Weak-form Efficiency Research Articles

An Entropic Analysis of Efficiency in the West Texas Intermediate Crude Oil Futures Market

For the last 50 years or so, the efficient market hypothesis (EMH) has been the central pillar of economic thought and the building block of portfolio theory. However, the validity of the EMH still remains controversial, and the methods of testing for market efficiency have been criticised. This study utilises entropy analysis combined with generalised autoregressive conditional heteroscedasticity (GARCH) regressions to provide extensive empirical evidence on informational efficiency. This study develops an innovative method for studying market efficiency by investigating the complexity of information saturated in the market. To this end, we have used daily West Texas Intermediate (WTI) crude oil futures contracts from June 1983 to February 2016, giving a total data set of 282,427 observations. The results of the Jensen–Shannon informational criteria indicate that the informational efficiency measure has never reached the maximum value of 1 which indicates weak-form efficiency. Our study has further found that the informational efficiency measure tends to decrease consistently during recessionary periods and to increase in subsequent periods. We have also found that the entropy measure tends to increase over time, supporting the adaptive market hypothesis over the EMH.

Evolving Efficiency of Cryptocurrency Market: Evidence from Leading Cryptocurrencies

The article investigated the efficiency of the cryptocurrency market, with a focus on Bitcoin (BTC), Ethereum (ETH), Tether (USDT), and Binance Coin (BNB-USD), based on their substantial market capitalization. For this purpose, we observed the daily closing prices spanning from January 2018 to December 2023 and employed a set of robust tests, including the generalized spectral test, automatic portmanteau test, and automatic variance ratio test. The findings of the study reveal a random pattern in price fluctuations, indicating weak form efficiency. Furthermore, we adopted the rolling window approach to investigate whether market efficiency is dynamic or static over time. The empirical result illustrated that the crypto market efficiency remains static over time, except for USDT. In conclusion, the overall empirical results support the notion of the random walk hypothesis, indicating that past price movements offer no predictive insight into future prices. These findings have significant implications for investors, emphasizing the lack of predictive insight from past price movements. Policymakers are urged to establish a robust framework for market integrity and reliable price discovery.

Testing the weak-form efficiency of Arab stock markets after the COVID-19 pandemic

Weak-form efficiency means that stock prices should reflect all historical information and follow a random walk. This study examines the effect of the COVID-19 pandemic on the stock market weak-form efficiency of Arab countries, namely, Jordan, Lebanon, Kuwait, Morocco, Oman, Palestine, Bahrain, Egypt, Iraq, Qatar, Saudi Arabia, the United Arab Emirates, Syria, Tunisia, and Sudan. Daily data from July 1st, 2021 to November 12th, 2022 (370 trading days) are used to cover the period after starting the pandemic. The variance ratio and the runs test are used to test return predictability. The results show that the variance ratio values of Boursa Kuwait, the Egyptian Exchange, Tadawul, and the Amman Stock Exchange are statistically significant, indicating that their returns are unpredictable. In specific, the indices of these stock markets follow a random walk, and their price changes are independent. This is evidence that these stock markets are efficient at a weak level. In contrast, the insignificant values of the variance ratio indicate that returns are predictable in other Arab stock exchanges after the pandemic era. The findings of the Egyptian Exchange, Tadawul, and the Amman Stock Exchange are confirmed using the run test of weak-form efficiency. It reveals that the indices of these stock exchanges follow a random walk, while the indices of other Arab stock markets do not.

Impact of Subprime and Covid-19 crises on WAEMU stock exchange efficiency: a classic Hurst vs dynamic Hurst approach

Financial markets are alternative sources of financing, above all, in the current context of financial globalization and the development of information and telecommunication technologies. In the WAEMU zone in particular, the size of the economies seemed insufficient to supply national markets without high costs. The union’s authorities therefore set up a regional market that seemed to be a beneficial outcome : the WAEMU stock market. This stock exchange has undergone significant modernizations since its inception, with the aim of achieving optimal resource allocation. The informational efficiency of this stock exchange has become a hot topic of interest among researchers and professionals, giving rise to a growing number of publications on the subject. Our article is set in this context and aims to analyze the WAEMU’s weak-form efficiency. Based on the limitations of traditional methods, we use new approaches. Firstly, the classic Hurst is a tool for characterizing market structure and analyzing efficiency. The results highlight the multifractal nature of the WAEMU’s market and the rejection of the null hypothesis of no memory in the return series. Given the resurgence of crises, it would be interesting to analyze stock market behavior during such events. We also study the impact of crises (subprime and covid-19) on efficiency, using the dynamic Hurst exponent to account for efficient market varying with time. The results show that during periods of crisis, the stock market alternates between efficiency and inefficiency. They also reveal that Covid-19’s impact was faster than subprime crisis. They also reveal that covid impact crisis was faster than that of subprimes. However, despite the big spike linked to the covid context, the composite index picked up and continued in the same vein.

Exploring the relationship between Chinese crude oil futures market efficiency and market micro characteristics

This paper uses daily frequency data spanning from March 26, 2018 to February 3, 2023, and combines the exponential generalized autoregressive conditional heteroskedasticity in mean (EGARCH-M) model with the time-varying parameters state-space (TVPSS) model to dynamically test the efficiency of the Chinese crude oil futures market (CCOFM). Additionally, the paper examines the relationship between market efficiency and market micro characteristics such as market depth, market liquidity, noise trading, speculation rate, and information asymmetry. The results show that the CCOFM exhibited weak-form efficiency in June 2020, which lasted until the end of February 2022, and after that, the efficiency showed a poor development trend. Analyzed from the macro level, the Market Maker System and Trader Suitability System have a positive effect on market efficiency, while the Russian-Ukrainian conflict has a negative effect on market efficiency. Analyzed from the micro level, market depth and information asymmetry have a positive effect on market efficiency, while the speculation rate has a negative effect on market efficiency, and noise trading and market liquidity have no significant effect on market efficiency. Market efficiency has a positive effect on market depth and a negative effect on speculation rate. Market liquidity and noise trading have a positive effect on speculation rate, while both information asymmetry and market liquidity have a negative effect on noise trading. In addition, speculation rate has a weak negative effect on information asymmetry, and market depth and speculation rate have a weak positive effect on market liquidity. This study provides theoretical support and decision-making foundation for the development of CCOFM by dynamically exploring the relationship between CCOFM efficiency and micro characteristics.

Examining the Random Walk Hypothesis: An investigation of the Indian stock market

Using the Efficient Market Hypothesis (EMH) as the theoretical foundation, this research study explores the Random Walk Hypothesis in the context of the Indian stock market. By using the Runs Test to analyse the daily closing prices of eight well-known Indian companies between January 1, 2018, and June 30, 2021, the study finds that patterns in stock prices in the Indian stock market show weak-form efficiency and are consistent with the Random Walk Hypothesis. The analysis indicates that stock price movements are largely unpredictable and devoid of discernible patterns, aligning with the notions posited by proponents of the Efficient Market Hypothesis. The research underscores significant implications, validating the presence of weak-form efficiency and emphasizing the need for alternative analytical approaches in investment strategies. Despite inherent limitations, this study contributes to ongoing discourse on market efficiency and financial dynamics, advocating for interdisciplinary approaches and global perspectives to refine understanding and facilitate more informed investment decisions in the Indian capital market.

Health Care REIT Returns & Covid-19: A Note

This study tests for pricing efficiency in Healthcare Real Estate Investment Trusts (REITs) surrounding the Covid-19 pandemic. Fractal analysis is used to ascertain whether any persistence or anti-persistence in returns can be observed over the “pre-Covid” and “Covid/post-Covid” periods for the 15 healthcare equity REITs included in the FTSE NAREIT US Real Estate Index. The results point to weak form efficiency during the complete sample period with some exceptions. A relative stability in Hurst exponents exists across the sub-periods for several of the REITs. However, there is evidence that many other REITs series switch from being anti-persistent to persistent, a result consistent with possible herding behavior. Some very limited evidence is found of series switching from being persistent to anti-persistent, consistent with investor overreaction for these REITs. Overall, inefficient pricing is seen in a limited number of cases, but there is a strong suggestion of a possible change like the return dynamic in the latter part of the study period associated with the pandemic.

Borsa İstanbul Katılım Endekslerinin Etkin Piyasa Hipotezi Analizi: Zayıf Formda Etkinlik İncelemesi

Endeks, borsada işlem gören yatırım araçlarının maliyetlerinde, fiyatlarında ve satışlarında belirli bir dönem içindeki göreli oynaklığı hesaplayan bir göstergedir. İslami endeks, İslam'ın hukuk kurallarına uygun olarak düzenlenen bir endekstir. İslami kurallar çerçevesinde faaliyet gösteren bir borsa endeksi olarak da nitelendirilebilir. Domuz eti, konvansiyonel finans, döviz işlemleri, faiz, alkollü içkiler, tütün ürünleri, kumar, şans oyunları, gümüş, yetişkinlere yönelik filmler, silahlar ve altın gibi faaliyetlerde bulunan şirketler bu endeksin faaliyetlerine dahil edilmemektedir. Etkin Piyasalar Hipotezi (EPPPH), kısaca piyasalarda var olan fiyatların her türlü bilgiyi içerdiğini, dolayısıyla bu bilgileri kullanarak normalin üzerinde bir getiri elde etmenin imkansız olduğunu ifade etmektedir. Bu çalışmanın amacı beş BIST katılım endeksi (BIST Katılım 30, BIST Katılım 50, BIST Katılım 100, BIST Katılım Sürdürülebilirlik ve BIST Katılım Tüm endeksleri) için zayıf formda etkin piyasalar hipotezini test etmektir. Uluslararası literatürde katılım (İslami) endekslerinin zayıf formdaki etkinliğini test eden pek çok akademik çalışma bulunmaktadır. Bu çalışmalardan bazıları yalnızca İslami endeksleri test ederken, diğerleri İslami ve geleneksel endekslerin karşılaştırmalı olarak zayıf formda etkinliğini test etmektedir. Ayrıca finansal kriz dönemlerinde İslami endekslerin sektörel zayıf formdaki etkinliği de araştırmalara konu olmuştur. Ayrıca gelişmiş ekonomilerde ve İslami finans piyasalarında İslami endekslerin etkinliği karşılaştırılmıştır. Türkiye'de yerel İslami endekslerin zayıf formda etkinlik testlerine yönelik çalışmalar sınırlıdır. Bu çalışmada BIST İslami endekslerin zayıf formdaki etkinliği analiz edilmektedir. Çalışmamız BIST adı altında katılım endekslerinin etkinliğine ilişkin yapılan ilk çalışma özelliğini taşımaktadır. Ayrıca ulusal şirketlerin yer aldığı katılım endekslerinin etkinliğine ilişkin daha önce yapılan çalışmalarda koşu (runs) testinin yöntem olarak kullanılmadığı tespit edilmiştir. Bu özellikleriyle çalışmanın Türkiye'deki yerli İslami endekslere ilişkin literatüre katkı sağlayacağına inanmaktayız. Bu çalışmada öncelikle 16.11.2021 - 06.09.2023 tarihleri arasında analize konu olan BİST Katılım endeksleri fiyat serilerinin normal dağılım sergileyip sergilemediğini araştırılmıştır. Bu amaçla basıklık (skewness), çarpıklık (kurtosis) ve Jarque - Bera istatistiklerini içeren tanımlayıcı istatistiksel yaklaşımlar kullanılmıştır. Daha sonra her bir zaman serisinde birim kök olup olmadığına ilişkin Augmented Dickey - Fuller (ADF) ve Phillips - Perron (PP) birim kök testleri yapılmıştır. Bunlara ek olarak, serilerin rassal bir düzen sergileyip sergilemediğini belirlemek için koşu testi (runs test) de yöntem olarak kullanılmıştır. Veri olarak BIST Katılım endekslerinin (BIST Katılım 30, BIST Katılım 50, BIST Katılım 100, BIST Katılım Sürdürülebilirlik ve BIST Katılım Tüm endeksleri) 16.11.2021 ile 06.09.2023 tarihleri arasındaki 453 günlük kapanış değeri üzerinden hesaplanan getirileri kullanılmıştır. Bu tarihlerin seçilmesinin en önemli nedeni BIST katılım endekslerinin bu isimle 16.11.2021 tarihinde kamuya açıklanmaya başlamasıdır. Normallik dağılımı sonuçlarına göre BIST katılım endekslerinin tamamı zayıf etkinlik formu koşulunu sağlayamamıştır. Ayrıca her iki birim kök testinin sonuçları da tüm getiri serileri için %1 anlamlılık düzeyinde anlamlıdır. Bu durum katılım endekslerinin getiri serilerinin durağan olduğunu göstermektedir. Getiri serilerinin durağan olması zayıf formda etkinliğin olmadığı ve serilerin rassal yürüyüş sergilemediğinin bir göstergesidir. Son olarak koşu testine göre getiri serilerinde diğer yukarıda bahsedilen analizlerde olduğu gibi rassal bir yürüyüş bulunmadığı tespit edilmiştir. Bu çalışma, üç farklı yöntem (normallik sınamaları, ADF ile PP birim kök testleri ve koşu testi) kullanılarak Türkiye'de faaliyet gösteren BİST katılım (İslami) endekslerin zayıf formda etkin olmadığı sonucuna varmıştır. Bu sonuçlarla Türkiye’deki katılım (İslami) endekslerin oluşturduğu piyasaların istenilen etkinliğe ve derinliğe ulaşmadığı görülmektedir.

Weak-Form Efficiency of Emerging Markets: Empirical Analysis on Day of the Week Effect with Conditional Heteroskedasticity Models

Etkin bir piyasada fiyatların rassal hareket ettiği, bilgilerin hisse senedi fiyatlarına hızlıca yansıdığı kabul edilmektedir. Bu nedenle hisse senetlerinin geçmiş fiyat hareketlerinden yararlanılarak borsa endeks getirisinden fazla kazanç elde edilemez. Fakat bazen farklı sonuçlarla karşılaşılmakta bu durum anomali olarak adlandırılmaktadır. Anomali, herhangi bir piyasanın etkinliğinin test edilmesinde kullanılmaktadır. Haftanın günleri anomalisinde, haftanın belirli gün veya günlerinde diğer günlere nazaran sürekli düşük veya yüksek getiri edinilmektedir. Bu çalışmada gelişmekte olan ülkelerin piyasalarının zayıf formda etkinliği incelenmek istenmiştir. Haftanın günlerine göre ortalama getirilerde ve volatilitelerde olası değişiklikleri tespit etmek için BIST100 Borsa Endeksi (Türkiye), BVSP Borsa Endeksi (Brezilya), MOEX Borsa Endeksi (Rusya), NIFTY50 Borsa Endeksi (Hindistan) ve SSEC Borsa Endeksinin (Çin) 14 Ocak 2002 ile 14 Nisan 2023 tarihleri arasındaki günlük kapanış verilerinden yararlanılmıştır. Önce, borsa endekslerinin günlük kapanış puanlarının logaritmik farklarıyla getiriler hesaplanmış, birim kök testleriyle verilerin durağanlık koşulunun sağlandığı görülmüştür. Daha sonra Autoregressive Conditional Heteroskedasticity (Otoregresif Koşullu Değişen Varyans) (ARCH) etkisinin varlığı tespit edildiğinden ARCH-GARCH modellerle tahminler yapılmış, kriterlere göre her bir borsa endeksine ait en uygun model seçilmiştir. Elde edilen bulgular ışığında, BVSP Borsa Endeksinin ortalama getirilerinde Pazartesi günü anomalisinin, SSEC Borsa Endeksinin ortalama getirilerinde ise Perşembe günü anomalisinin olduğuna ulaşılmıştır. BIST100 Endeksinde Pazartesi, Salı, Perşembe ve Cuma günlerinin volatilitede etkisinin olduğu; SSEC Borsa Endeksinde Pazartesi, Salı ve Perşembe günlerinin volatilitede etkisinin olduğu; MOEX ve NIFTY50 Borsa Endekslerinde ise Pazartesi ve Salı günlerinin volatilitede etkisinin olduğu; ayrıca BVSP Borsa Endeksi dışındaki tüm endekslerde olumsuz şokların volatilitede olumlu şoklara göre daha fazla etkili olduğu tespit edilmiştir.

Study on the Efficiency of China's Convertible Bond Market Based on ARMA-GARCH Models

This study examines the prediction and analysis of China's convertible bond market using a combined ARMA and Generalized GARCH model. If this model can effectively achieve its predictive goals, it indirectly suggests that China's convertible bond market has not yet reached weak-form efficiency. The study focuses on the Shenzhen Investment Grade Convertible Bond Index, utilizing daily closing price data from January 2, 2019, to June 18, 2024, as the sample, providing a robust empirical foundation for the model. Empirical results indicate that the constructed model effectively captures the volatility patterns of current convertible bond yields, implying that historical price data holds certain predictive significance for current prices. Furthermore, through empirical analysis using the GARCH-M(1, 1) model, we find a relationship between yield volatility in the convertible bond market and historical risk levels. This suggests that market risk may not be fully priced rationally, as historical risk levels can help forecast current yield volatility, further confirming that China's convertible bond market has not yet achieved weak-form efficiency

An Empirical Study on the Efficiency of China's Convertible Bond Market

Since 2017, with the increased demand for margin financing and securities lending in the capital market and the improvement of relevant regulations, China's convertible bond market has experienced a boom. As of March 9, 2024, China has issued a total of 823 convertible bonds, amounting to 1.3 trillion yuan. The stock of convertible bonds has expanded from 24 bonds totalling 55.9 billion yuan at the end of 2016 to 553 bonds totalling 853.3 billion yuan. The importance of convertible bonds in the capital market has become increasingly prominent, becoming an essential part of financial tool diversification and market development. However, academic research on the convertible bond market is relatively scarce, mostly focusing on pricing mechanisms, financing effects, and the impact on the underlying stock prices, with little attention paid to the market itself. This paper uses runs tests, autocorrelation tests, and variance ratio tests to analyze the efficiency of China's convertible bond market. By examining whether the daily returns of the convertible bond index follow a random walk, the paper tests if the market is weak-form efficient. The results show that China's convertible bond market has not reached weak-form efficiency. Subsequently, a new index sample was created from the top ten convertible bonds by trading volume in May 2024, and its daily returns were tested for adherence to the random walk model. The results were compared to the overall market's convertible bond index returns in the same period of 2023 to identify factors influencing market efficiency, providing directions and insights for future research.

Testing weak form efficiency of the Egyptian and Saudi stock markets

Testing weak form efficiency of the Egyptian and Saudi stock markets

TESTING WEAK-FORM EFFICIENCY FOR THE SAUDI PARALLEL MARKET (NOMU)

Market efficiency is essential for a thriving stock exchange and has a substantial impact on capital investments, particularly in emerging markets. This article examines the weak-form efficiency of Nomu, the Saudi Arabian parallel stock exchange. The study employed various statistical tests on the collected closing values of the Nomu index from May 1, 2019, to May 31, 2023. The return normality and stationarity were investigated using the Jarque-Bera, Augmented Dickey-Fuller (ADF), and Phillips-Perron (PP) tests. The Variance Ratio (VR) test was used to assess autocorrelation, while the Wald-Wolfowitz Runs (WWR) test was utilized to examine random walk behavior. While the Runs test indicated some randomness, all other tests rejected their null hypotheses, indicating that the Nomu market is inefficient according to the weak-form model. This inefficiency suggests that historical trading data may predict future prices, which could discourage foreign capital inflows, thereby limiting Nomu's growth and investment appeal. The significance of these findings for regulators and policymakers in formulating market regulations and policies aimed at enhancing Nomu's efficiency and investor appeal cannot be overstated. This paper, with its robust methodology, is believed to be the first to evaluate the Nomu market's weak-form efficiency since its inception, contributing to a better understanding of market dynamics in emerging stock exchanges.

The Impact of COVID-19 on Weak-Form Efficiency in Cryptocurrency and Forex Markets.

The COVID-19 pandemic has had an unprecedented impact on the global economy and financial markets. In this article, we explore the impact of the pandemic on the weak-form efficiency of the cryptocurrency and forex markets by conducting a comprehensive comparative analysis of the two markets. To estimate the weak-form of market efficiency, we utilize the asymmetric market deficiency measure (MDM) derived using the asymmetric multifractal detrended fluctuation analysis (A-MF-DFA) approach, along with fuzzy entropy, Tsallis entropy, and Fisher information. Initially, we analyze the temporal evolution of these four measures using overlapping sliding windows. Subsequently, we assess both the mean value and variance of the distribution for each measure and currency in two distinct time periods: before and during the pandemic. Our findings reveal distinct shifts in efficiency before and during the COVID-19 pandemic. Specifically, there was a clear increase in the weak-form inefficiency of traditional currencies during the pandemic. Among cryptocurrencies, BTC stands out for its behavior, which resembles that of traditional currencies. Moreover, our results underscore the significant impact of COVID-19 on weak-form market efficiency during both upward and downward market movements. These findings could be useful for investors, portfolio managers, and policy makers.

Do technical trading rules outperform the simple buy-and-hold strategy in the cryptocurrency market?

The authors test the weak-form efficiency in cryptocurrency markets using the most recent and comprehensive data as of 2021. The authors apply various technical indicators to take a long or short position on 99 cryptocurrencies and compare the 10-day returns based on the technical trading strategies to the simple buy-and-hold returns. The authors find that the trading strategies based on single indicators or the combination of two indicators do not generate higher returns than buy-and-hold returns among cryptos. These findings suggest that cryptocurrency markets are weak-form efficient in general.

Can Machine Learning Outperform the Market? Testing the Weak-form Efficiency Hypothesis of the Indian Stock Market Using Support Vector Machines

This article examines the validity of the weak form of the efficient market hypothesis (EMH) in the context of the Nifty stock market index by applying a support vector machine (SVM) model. The aim is to forecast future stock prices using historical data and to evaluate the performance of the SVM model based on accuracy, precision, recall and the area under the receiver operating characteristic (ROC) curve (AUC). The findings offer important implications for the efficiency of the Nifty market and its consequences for investors. The EMH posits that stock prices incorporate all available information, making it impossible to consistently beat the market using historical data. This article tests this proposition by using an SVM model to forecast future stock prices using historical data. The methodology consists of applying the SVM algorithm on historical data of the Nifty stock market index. Performance measures, such as accuracy, precision, recall and AUC, are used to assess the effectiveness of the SVM model. The results show an accuracy of 63.25% in forecasting stock prices, indicating a substantial agreement between predicted and actual labels. The precision score of the model is 97.97%, indicating a high proportion of correctly predicted positive instances. However, the recall score is relatively low at 34.36%, suggesting that some actual positive instances were overlooked. The ROC curve visually illustrates the trade-off between true positive rate and false positive rate for different classification thresholds. This article contributes to the literature on market efficiency by applying a novel SVM model to forecast future stock prices of the Nifty index and finding that the model outperforms random chance, thus challenging the weak form of the EMH.

Measuring the competitiveness of commodity markets using price signals and information theory

Technological advancements, abrupt changes in market conditions, and political reforms, among other things, necessitate strong regulatory oversight, and accurate measurement of performance related indicators. The more accurate, information rich, and transparent these measurements/signals, the lower the level of uncertainty felt by value chain participants, who are thus able to recognize and observe whether the market’s state is efficient. Its lack, may lead to indecisiveness, translating into false interpretations that could lead to wrong policy directions. This paper provides an ex-post evaluation tool intending to deliver additional insights or quality information that would aid the regulator in assessing the state of the market. The tool is applied to the UK wholesale natural gas market for the period between 2011 and 2020, assessing and testing the market’s weak-form efficiency. It claims that today’s gas prices reflect a specific type of information, primarily past gas prices, and that only new information can help predict future prices. In this manuscript, based solely on a limited and available untapped dataset (day-ahead price time series), and working under the assumption that gas prices are the result of market processes, a variety of information metrics (gas price randomness, distribution of extreme prices, ability to predict prices - based on historical sets) is extracted with the use of suitable mathematical statistical models. A weighted entropy index is then computed, and measures the state of the commodity market. The results indicate that the analysis has helped gain information, thus reducing uncertainty (relative to a pre-analysis) by 86.5 %. Additionally, there is sufficient evidence that the UK natural gas prices are weak-form efficient.

The weak-form efficiency of cryptocurrencies

This study aimed to examine the weak-form efficiency of some of the most capitalised cryptocurrencies. The sample consisted of 24 cryptocurrencies selected out of 30 cryptocurrencies with the highest market capitalisation as of October 19, 2022. Stablecoins were not considered. The study covered the period from January 1, 2018 to August 31, 2022. The results of robust martingale difference hypothesis tests suggest that the examined cryptocurrencies were efficient most of the time. However, their efficiency turned out to be time-varying, which validates the adaptive market hypothesis. No evidence was found for the impact of the coronavirus outbreak and the Russian invasion of Ukraine on the weak-form efficiency of the examined cryptocurrencies. The differences in efficiency between the most efficient cryptocurrencies and the least efficient ones were noticeable, but not large. The results also allowed to observe some slight differences in efficiency between the cryptocurrencies with the largest market cap and cryptocurrencies with the lowest market cap. However, the differences between the two groups were too small to draw any far-reaching conclusions about a positive relationship between the market cap and efficiency. The obtained results also did not allow us to detect any trends in efficiency.

Assessing and interpreting carbon market efficiency based on an interpretable machine learning

The urgency of addressing climate change and reducing carbon emissions necessitates the establishment of effective carbon markets. Our paper focuses on assessing and interpreting the efficiency of carbon markets, which is a crucial aspect of their successful implementation. We selected Hubei, Shenzhen, and Guangdong carbon pilots as examples to measure their dynamic information efficiency by combining the rolling time window and wild-bootstrap variance ratio test. Furthermore, we combined SHapley Additive exPlanations (SHAP) and Extra Trees (ET) regressor to reveal the nonlinear relationship between market performance and efficiency. Our findings highlight the time-varying nature of carbon market efficiency and reveal that China's carbon market has not yet achieved stable weak-form efficiency. Additionally, we identified excessive trading volume volatility as a significant constraint on market efficiency, while the trading volume itself exhibits weak explanatory power. Our proposed hybrid model demonstrates superior predictive and explanatory capabilities, offering regulators a valuable tool for continuously monitoring and interpreting carbon market efficiency. Finally, we suggested that reducing trading volume volatility should be a major concern for regulators to optimize market operations at present.

Assessing market efficiency in Palestine Securities Exchange (PSE) market at weak form: Analysis from 2010–2022

The efficient market hypothesis (EMH) asserts that financial markets are efficient, meaning that current market values of stocks incorporate all available information. This study examines the weak-form efficiency of Palestine Stock Exchange stocks using the indices returns from 2010 to 2022. The study used parametric tests (Augmented Dickey-Fuller (ADF) unit root, serial autocorrelation) and nonparametric tests (Phillips-Perron (PP) unit root, run test, variance ratio test). The findings of these tests provide insights into the behavior of the Palestine Stock Exchange market. The run test outcomes reveal a statistically significant pattern in the data for general, insurance, and service indices, with a p-value below the significance level. Furthermore, the unit root tests indicate statistical significance for all indices with 0.00 p-values and t-statistic below the critical values of –2.86 for level and intercept, and –3.14 for level, trend, and intercept, signifying that the indices returns are stationary. In addition, serial autocorrelation test show that the general and Al-Quds indices show statistically significant links between consecutive observations at all four lags. However, the insurance, investment, and services indices show statistically significant results on three lags. The variance ratio test results challenge the random-walk hypothesis for all indices except industry and insurance. With low probability values, a discernible, long-term, predictable pattern is evident in the Palestine Stock Exchange indices. The analysis reveals that Palestine Stock Exchange index returns exhibit nonrandom behavior, suggesting predictability and patterns in daily returns, indicating the possibility of exploiting market inefficiencies in investment strategies.