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This study investigates the time evolution of market efficiency in the Japanese stock markets, considering three indices: Tokyo Stock Price Index (TOPIX), Tokyo Stock Exchange Second Section Index, and TOPIX-Small. The Hurst exponent reveals that the Japanese markets are inefficient in their early stages and improve gradually. TOPIX and TOPIX-Small showed an anti-persistence around the year 2000, which still persists. The degree of multifractality varies over time and does not show that the Japanese markets are permanently efficient. The multifractal properties of the Japanese markets changed considerably around the year 2000; this may have been caused by the complete migration from the stock trading floor to the Tokyo Stock Exchange's computer trading system and the financial system reform, also known as the 'Japanese Big Bang'.

Online reviews represent an important decision aid for consumers. Therefore, the question of whether online reviews reflect the currently available information is of high importance. Nevertheless, previous research neglects information processing on online review platforms. We address this research gap and analyze whether restaurant health inspection results have an impact on the review generation process of online restaurant reviews. We find that while severe health inspection results lead to changes of online review star ratings, information processing depends on the current environment. We find indications for corrective actions after critical health inspections: on the one hand, the restaurant health score improves, which shows an increase in restaurant quality. On the other hand, we observe indications for an increased amount of fake reviews in case of poorly-graded restaurants. We contribute to theory by providing an understanding of the nature of information processing on online review platforms. For practitioners, our findings allow for an understanding of the dynamics of online review generation. Furthermore, we outline the importance of considering the risk of deceptive behavior.

Share prices reflect available financial information about those firms and a substantial amount of these information come from financial statement figures. The informativeness of the reported earnings and book values in financial statements depend on accounting standards that govern their preparation, thus accounting standards could influence the informativeness of financial statement figures as well as the degree to which investors consider these figures in making investment decision. This relevance of accounting figures to investors is referred to in existing literature as value relevance. This study investigated the relationship between value relevance and the adoption of International Financial Reporting Standards (IFRS). Most pioneer studies on value relevance and changes in accounting standards discovered a decline in the value relevance of financial statements in the US while most of the reviewed studies that address IFRS specifically discovered an increase in value relevance in the respective markets after adoption of IFRS. A few studies also reported a lack in improvement of value relevance following IFRS adoption but attributed the results to anomalies like government interference, mock compliance, improper enforcement, firm-specific differences and business changes that are outside the scope of financial reporting. The study recommended the adoption of IFRS standards as a possible factor that can improve value relevance.

The specific properties of assets such as cryptocurrencies, gold, and stocks have welcomed more empirical studies in assessing their nexus. As a result, market conditions, whether good or bad, become imperative to assess the benefits of safe have, hedges or diversification. Also, the presence of uncertainties in markets may have asymmetrical effects which make it necessary to assess their impact over time. The emergence of COVID-19 pandemic as a global uncertainty has altered the dynamics of most financial markets. Consequently, this may influence the lead/lag relationships in most financial time series at various frequencies to contribute to the heterogeneous nature of market participants. Hence, the study examines the interdependencies between cryptocurrencies, selected stocks markets of Africa, and Gold returns in a time-frequency domain before and during the COVID-19 pandemic. Using a day-to-day observations, from August 8th, 2015 to May 5th, 2020, we assess the benefits of portfolio diversification, hedges, and safe haven with the bi-wavelet technique. The findings reveal that gold and cryptocurrencies provide a safe haven, diversification and, hedge for investors of African stock especially in the Ghanaian stock market (short-term) and also during this COVID-19 period. These findings contribute to the literature on financial market interdependencies, asymmetries to demonstrate financial market participants' diverse investment horizons. Again, policymakers and governments of these stock markets should institute a sound system of controls in regulating stock markets. This will enable the benefits of safe haven, hedges or diversification to be efficiently realized for Gold and Cryptocurrencies during different market conditions.

The objective of this study was to examine the level and behaviour of the weak-form efficiency of the 16 most capitalised cryptocurrencies using intraday data. The study employed martingale difference hypothesis tests utilising the rolling window method. The predictability of high frequency returns varied over time. For most of the time, the cryptocurrencies were unpredictable. Nevertheless, their weak-form efficiency appeared to decrease along with an increase in frequency. In general, most cryptocurrencies were marked by high levels of unpredictability. However, there were some significant differences between the most and least efficient ones. To exploit market inefficiencies, investors should focus on higher frequencies. Higher frequencies should also be a concern to regulators when it comes to ensuring market efficiency.

In this study, we examine the random walk hypothesis for two well-known Indian indices, BSE (Sensex) and NSE (Nifty), by considering country-specific political events (parliamentary elections). Two pertaining questions were studied. First, efficiency with respect to weak form, semi-strong form, and strong form; and second, the random walk pattern of the return by applying the new variance ratio tests. We use 21 years of daily closing stock price data of both the National Stock Exchange (NSE) Nifty Index and the Bombay Stock Exchange (BSE) Sensex Index. The hypothesis is tested by using both conventional and new variance ratio tests: The Lo–MacKinlay variance ratio test, the Chow–Denning test, and Wright’s Rank and Sign test. All three tests report that the return does not follow the random walk for the full sample, suggesting the possibility of making gains by exploiting various investing strategies. It was found that both Indian indices follow the random walk hypothesis during the phase of parliamentary elections. This study contributes to the existing literature on the Efficient Market Hypothesis (EMH).

This article examines the adaptive market hypothesis in the five most important Latin American stock indices. To that end, we apply three versions of the variance ratio test, as well as the Brock-Dechert-Scheinkman test for nonlinear predictability. Additionally, we perform the Dominguez-Lobato and generalized spectral tests to evaluate the Martingale difference hypothesis. Moreover, we consider salient news related to the plausible market inefficiencies detected by these four tests. Finally, we apply a GARCH-M model to assess the risk-return relationship through time. Our results suggest that the predictability of stock returns varies over time. Furthermore, the efficiency in each market behaves differently over time. All in all, the analyzed emerging market indices satisfy the adaptive market hypothesis, given the switching behavior between periods of efficiencies and inefficiencies, since the adaptive market hypothesis suggests that market efficiency and market anomalies might coexist in capital markets. Este artículo examina la hipótesis del mercado adaptativo en los cinco índices bursátiles más importantes de América Latina. Para tal fin, aplicamos tres versiones de la prueba de razón de varianza (VRT), así como la prueba de Brock-Dechert-Scheinkman (BDS) para predictibilidad no lineal. Adicionalmente, realizamos las pruebas Domínguez-Lobato (DL) y generalized spectral (GS) para evaluar la hipótesis de la diferencia Martingala. Además, consideramos las noticias más destacadas relacionadas con las plausibles ineficiencias del mercado detectadas por estas cuatro pruebas. Finalmente, se aplicó un modelo GARCH-M para evaluar la relación riesgo-rendimiento a lo largo del tiempo. Nuestros resultados sugieren que la predictibilidad de los rendimientos de las acciones varía con el tiempo. Además, encontramos que la eficiencia en cada mercado se comporta de manera diferente a lo largo del tiempo. Así, los índices de mercados emergentes analizados satisfacen la hipótesis del mercado adaptativo, debido al comportamiento cambiante entre períodos de eficiencias e ineficiencias, ya que la hipótesis del mercado adaptativo sugiere que la eficiencia del mercado y las anomalías del mercado pueden coexistir en los mercados de capital.

This study has investigated the changing efficiency for the phase III EU ETS CO 2 market using the daily historical data of allowance future prices and coverage from August 2015 to December 2020. We have applied two alternative tests for checking dependency by linear and nonlinear methods to achieve this goal, including generalized spectral ( GS ) and automatic portmanteau ( AQ ). Also, we had a comprehensive look at the carbon market evolution and the EU ETS scheme development over time. The analysis of observed results validates the adaptive market hypothesis (AMH) in the market, which corresponds with the oscillatory behavior of the applied test statistics’ p -values. The other aspect of the study was to analyze the existence of evolutionary behavior on the market. To reach this purpose, we checked the results by applying a rolling window technique with four different time windows (50, 100, 150, and 250 days) on the test statistics in harmony with the adaptive market hypothesis. The obtained results show that overall, market efficiency has been improved by implementing higher window lengths.

This article assesses cyclical market efficiency under different market conditions. We examine the cyclical return predictability, the time-varying effectiveness of trading strategies and their profitability, along with the relationships between volume and price. We select a diverse set of indices namely Nifty Next 50, BSE Sensex, IBOV (Brazil) and JSE (South Africa) and use the data for the years 2005 to 2022. We use linear and non-linear autocorrelation tests, regression analysis and Granger causality tests to explore the different phases of market efficiency across these indices. Our results offer a multifaceted understanding of market efficiency, highlighting various aspects of the data across different regions and market structures. We cross-validate our findings, adding robustness to our understanding of the manifestation of the adaptive market hypothesis (AMH) in the global stock markets. We use a rolling window framework and structural break tests to ensure that our findings are resilient to potential structural changes. The results reveal varying degrees of market efficiency across all indices, providing useful implications for both academia and industry. Our results show that portfolio diversification benefits exist. Future research could examine whether the markets across and within countries offer diversification benefits. Market efficiency has been a topic of interest for a long time. Different papers and books have been written examining different forms of market efficiency like weak form, semi-strong form and strong form. However, studies have shown that markets are not always efficient in different forms. Markets do exhibit efficiency at some point in time and efficiency is not found at another point in time. Therefore, market efficiency is said to be time varying. We investigate this time varying nature of market efficiency in the context of adoptive market hypothesis (AMH) by using the market indices data of four different markets across three emerging economies and test the AMH. We examine the cyclical return predictability, the time-varying effectiveness of trading strategies and their profitability, along with the relationships between volume and price in the data. To investigate the cyclical characteristics of market efficiency, we select a diverse set of indices namely Nifty Next 50 (representing companies in the growth phase), BSE Sensex (a mature market index from India), IBOV (Brazil) and JSE (South Africa) and use the data for the years 2005 to 2022.We employ a combination of linear and non-linear autocorrelation tests, regression analysis and Granger causality tests to explore the different phases of market efficiency across these indices. The results reveal varying degrees of market efficiency across all indices, providing useful implications for both academia and industry. Our results show that portfolio diversification benefits do exist. if appropriate markets are used. Future research could examine whether the markets across countries and withing countries offer diversification benefits.

This paper investigates the time-varying efficiency of Western European stock markets and examines how macroeconomic events defined as endogenous and exogenous shocks influence the degree of efficiency by either long-range dependence or mean reverting. We apply a rolling-window detrended fluctuation analysis (DFA) with two window sizes, complemented by the Efficiency Index to synthetize multiple measures of market efficiency. The results confirm that efficiency evolves dynamically in response to macroeconomic disruptions. Specifically, endogenous shocks tend to generate anti-persistent behavior, while exogenous shocks are associated with long-memory effect. These shifts in efficiency are also reflected in rolling Kurtosis estimates, suggesting that only the most severe shocks produce spikes in Kurtosis, fat-tailed returns distributions, and structural inefficiencies. This dual approach allows us to classify shocks as major or minor based on their joint impact on both market efficiency and tail behavior. Overall, our findings support the adaptive market hypothesis and extend its implications through the fractal market hypothesis by underlining the role of heterogenous investment horizons during periods of turmoil. The combined use of dynamic DFA and Kurtosis offer a framework to assess how financial markets adapt to different types of macroeconomic shocks.