks in Europe.

This study examines 1,187 stocks from 20 European countries to assess the impact of the mandatory adoption of IFRS on certain aspects of the market quality of the adopting firms.

The observed decrease in the first order autocorrelation and the permanent component of the conditional variance indicates that the mandatory IFRS adoption enhances informational efficiency and contributes to the market stability of the underlying stocks. The authors find no evidence that IFRS adoption affects the role old news has in determining the conditional variance of adopting firms. The effects of IFRS adoption on the equity cost of capital are shown to depend on the country‐specific characteristics. Specifically, IFRS adoption is more likely to increase (decrease) the betas of stocks that are listed in the common (civil) law countries.

Like any empirical event‐study, the validity of the results depends on the absence of confounding events.

To the best of the authors’ knowledge, this paper is the first to use GARCH type models to empirically examine the effects of mandatory IFRS adoption on the informational efficiency and market stability of adopting firms.