The effect of overseas investors on local market efficiency:evidence from the Shanghai/Shenzhen–Hong Kong Stock Connect

Using a recent stock market liberalization reform policy in China—the Stock Connect—as a quasi-natural experiment,this study examines the effect of stock market liberalization on market efficiency.Employing a dataset of 17,086 Chinese listed firms covering 2009 to 2018,we find that stock market liberalization improves the market efficiency of the Chinese mainland stock market.We further explore the potential channels through which the Stock Connect can enhance the efficiency of the A-share(A-shares refer to shares issued by Chinese companies incorporated in China's Mainland,traded in the Shanghai Stock Exchange and the Shenzhen Stock Exchange.They are denominated in Chinese RMB(the local currency).A-shares were restricted to local Chinese investors before 2003,are open to foreign investors via the Qualified Foreign Institutional Investor,RMB Qualified Foreign Institutional Investor,or the Stock Connect programs.)market.The findings show that liberalizing capital markets could benefit local market efficiency by increasing stock price informational efficiency and improving corporate governance quality.The additional analysis shows that stock market liberalization has a significant and positive impact on local market efficiency,enhancing firm value and reducing stock crash risk.We conduct various robustness checks to corroborate our findings.This study provides important policy implications for emerging countries liberalizing capital markets for foreign investors.

How to compare market efficiency? The Sharpe ratio based on the ARMA-GARCH forecast

This paper derives a new method for comparing the weak-form efficiency of markets.The author derives the formula of the Sharpe ratio from the ARMA-GARCH model and finds that the Sharpe ratio just depends on the coefficients of the AR and MA terms and is not affected by the GARCH process.For empirical purposes,the Sharpe ratio can be formulated with a monotonic increasing function of R-squared if the sample size is large enough.One can utilize the Sharpe ratio to compare weak-form efficiency among different markets.The results of stochastic simulation demonstrate the validity of the proposed method.The author also constructs empirical AR-GARCH models and computes the Sharpe ratio for S&P 500 Index and the SSE Composite Index.

Efficiency of Stock Exchange Markets in G7 Countries： Bootstrap Causality Approach

Market efficiency is based on efficient market hypothesis （EMH）. EMH claims that market totally contains the available information. In case of EMH, valid investors who take position will not gain abnormal profits. If the efficiency can not be established, that is, if markets are not efficient, investors will have the opportunity of abnormal profits. This paper investigates the causality relations to determine validity of EMH among G7 （Canada, France, Germany, Italy, Japan, United Kingdom, and United States） countries＇ stock exchange markets for the period from July 2003 to October 2014. To find out whether the variables cause each other or not provides knowledge about the market efficiency. The implication of this analysis is twofold. One implication is that if the markets are informationally efficient, the possibility of abnormal returns through arbitrage is ruled out and investors can reduce the risk of their investment for the same expected returns, if they establish portfolios that consist of both markets rather than consisting of only one market. Based on this, Hacker-Hatemi-J. bootstrap causality test that is newer and has many advantages contrary to other tests was used. Results showed that EMH is valid among each G7 countries＇ stock exchange markets. Also portfolio diversification benefits exist among these markets.

Real estate market efficiency: Evidence from Chinese cities

The price in an efficient market can adjust to new information instantaneously to eliminate any arbitrage opportunities. Such a phenomenon is not always observed in the real estate market because of its unique characteristics, which include fixed location, heterogeneity and low transaction frequency. Using housing and office market data of some major cities in China, this paper examines the return and risk characteristics in these markets and assesses market efficiency. It finds that a number of instruments, including lagged quarterly and annual excess returns and, to some extent, the measure of the deviation of price from the intrinsic value, predict future returns. Therefore, weak form and semi-strong form efficiency can both be rejected in these real estate markets. These empirical findings suggest that there is slow price adjustment in real estate markets in China, which may be attributed to inefficient information transmission systems and long searching time in the markets.

Carbon trading thickness and market efficiency in a socialist market economy

Unlike the European Union emission trade system(EU ETS), China s pilot ETSs implemented diversified policy designs instead of using a uniform framework. Variance ratio test is used to evaluate the Efficient Market Hypothesis(EMH) in China's carbon trading markets. The results of two versions of variance ratio tests indicate that the carbon trading market in Hubei is considered weak form efficient, and the socialist market economy does not necessarily lead to market inefficiency in carbon trading markets. Thin trading activities generate market frictions and bias the Efficient Market Hypothesis(EMH) tests.

Cryptocurrencies,gold,and WTI crude oil market efficiency:a dynamic analysis based on the adaptive market hypothesis

This study examined the evolving oil market efficiency by applying daily historical data to the three benchmark cryptocurrencies(Bitcoin,Ethereum,and Ripple),gold,and West Texas Intermediate(WTI)crude oil.The data coverage of daily returns was from August 2015 to April 2019.We applied two alternative tests to examine linear and nonlinear dependency,i.e.,automatic portmanteau and generalized spectral tests.The analysis of observed results validated the adaptive market hypothesis(AMH)in all markets,but the degree of adaptability between the data was different.In this study,we also analyzed the existence of evolutionary behavior in the market.To achieve this goal,we checked the results by applying the rolling-window method with three different window lengths(50,100,and 150 days)on the test statistics,which was consistent with the findings of AMH.

Testing the Semi-strong Form Efficiency of Islamic Capital Market With Response to Information Content of Dividend Announcement： A Study in Jakarta Islamic Index

The specific concepts of Islamic capital market are based on transparency, accountability, and no asymmetric information. A capital market is said to be efficient with respect to an information item if the prices of securities fully impound the return implication of that item. This study has two main objectives. Firstly, for testing the efficiency of Islamic capital market which focuses on Jakarta Islamic Index （JII）. Secondly, by this research finding the regulator can make a good solution to create the real Islamic capital market. This study concludes that the Islamic capital market is not efficient in information. This is proved by test, where the result for both mean adjusted model and market adjusted model shows not significant, which means that the stock price that occurred has not been able to reflect a strong relationship with the real conditions that exist within the company. The second conclusion is the magnitude of abnormal return suggests that the market still has asymmetric information that will cause the occurrence of abnormal return. This is very unfortunate because Islamic capital market should be efficient in reflecting information transparency that could create a fair price in accordance with the real condition of the company＇s stock issuance.

A Literature Review about Demonstrating Whether China＇s Stock Market Has Reached Weak-form Efficiency

The efficient Market Hypothesis divided the stock market into three parts： weak-form efficiency, semi-strong-form efficiency, and strong-form efficiency. There are so many scholars have conducted researches on whether China＇ s stock market has reached weak-form efficiency. The author of this literature review summaries the results of these researches and makes a systematic induction. This article attempts to show the achievements of these researches and ~ive readers new ideas about how to improve China＇ s stock market efficiency.

Study on the Interior Market Network Structure and Its Efficiency in a Knowledge Based Company

A knowledge based company is the microcosmic foundation of the knowledge economy, the design of its organization structure should amplify the company competence to be agile to the knowledge elements. This paper expounds an interior market network structure which is fit for the company intellectual capital operation, and analyses this organization pattern about the reasons of existence, the effectiveness of growing up in scale, the economies of knowledge distribution and the efficiency of operation, and it will provide some beneficial theoretical guidance about how can a company improve its competition competence in the knowledge environment through organization innovation.

Does Margin Trading Enhance Information Efficiency of the Capital Market?——Evidence from China

On March 31,2010,China formally introduced a margin trading system,which announced that China's capital market has completed the transformation from a unilateral transaction model to a bilateral transaction model with a short-selling mechanism.However,the current development of China's margin trading and securities lending businesses is seriously unbalanced,and the scale of financing far exceeds the scale of securities lending.The short selling effect of securities lending exchanges is extremely limited,which to some extent violates the original intention of introducing the system.In order to help margin trading and securities lending to correct a healthy and sustainable development path,this article uses stock price synchronicity as a proxy indicator to measure the information efficiency of the capital market,explores the impact of the margin trading system on the information efficiency of the capital market,and study the detailed characteristics and economic consequences of the margin trading system.Aiming at this topic,this article analyzes the relationship between margin financing and securities lending and stock price synchronicity.Finally,it analyzes the influence of margin financing and securities lending system on stock price synchronicity from three dimensions of corporate governance,external supervision,and institutional environment mechanism.In terms of empirical research,this article takes advantage of the“quasi-natural experiment”provided by the gradual opening of margin trading and securities lending in China’s securities market,and selects listed companies on the Shanghai and Shenzhen stock exchanges from 2007 to 2019 as the research objects,starting from the perspective of stock price synchronicity,and passing The DID-FE model studies the impact of the margin trading and securities lending system on the information efficiency of the capital market.It uses three methods:parallel trend and dynamic testing,PSM-DID analysis,and placebo testing for robustness testing to solve the endogeneity problem of the experiment.This article also conducts deeper research on the subject based on the two dimensions of the impact mechanism of margin financing and securities lending and the size of the company,and finally discusses the economic impact of margin financing and securities lending on the level of company innovation.

Social–financial approach for analyzing financial transitions

This study proposes a social-financial approach(SFA)to fill the methodological research gap in strategic policy design for managing financial transitions during social changes.The SFA seeks to characterize inclusive transitions in response to innovation and analyze financial management in social changes.Using a multilevel perspective,we combine evolutionary finance and inclusive growth analytics into this framework.We contend that the interaction between the different levels can be summarized as spontaneous adjustments and the alignment of financial elements with the indicators.Actors who attempt to achieve their goals based on past performance evaluations and other forms of bounded rationality strive to cope with adjustments and further trigger a reorientation of the existing regime.We also developed a new configuration tool called the three-axis description to describe the evolution of financial transitions at different stages.These methods allow us to analyze the evolution of financial transition and efficiency,and we argue that market efficiency evolves in stages with the finan-cial transition.Finally,to demonstrate the capability of SFA to identify diverse financial transition pathways,we examined an example case:the establishment of the Bretton Woods System.

Holt-Winters Algorithm to Predict the Stock Value Using Recurrent Neural Network

Prediction of stock market value is highly risky because it is based on the concept of Time Series forecasting system that can be used for investments in a safe environment with minimized chances of loss.The proposed model uses a real time dataset offifteen Stocks as input into the system and based on the data,predicts or forecast future stock prices of different companies belonging to different sectors.The dataset includes approximatelyfifteen companies from different sectors and forecasts their results based on which the user can decide whether to invest in the particular company or not;the forecasting is done for the next quarter.Our model uses 3 main concepts for forecasting results.Thefirst one is for stocks that show periodic change throughout the season,the‘Holt-Winters Triple Exponential Smoothing’.3 basic things taken into conclusion by this algorithm are Base Level,Trend Level and Seasoning Factor.The value of all these are calculated by us and then decomposition of all these factors is done by the Holt-Winters Algorithm.The second concept is‘Recurrent Neural Network’.The specific model of recurrent neural network that is being used is Long-Short Term Memory and it’s the same as the Normal Neural Network,the only difference is that each intermediate cell is a memory cell and retails its value till the next feedback loop.The third concept is Recommendation System whichfilters and predict the rating based on the different factors.

Design of Robust Var Reserve Contract for Enhancing Reactive Power Ancillary Service Market Efficiency

In a deregulated Var market, market power issue is more serious than in an energy market since reactive power cannot be transmitted over long distances. This letter designs a multi-timescale Var market framework, where market power that may arise in the hourly-ahead Var support service market due to system configuration deficiency and market structure flaws can be eliminated by day-ahead contract-based Var reserve service market. Settlement of day-ahead Var reserve contract is formulated as a two-stage robust optimization (TSRO) model considering worst case of uncertainty realization and potential market power that may arise in hourly-ahead market. TSRO with integer recourses is then solved by a new column and constraint generation algorithm. Results show a robust Var reserve contract can fully eliminate market power, and prevent suppliers from manipulating market prices.

No more free lunch:The increasing popularity of machine learning and financial market efficiency

In this paper,we show that the increasing popularity of machine learning improves market efficiency.By analysing the performance of a set of popular machine learning-based investment strategies,we find that profits from these strategies experience significant declines since the wide adoption of machine learning techniques,especially for profits based on the more preferred method of neural networks.These declines mainly come from long legs.Using the‘machine learning’Google search index as a proxy for machine learning-based trading intensity,we find that returns from the neural networks-based long–short and long-only strategies are weaker following high levels of machine learning intensity,while no relation is found between machine learning intensity and the short-only neural networks-based strategy.

Assessing the maturity of China's seven carbon trading pilots

Indicators based on the developed version of the Capability Maturity Model were set up to access the maturity degree of China's seven pilot carbon markets from 2013 to 2017. Results show that the maturity degree of Shenzhen and Beijing pilot carbon markets ranks first;while those of Guangdong, Hubei, and Shanghai rank second. Tianjin and Chongqing rank lowest. Most of pilot markets failed to perform well on price efficiency except Shenzhen. There is significant disparity in the scores that the pilot carbon markets got, with a range from 9 to 73. The drivers to maintain market maturity is different among the pilot markets, either with a good performance on market structure, scale, or efficiency could lead to a certain score. Much could be done to increase the maturity level of the carbon market. Further downscaling the firm size, raising the legislation level, and increasing the participation of the third party entities may help the carbon market to grow healthier.

S&P BSE Sensex and S&P BSE IT return forecasting using ARIMA

This study forecasts the return and volatility dynamics of S&P BSE Sensex and S&P BSE IT indices of the Bombay Stock Exchange.To achieve the objectives,the study uses descriptive statistics;tests including variance ratio,Augmented Dickey-Fuller,Phillips-Perron,and Kwiatkowski Phillips Schmidt and Shin;and Autoregressive Integrated Moving Average(ARIMA).The analysis forecasts daily stock returns for the S&P BSE Sensex and S&P BSE IT time series,using the ARIMA model.The results reveal that the mean returns of both indices are positive but near zero.This is indicative of a regressive tendency in the longterm.The forecasted values of S&P BSE Sensex and S&P BSE IT are almost equal to their actual values,with few deviations.Hence,the ARIMA model is capable of predicting medium-or long-term horizons using historical values of S&P BSE Sensex and S&P BSE IT.

Daily Patterns in Stock Returns： Evidence From the New Zealand Stock Market

In this paper, we study day-of-the-week effects in stock retums across different industry sectors in the New Zealand market. Unlike other studies on this market, we examine weekday seasonality using daily stock return data of four market indexes and 16 industry sectors for the period from October 1, 1997 to April 16, 2009. We do not find significant Monday anomalies of the market index, large capitalization stock index and all industry sectors except for the property sector. Our finding is inconsistent with the literature on the New Zealand stock market. However, we find that the mid and small capitalization stocks have significant negative returns on Mondays than on other weekdays, which is consistent with the previous studies in some other markets.

Monthly Seasonality in the Top 50 Australian Stocks

We studied monthly seasonality in the top 50 Australian stocks across different industry sectors. Unlike other Australian studies, we examined monthly seasonality using stock return data of individual companies for the period of January 1980 through to August 2010. We found that stock returns of over half of the 50 companies are significantly positive in April and December, and most companies have low stock returns in October. Seven companies have higher returns in April than in other months of the year, most of which are banking and financial services companies, while six companies have lower returns in February than in other months. Although Australia has a July-June taxation cycle, we found that only three stocks have a July anomaly. The findings are inconsistent with the tax-loss selling hypothesis and other studies on the Australian equity markets （e.g., Brown, Keim, Kleidon, ＆ Marsh, 1983; Brailsford ＆ Easton, 1991）. However, our findings are generally consistent with Bonin and Moses （1974） on individual stock seasonality

Nonlinearity in Stock Exchange Markets: The Case of Bist 100 Indices

In this paper,using data for the Bist 100 index,we investigate the presence of nonlinearities by employing several nonlinearity tests.The Brock,Dechert,and Scheinkman(BDS)and runs tests were first applied to the series to show an initial indication of nonlinearity.The findings for the BDS and runs test of randomness were followed by other sets of direct nonlinearity tests developed by White(1989),Terasvirta(1993),Keenan(1985),and Tsay(1986).Also,the Threshold Autoregression(TAR)test is employed as a final test to confirm the existence of nonlinearity in the Turkish stock exchange market.From the results of the nonlinearity test,it is concluded that the Bist 100 index is characterised by the presence of nonlinearities and cycles.This finding is in contrast with the efficient market hypothesis(EMH)implying that the Turkish stock exchange market is inefficient.

The Efficient Market Theory and Mergers and Acquisitions （M＆As） Puzzle： Evidence From Italy

The efficient market theory is a central point in finance. If the capital market is competitive, the investors cannot expect superior gains from their investment strategies with respect to the risk profile. Event studies are an approach to verify the impact of the information on the stock prices. In an efficient market, stock prices should fully, promptly, and quickly capture all the information. Instead, the market shows phenomena of an under-reaction and over-reaction for both the short and the long run. The mergers and acquisitions （M＆As） are examples of anomalies. Often, the bidder companies record the negative abnormal returns for both the short and the long run. In contrast to the efficient market theory, the empirical evidence shows that this phenomenon is widespread in all （or most of） the countries of the world. This work examines the long-run performance in M＆As. For this purpose, 40 bidders were observed in Italy during the period of 1994-2008 among listed companies. The buy and hold abnormal returns （BHARs） methodology was used, with which it was possible to observe the returns for three years following the deal.