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.

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.

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.

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.

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.

An Empirical Analysis of the Efficient Market Hypothesis in China's Stock Market

The efficient market hypothesis is one of the most important theories in finance.According to this hypothesis,in a stock market with sound laws,good functions,high transparencies,and extensive competitions,all valuable information is timely,accurately,and fully reflected in the trend of stock prices including the current and future values of enterprises.Unless there are market manipulations,it would be impossible for investors to gain more above the average profits in the market by analyzing former prices.Since the efficient market hypothesis has been introduced,it has become an interest in the empirical research of the security market.It is one of the most controversial investment theories and there are many evidences supporting and also opposing this hypothesis.Nevertheless,this hypothesis still holds an important status in the basic framework of mainstream theories in modem financial markets.By analyzing simulated investment transactions in regard to stock trading of three different enterprises,this paper verified that the efficient market hypothesis is partially valid.

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.

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.

The Efficiency of the Chinese Commodity Futures Markets: Development and Empirical Evidence

This study investigates the efficiency of the Chinese metal futures （i.e. copper and aluminum） traded on China＇s Shanghai Futures Exchange. First, we thoroughly analyze the development of China＇s commodity futures markets, which provides a fundamental background. Then we examine the random walk and unbiasedness hypotheses for two metal futures during 1999-2004. Based on the empirical evidence, we argue that China＇s copper and aluminum futures markets are efficient, and that they aid the process of price discovery because futures prices can be considered as unbiased predictors of future spot prices. We attribute this efficiency to the regulatory changes made in 1999 and the increased financial skills and acumen of the participants in the market.

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.

R/S Analysis of China Securities Markets

This paper presents the law of changes of indices and stocks in the Shanghai and Shenzhen Stock Exchanges by using rescaled range analysis in nonlinear time series analysis. The Hurst exponents of the stock indices and of all stocks listed in the Shanghai and Shenzhen Stock Exchanges are estimated. The results show that the changes of indices and stocks in the last period have positive impact in the next period in the short run, but this impact disappears for long time.

The impact of patent citation information flow regarding economic innovation on common stock returns:Volume vs.patent citations

This study examines whether the number of forward patent citations(along with alternative patent data)dwhen used as a proxy for the mixing variabledcould infer the aggregate amount of economic-innovation information arriving at the New York Stock Exchange(NYSE)in the United States.The results show that the number of forward patent citations,when used as a mixing variable,fails to eliminate total volatility persistence in the conditional variance equation of the exponential generalized autoregressive conditional heteroscedastic(EGARCH)model.However,the trading volume successfully eliminates total volatility persistence,thus confirming the validity of the framework used.When the volatility is modeled with an expectation of mean return,the persistence of conditional variance is deterministically increased,and the sum of the volatility coefficients exceeds unity.The inclusion of trading volume with a time trend in the variance equation rectifies the deterministic increase in the conditional volatility.These findings suggest that the form of heteroscedasticity(i.e.,as per the autoregressive conditional heteroscedastic model,ARCH model)in NYSE portfolio returns is based on the type of shocks to volatility(e.g.,deterministic vs.stochastic),which manifests as news arrivals(i.e.,new information arrivals proxied by trading volume)at the stock market.The volume therefore reflects the time dependence in the innovations to the ARCH error generation process.The response of volatility to volume persists over time when the volatility estimates are derived from the EGARCH model with an expectation for the mean of return.Backward patent citations,patent applications,and patents issued have been found to interact somewhat with trading volume,suggesting that each of these variables could play the role of an absorptive capacity variable as the new information flow associated with economic innovation(i.e.,flow of firms’stock of new knowledge)could be picked up by the trading volume.

Linguistic specificity and stock price synchronicity

Linguistic specificity effectively reduces barriers to information cognition,increasing the efficiency of information acquisition,integration and processing.Combining the psycholinguistics theory of the concreteness effect with assetpricing theory,we determine that linguistic specificity in the management discussion and analysis section of a firm’s annual reports is negatively associated with stock price synchronicity,particularly in firms with strong external information demand or insufficient information supply.Furthermore,only specificity of the review section leads to a reduction in stock price synchronicity.Mechanism tests show that specificity reduces information processing costs and enhances information credibility.Additionally,proprietary costs are an essential determinant of linguistic specificity adoption.Our findings suggest that linguistic specificity plays an essential role in improving market pricing efficiency.