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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 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.

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.

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’s goal was to identify how several markets have developed over time and what determinants have influenced this process, based on adaptive markets hypothesis (AMH). In this regard, the authors consider that agents are driven by the seeking for abnormal returns to stay “alive” and their environment could somehow modify their decision-making processes, as well as influence the degree of efficiency of the market.

The authors collected the daily closing-of-the-market index from 50 countries, between 1990 and 2022. The sample includes emerging countries, developed countries and frontier markets. Then, the authors ran multilevel modeling using Hurst exponent as an informational efficiency metric estimated by two different moving windows: 500 and 1,250 observations (approximately 2 and 5 years).

The results indicate that the efficiency of the markets is not constant over time. The authors also have identified that markets follow a cyclical pattern of efficiency/inefficiency, and they are currently in a period of convergence to efficiency, possibly explained by the increase in computational capacity and speed of the available information to agents. In addition, this study identified that country characteristics are associated with market efficiency, considering institutional factors.

Studies of this nature contribute to the literature, considering the importance of better comprehension of market efficiency dynamics and their determinants, specially observing other theories on the relationship between information and markets (like AMH), which work with other investor assumptions than those used by efficient market hypothesis.

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.

This paper aims to enhance the existing literature on adaptive market hypothesis (AMH) as this study first time links the month of Ramadan with AMH that permits the performance of well-known Ramadan effect to fluctuate over time.

To fulfill the purpose, the authors inspect the daily returns of 107 individual firms listed at Pakistan Stock Exchange over the period of 20 years. To explore the varying degree of return predictability during Ramadan, the authors use four different subsamples comprising equal length of observations of five years each. The authors use a GARCH (1,1) regression model which facilitates for time varying nature of volatility in equity returns. To facilitate the non-normal nature of stock return data, the authors use Kruskal–Wallis test statistic.

The authors find that behavior of Ramadan effect evolves over time, as performance of this effect varies from time to time and consistent with AMH. Finally, the paper proposes that AMH is well elucidation of behavior of Ramadan effect than traditional efficient market hypothesis.

First limitation is related to the choice of sub-sample as the study uses a sub-sample of five years. Second, the authors ignore transection cost (commissions, fee and taxes) as it is freely negotiated and varies between 4 and 10% (Khan, 2013). Due to such varying information we ignore the transaction cost. It is suggested that a sub-sample analysis of long period may be a more appropriate method to elucidate the idea of AMH in future research and suggest the current method could be adapted and helpful to examine other calendar and market anomalies in different equity markets.

The paper includes implications for investors to choose a better model for investment. Investors can exploit greater returns in future month of Ramadan periods. Furthermore, the researchers can easily extend the methodology used in the study to address multiple issues like adaptive behavior of returns from bonds, real estate investment trusts, cryptocurrencies and trading rules of strategies.

Study confirms from sample t-test and GARCH (1,1) model that Ramadan effect is present in the full and in certain sub-samples; therefore, based on these discrepancies investors can earn abnormal returns by developing specific investment strategies as investors usually make investments in share according to the religious context of Islamic Calendar. The results provide good references for suitable time of investment in stock market. The findings of this study will be helpful to investors and brokers as well as portfolio managers to capture favorable returns across the Islamic calendar.

The paper identified need to study why behavior of Ramadan effect varies over time. The data set comprises daily returns of 107 individual companies over the period of 20 years to better investigate the varying nature of anomalous effect of month of Ramadan. The findings are valuable for international investors and portfolio managers.

The authors aim to verify the indicators that influence the efficiency reported by Brazilian listed financial companies.

The sample consists of companies in the financial segment that have shares traded in B3, comprising nine institutions from 2000 to 2018 were selected. The authors adopted the regression model with unbalanced panel data to analyze the data. The dependent is the efficiency, which the authors calculated using Hurst Exponent. As independent variables, we used the sector-specific indicators: earnings management, banking resilience, management efficiency, and profitability. The authors controlled the models by size and type of control.

The findings indicate that the efficiency of financial companies' securities is affected by aspects related to management, resilience, and efficiency in administration. The lower the earnings management, the greater the banking resilience, the efficiency in the management of resources, and the efficiency of stock prices of these companies. These results show that efficiency is affected by intrinsic factors of the entities, corroborating the hypothesis that markets adapt, among others, to institutional factors.

Many users of financial institutions understand whether their stock prices reflect the information provided by accounting. The findings are original because they provide evidence that institutional factors affect the efficiency of companies in the Brazilian financial segment.

The purpose of this paper is to analyse the adaptive market efficiency in the price–volume (P–V) relationship of the stocks listed in the Mexican Stock Exchange. The period under study goes from 1982 to 2015. In order to detect causality and, thus, determine adaptive efficiency in the market, one linear and two non-linear tests are applied. There are few papers in the literature that study the P–V relationship in Latin American markets; as such, this paper may be of interest and importance to financial academics and practitioners alike.

The Diks and Panchenko (DP) non-parametric Granger causality and the Brooks and Hinich (BH) cross-bicorrelation tests are applied.

Derived from the DP test, the findings show that there exists bi-directional non-linear Granger causality in 25.71 per cent of the firms studied, compared to 8 per cent when applying the linear Granger causality test. Therefore, there is evidence of weak-form efficiency in the market. From the BH test, evidence is shown of the adaptive market efficiency, since 71.42 per cent of firms exhibited some form of non-linear dependence in certain periods of time. With these results, the information process should be better studied for a greater comprehension of regulatory policies in the market and better decision-making tools for the investors.

This paper complements studies on the P–V relationship and efficiency in a Latin American market.

Este documento analiza la eficiencia adaptativa del mercado para la relación precio-volumen de las empresas que cotizan en la Bolsa Mexicana de Valores. El periodo bajo estudio es de 1982 a 2015. Para detectar causalidad y determinar la eficiencia adaptativa del mercado, se aplicó una prueba lineal y dos no-lineales. Existen pocos documentos en la literatura que estudien la relación precio-volumen en mercados latinoamericanos. Como tal, este documento puede ser de interés e importancia tanto para académicos como para profesionales de las finanzas.

Se aplicó la prueba de causalidad no-paramétrica de Diks y Panchenko y la prueba de bicorrelación cruzada de Brooks y Hinich.

Derivado de la prueba DP, los hallazgos muestran que existe causalidad no-lineal bidireccional en 25.71% de las empresas bajo estudio, comparado a un 8% cuando se aplica la prueba de causalidad lineal de Granger. Por lo tanto, existe evidencia de eficiencia en forma débil del mercado. De la pruba BH, se muestra evidencia de eficiencia adaptativa del mercado, dado que el 71.42% de las empresas exhibieron alguna forma de dependencia no-lineal en ciertos periodos de tiempo. Con estos resultados, el proceso de información debe ser mejor estudiado para una mayor comprensión de las políticas regulatorias del mercado y mejores herramientas para la toma de decisiones por los inversionistas.

Este documento complementa los estudios sobre la relación precio-volumen y la eficiencia en un mercado latinoamericano.

This study broadly attempts to explore adaptive or dynamics patterns of calendar effects existed in the cryptocurrency market as per the adaptive market hypothesis (AMH) framework. Another agendum of this study is to investigate the quantum of extra returns which may result from the presence of calendar effects.

The present study considers both parametric and non-parametric approaches to verify calendar effects empirically. Specifically, this study has implemented Generalised Autoregressive Conditional Heteroscedasticity (1, 1) and Kruskal–Wallis tests in the rolling window approach to reveal adaptive patterns of calendar effects. Additionally, the present study has used the implied trading strategy to evaluate the volume of excess returns resulted from calendar effects than buy-and-hold (BH) strategy.

The overall results of the current study exhibit that calendar effect in the cryptocurrency market is dynamic rather than static which indicates the calendar effect is a time-varying phenomenon. Moreover, this study also confirmed that ITS is not suitable to obtain extra returns despite the existence of calendar effects.

The present study has covered some broad aspects of calendar anomalies in the cryptocurrency market, keeping aside certain other limitations which need to be addressed in the following dimensions. Future studies may aim at addressing issues like, Turn-of-the-Year effect, Halloween effect, weather effect, and Month-of-the-Year effects, and try to explore the reasons of presence of dynamic patterns of calendar effects.

The significant implication of this study is that it alerts investors about market return predictability due to calendar patterns or effects in different periods. It also suggests the period in which the ITS can perform better than the BH strategy.

It is the first study in the cryptocurrency literature which has adopted the AMH framework to verify adaptive calendar effects or anomalies. Furthermore, this study, instead of a mere examination of the presence of calendar effects, has evaluated the potential of calendar effects to produce extra returns through trading strategies.