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Showing papers on "Stock exchange published in 2016"


Journal ArticleDOI
TL;DR: In this paper, the impact of economic policy uncertainty on stock markets in the United States over the period 1900-2014 was studied and it was shown that an increase in policy uncertainty reduces significantly stock returns and that this effect is stronger and persistent during extreme volatility periods.

295 citations


Journal ArticleDOI
TL;DR: In this paper, the authors investigate the relationship between Corporate Social Responsibility and financial performance in Spanish listed companies and demonstrate that the social is profitable and that the profitable is social, thereby originating a positive feedback virtuous circle.

283 citations


Journal ArticleDOI
TL;DR: In this article, the ability of artificial neural network (ANN) in forecasting the daily NASDAQ stock exchange rate was investigated, and several feed forward ANNs that were trained by the back propagation algorithm have been assessed.

272 citations


Proceedings ArticleDOI
26 Jun 2016
TL;DR: A novel application of deep learning models, Paragraph Vector, and Long Short-Term Memory, to financial time series forecasting and models the temporal effects of past events on opening prices about multiple companies with LSTM is proposed.
Abstract: This paper proposes a novel application of deep learning models, Paragraph Vector, and Long Short-Term Memory (LSTM), to financial time series forecasting. Investors make decisions according to various factors, including consumer price index, price-earnings ratio, and miscellaneous events reported in newspapers. In order to assist their decisions in a timely manner, many automatic ways to analyze those information have been proposed in the last decade. However, many of them used either numerical or textual information, but not both for a single company. In this paper, we propose an approach that converts newspaper articles into their distributed representations via Paragraph Vector and models the temporal effects of past events on opening prices about multiple companies with LSTM. The performance of the proposed approach is demonstrated on real-world data of fifty companies listed on Tokyo Stock Exchange.

251 citations


Journal ArticleDOI
TL;DR: In this paper, the authors explore the relation between global prices of gold, crude oil, the USD-INR exchange rate, and the stock market in India and highlight the need for dynamic policy making in India to contain exchange rate fluctuations and stock market volatility using gold price and oil price as instruments.

250 citations


Journal ArticleDOI
TL;DR: In this paper, the authors evaluate the potential implications of these changes for managers, institutional investors, small shareholders, auditors, and other parties involved in corporate governance, and propose that the lower cost, greater liquidity, more accurate record-keeping and transparency of ownership offered by blockchains may significantly upend the balance of power among these cohorts.
Abstract: Blockchains represent a novel application of cryptography and information technology to age-old problems of financial record-keeping, and they may lead to far-reaching changes in corporate governance. During 2015 many major players in the financial industry began to invest in this new technology, and stock exchanges have proposed using blockchains as a new method for trading corporate equities and tracking their ownership. This essay evaluates the potential implications of these changes for managers, institutional investors, small shareholders, auditors, and other parties involved in corporate governance. The lower cost, greater liquidity, more accurate record-keeping, and transparency of ownership offered by blockchains may significantly upend the balance of power among these cohorts.

197 citations


Journal ArticleDOI
TL;DR: In this article, the authors investigated the effect of gender-diverse boards on the association between sustainability reporting and shareholders' welfare and found that the presence of WDOCBs favorably influences on firm's risk and performance through promoting a firm's investment in effectual social engagements and reporting on them.
Abstract: Purpose As pressures mount for women directors on corporate boards (WDOCBs) from different stakeholders, companies become more interested in finding out how WDOCBs impact sustainability disclosure. The purpose of this paper is to investigate the effect of gender-diverse boards on the association between sustainability reporting and shareholders’ welfare. Design/methodology/approach This paper examines the implications of women on board for firm-related factors, particularly environmental, social and governance (ESG) disclosure and firm performance. The firms studied are all listed in the Financial Times Stock Exchange 350 index between 2007 and 2012. Bloomberg social disclosure score is used and panel data through a regression model are applied. Findings The results reveal that the presence of WDOCBs favorably influences on firm’s risk and performance through promoting a firm’s investment in effectual social engagements and reporting on them. The desirable effect of WDOCB on the ESG-performance relationship leads to increased risk-adjusted and buy-and-hold abnormal returns and reduced firm risks, measured by both volatility of returns and systematic risk. Originality/value The research contributes to the literature on the relationship between women participation on corporate boards and firms’ good citizenship and enhanced shareholders’ welfare. The empirical findings contribute to providing statistical and economical validity to the UK Corporate Governance Code 2014 recommendation on the importance of board gender diversity for effective board functioning.

174 citations


Journal ArticleDOI
01 May 2016
TL;DR: A hybrid time-series ANFIS model based on EMD based on empirical mode decomposition (EMD) to forecast stock prices in the Taiwan Stock Exchange Capitalization Weighted Stock Index and Hang Seng Stock Index is proposed.
Abstract: This paper proposes a hybrid time-series ANFIS model based on EMD to forecast stock price.In order to evaluate the forecasting performances, the proposed model is compared with other models.The experimental results show that proposed model is superior to the listing models. Time series forecasting is an important and widely popular topic in the research of system modeling, and stock index forecasting is an important issue in time series forecasting. Accurate stock price forecasting is a challenging task in predicting financial time series. Time series methods have been applied successfully to forecasting models in many domains, including the stock market. Unfortunately, there are 3 major drawbacks of using time series methods for the stock market: (1) some models can not be applied to datasets that do not follow statistical assumptions; (2) most time series models that use stock data with a significant amount of noise involutedly (caused by changes in market conditions and environments) have worse forecasting performance; and (3) the rules that are mined from artificial neural networks (ANNs) are not easily understandable.To address these problems and improve the forecasting performance of time series models, this paper proposes a hybrid time series adaptive network-based fuzzy inference system (ANFIS) model that is centered around empirical mode decomposition (EMD) to forecast stock prices in the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and Hang Seng Stock Index (HSI). To measure its forecasting performance, the proposed model is compared with Chen's model, Yu's model, the autoregressive (AR) model, the ANFIS model, and the support vector regression (SVR) model. The results show that our model is superior to the other models, based on root mean squared error (RMSE) values.

153 citations


Journal ArticleDOI
TL;DR: In this paper, the authors examined the dynamic relationship among local stock returns, foreign exchange rates, interest differentials, and U.S. S&P 500 returns in BRICS countries, including Brazil, Russia, India, China, and South Africa.

126 citations


Posted ContentDOI
TL;DR: In this article, the authors proposed an alternative approach to estimate China's capital stock series by region as well as across three economic sectors (agriculture, industry and services) and preliminary analyses of the derived capital stock statistics are conducted to examine growth, disparity and convergence in China's regional economies.
Abstract: The lack of capital stock statistics for empirical research of the Chinese economy has for a long time been one of the major impediments in the profession Professor Gregory Chow is one of the pioneers who attempted to deal with this matter His seminal paper on China's capital formation and economic growth was published in 1993 (Chow, 1993) Since then many authors have estimated their own capital stock data series However, most authors have focused on investigations at the national level and their findings are not without controversies In particular, few studies have provided estimates of capital stock for China's regional economies This paper adds to the existing literature in several ways First, it presents a critical review of the methods and findings in the existing literature Second, it proposes an alternative approach to estimate China's capital stock series by region as well as across three economic sectors (agriculture, industry and services) Finally, preliminary analyses of the derived capital stock statistics are conducted to examine growth, disparity and convergence in China's regional economies

116 citations


Journal ArticleDOI
TL;DR: In this paper, the authors investigated the effect of corporate governance quality on earnings management in Jordan using a panel data set of all industrial and service firms listed on Amman Stock Exchange (ASE) during the period 2009-2013.
Abstract: This paper investigates the effect of corporate governance quality on earnings management in Jordan. Using a panel data set of all industrial and service firms listed on Amman Stock Exchange (ASE) during the period 2009-2013; this paper provides evidence that earnings management is affected negatively by corporate governance quality. In particular; the results show that earnings management is affected negatively by overall categories of governance index represented by board of director, board meeting, Audit and nomination and compensation committee. Furthermore, results suggest that corporate governance quality has increased over time. Thus, its ability to constrain earnings management has also increased. It is recommended to industrial and service companies to boost their compliance with corporate governance code to improve the integrity and reliability of financial reports. This paper fills a gap in the literature by providing evidence about the effect of corporate governance quality on earnings management in Jordan as an emerging economy.

Journal ArticleDOI
TL;DR: In this article, the authors examined the relationship between corporate governance and firm performance of listed Ghanaian companies using a longitudinal and cross-sectional data set of 20 sampled companies over a period of five years and found that ownership concentration and female representation on board have a positive impact on performance.
Abstract: Purpose The purpose of this paper is to examine the relationship between corporate governance and firm performance of listed Ghanaian companies. Design/methodology/approach The paper adopts a longitudinal and cross-sectional data set of 20 sampled companies over a period of five years. The data were analyzed using a panel regression and ANOVA analysis to establish the relationship between corporate governance and firm performance. Corporate governance is defined in terms of three indices – board structure, ownership structure and corporate control, while firm performance is measured by return on assets, return on equity, net profit margin and Tobin’s Q. Findings The empirical results show that ownership concentration and female representation on board have a positive impact on performance. Although the results revealed no evidence to support the impact of board size and audit committee size on performance, there is significant evidence to support the fact that independent directors and audit committee frequency both adversely affect firm performance. Research limitations/implications The scope of this paper can be expanded to include non-listed firms. In addition, other corporate governance mechanisms could be considered to broaden the scope of the paper. Originality/value This paper contributes to the scarce literature on corporate governance and firm performance in developing countries, especially in sub-Saharan Africa. The paper provides useful information that is of great value to policymakers, academics and other stakeholders.

Journal ArticleDOI
TL;DR: In this paper, the authors investigate the time varying co-movements between crude oil and Indian stock market returns both at aggregate and sector level using weekly closing prices for Brent Crude, BSE-Sensex and seven sector indices of Bombay Stock Exchange.

Journal ArticleDOI
TL;DR: The results prove the robustness and effectiveness of the proposed exchange market algorithm and show that it could be used as a reliable tool for solving practical ELD problems.

01 Jan 2016
TL;DR: In this paper, the authors examined long-run and short-run relationship between Lahore Stock Exchange and macroeconomic variables in Pakistan, which revealed that there was a negative impact of consumer price index on stock returns, while, industrial production index, real effective exchange rate, money supply had a significant positive effect on the stock returns in the long run and VECM analysis illustrated that the coefficients of ecml (-1), and ecm2 (-1) were significant with negative signs.
Abstract: The movements in the stock prices are an important indicator of the economy. The intention of this study was to examine long-run and short-run relationships between Lahore Stock Exchange and macroeconomic variables in Pakistan. The monthly data from December 2002 to June 2008 was used in this study. The results revealed that there was a negative impact of consumer price index on stock returns, while, industrial production index, real effective exchange rate, money supply had a significant positive effect on the stock returns in the long-run. The VECM analysis illustrated that the coefficients of ecml (-1), and ecm2 (-1) were significant with negative signs. The coefficients of both error correction terms showed high speed of adjustment. The results of variance decompositions revealed that out of five macroeconomic variables consumer price index showed greater forecast error for LSE25 Index.

Journal ArticleDOI
TL;DR: In this paper, the authors investigate if the link between local air pollution and domestic equity returns is mediated by the trading floor community, using the transition of Italy's main stock exchange from a trading floor technology to an electronic and delocalized trading system as a natural experiment.

Journal ArticleDOI
TL;DR: In this paper, the Tobin's Q model was used to determine if there is significant influence between the company's profile such as industry, company age and its profitability with the firm value.
Abstract: The main objective of every company is to maximize the assets or firm value. Maximizing firm value is essential for a company because it means increasing the wealth of shareholders as well. This study aims to determine if there is significant influence between the company’s profile such as industry, company age and its profitability with the firm value using Tobin’s Q model. The proponents selected 86 diversified companies in the Philippines by gathering and analyzing annual financial reports on 2014 in the Philippine Stock Exchange (PSE) to obtain the objective of the study and also employed predictive correlational design. Frequency, Mean and Multiple Regression were used to determine the significant influence between the independent and dependent variables. The multiple regression reveals that of the three factors assumed to influence value of the firm using the Tobin’s Q, only profitability shows significant positive impact on the firm’s value.

Journal ArticleDOI
TL;DR: In this paper, the authors examined the relationship between intellectual capital and firm performance in Iran using the Pulic's model and found that intellectual capital is the main source of value creation in the modern economy.
Abstract: Today, competitive advantage and success are achieved by strategic management of intellectual capital rather than allocation of physical and financial resources. Although intellectual capital is not a tangible and objective factor, it is often measured in order to compare the market value and development of firms and improve their performance. This paper examines the relationship between intellectual capital and firm performance in Iran using the Pulic's model. In this model, value added intellectual coefficient is used to evaluate firms' intellectual capital. Also, the relationship between intellectual capital and firms' market value is examined. In addition to intellectual capital, the relationship between the components of intellectual capital—that is, human and structural capital—and performance is also investigated. The empirical data is collected from 100 firms listed on Tehran Stock Exchange (TSE) during the period 2000–2006. The results support the hypothesis that human and intellectual capital are positively related to performance (Tobin's Q), and intellectual capital can be taken into consideration for improving the performance of Iranian firms. Also, value added intellectual coefficient proves to be an effective tool that can be used by current decision-makers in Iran's capital market. The findings and discussions provided in this paper can be of interest to managers and capital market stakeholders. We emphasize that intellectual capital is the main source of value creation in the modern economy. Copyright © 2016 John Wiley & Sons, Ltd.

Journal ArticleDOI
TL;DR: In this paper, the authors found that analysts' forecast error and dispersion reduces as the level of alignment with the integrated reporting framework increases, and that the improved alignment is associated with a subsequent reduction in the cost of equity capital for certain reporting companies.
Abstract: Integrated reporting (IR) is an emerging international corporate reporting initiative arising to address, inter alia, the limitations of the current corporate reporting suite which are commonly criticized for being both voluminous and disjointed. While IR is gaining in popularity, current momentum is limited until there is clear evidence of benefits. Utilising the most suitable setting currently available, being disclosures in accordance with the Johannesburg Stock Exchange IR listing requirements, this study provides evidence of such benefits by finding that analysts’ forecast error and dispersion reduces as the level of alignment with the IR framework increases. Further, the improved alignment is associated with a subsequent reduction in the cost of equity capital for certain reporting companies. The results are obtained after controlling for factors relating to financial transparency and the issue of standalone non-financial reports, suggesting that IR is providing incrementally useful information over existing reporting mechanisms to the capital market.

Journal ArticleDOI
TL;DR: In this paper, the impact of innovations in US economic policy uncertainty on the co-movements of the Shanghai A-share, the Shenzhen A -share, Shenzhen B-share and the Shanghai C-share with the US stock market was investigated.
Abstract: This paper investigates the impact of innovations in US economic policy uncertainty on the co-movements of, respectively, the Shanghai A-share, the Shenzhen A-share, the Shanghai B-share and the Shenzhen B-share market, with the US stock market. We show that it is absolute changes in the US economic policy uncertainty index that have a negative impact on the co-movements. The finding is robust to the asymmetric effects of non-policy-uncertainty shocks, to a break in the correlation structure, and to the four different Chinese stock markets investigated. Our results provide the first evidence regarding how stock market correlations are driven by policy-related uncertainty shocks in the international context.

Journal ArticleDOI
TL;DR: This article examined the effect of ownership structure on firm performance, for firms listed on Vietnamese stock exchanges, using 2744 firm-year observations over the period from 2007 to 2012, and found a non-linear relationship between ownership structure and firm performance.
Abstract: We examine the effect of ownership structure on firm performance, for firms listed on Vietnamese stock exchanges, using 2744 firm-year observations over the period from 2007 to 2012. We find a non-linear relationship between ownership structure and firm performance. State ownership has a convex relationship with firm performance. This paper finds that firm performance increases beyond 28.67 percent level of state ownership. Foreign ownership has a concave relationship with firm performance. We find that firm performance increases with an increase of foreign ownership up to a level of 43 percent and then decreases. Policy makers should encourage foreign ownership and widely dispersed state ownership in firms, which can help improve firm performance.

01 Jan 2016
TL;DR: The authors used the difference between prices and net asset values of closed-end mutual funds at the end of the 1920s to estimate the degree to which the stock market was overvalued on the eve of the 1929 crash.
Abstract: Economists directly observe warranted "fundamental" values in only a few cases. One is that of closed-end mutual funds: their fundamental value is simply the current market value of the securities that make up their portfolios. We use the difference between prices and net asset values of closed-end mutual funds at the end of the 1920s to estimate the degree to which the stock market was overvalued on the eve of the 1929 crash. We conclude that the stocks making up the S & P composite were priced at least 30 percent above fundamentals in late summer, 1929.

Journal ArticleDOI
TL;DR: The proposed short-term fuzzy system can be characterised as conservative, since it produces smaller losses during bear market periods and smaller gains during bull market periods compared with the buy and hold strategy.
Abstract: The proposed short-term fuzzy system uses a set of appropriate technical indicators.The returns of the proposed system are higher than those of the B&H strategy.The proposed system avoids big losses during bear markets.During bull markets the system produces lower returns than the B&H strategy.Transaction costs significantly affect the performance of the proposed system. Financial markets are complex systems influenced by many interrelated economic, political and psychological factors and characterised by inherent nonlinearities. Recently, there have been many efforts towards stock market prediction, applying various fuzzy logic techniques and using technical analysis methods.This paper presents a short term trading fuzzy system using a novel trading strategy and an "amalgam" between altered commonly used technical indicators and rarely used ones, in order to assist investors in their portfolio management. The sample consists of daily data from the general index of the Athens Stock Exchange over a period of more than 15 years (15/11/1996 to 5/6/2012), which was also divided into distinctive groups of bull and bear market periods.The results suggest that, with or without taking into consideration transaction costs, the return of the proposed fuzzy model is superior to the returns of the buy and hold strategy. ?he proposed system can be characterised as conservative, since it produces smaller losses during bear market periods and smaller gains during bull market periods compared with the buy and hold strategy.

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed the financial and economic performance of companies listed in the Corporate Sustainability Index in comparison with the performance of the companies listed on the Sao Paulo Stock Exchange Index.

Journal ArticleDOI
01 Dec 2016
TL;DR: Numerical results indicate that the developed hybrid model is not only simple but also able to satisfactorily approximate the actual CSI300stock price index, and it can be an effective tool in stock market mining and analysis.
Abstract: Display Omitted Original v-support vector regression is improved from two aspects.Principal component analysis is used to select suitable inputs for v-SVR.Brain storm optimization is first used to optimize three parameters of v-SVR.Two case studies of representative Chinese stock indices are presented.The developed hybrid model outperforms competing models for stock price forecast. Big data mining, analysis and forecasting always play a vital role in modern economic and industrial fields, and selecting an optimization model to improve time series forecasting accuracy is challenging. A support vector regression (SVR) model is widely used forecasting and data processing, but the individual SVR cannot always satisfy the requirements of time series forecasting. In this paper, a hybrid v-SVR model is developed and combined with principal component analysis (PCA) and brain storm optimization (BSO) for stock price index forecasting. Correlation analysis and PCA are conducted initially to select the input variables of the v-SVR from 20 technical indicators, while the advanced BSO algorithm is used to search for optimal parameters of v-SVR. Case studies of the China Securities Index 300 (CSI300) and the Shenzhen Stock Exchange Component Index (SZSE Component Index) are examined as illustrative examples to evaluate the effectiveness and efficiency of the developed hybrid forecast strategy. Numerical results indicate that the developed hybrid model is not only simple but also able to satisfactorily approximate the actual CSI300stock price index, and it can be an effective tool in stock market mining and analysis.

Journal ArticleDOI
TL;DR: In this paper, the effects of board social capital on firm performance using a sample of the 103 companies listed on The Madrid Stock Exchange (2008) were examined. But the authors did not consider the effect of board co-working experience on the board.
Abstract: Board social capital encompasses two types of relationships: external and internal ties. This study examines the effects of board social capital on firm performance using a sample of the 103 companies listed on The Madrid Stock Exchange (2008). In order to measure board internal social capital, we consider the directors’ co-working experience on the board. On the other hand, to measure external board social capital, we rely on the directors’ ties to other organizations through interlocking directorates. We introduce internal social capital as a necessary variable for a more complete understanding of the external social capital/firm performance relationship. Our results have important implications for corporate governance practices. When firms propose reconsidering the composition of boards, they should not be guided solely by the intention of maximizing external connections. On the contrary, they should really take into account the fundamental role of internal social capital, which (1) intensifies the pos...

Journal ArticleDOI
01 Dec 2016
TL;DR: The results show that the status box method not only have the better classification accuracy but also effectively solve the unbalance problem of the stock turning points classification.
Abstract: Display Omitted A new status box method is proposed to perform the stock trend prediction.A new feature construction approach for status box is presented.A new hybrid classifier that integrates AdaBoost algorithm, genetic algorithm and probabilistic support vector machine.The status box method can solve the unbalance problem of the stock turning points classification. Stock trend prediction is regarded as one of the most challenging tasks of financial time series prediction. Conventional statistical modeling techniques are not adequate for stock trend forecasting because of the non-stationarity and non-linearity of the stock market. With this regard, many machine learning approaches are used to improve the prediction results. These approaches mainly focus on two aspects: regression problem of the stock price and prediction problem of the turning points of stock price. In this paper, we concentrate on the evaluation of the current trend of stock price and the prediction of the change orientation of the stock price in future. Then, a new approach named status box method is proposed. Different from the prediction issue of the turning points, the status box method packages some stock points into three categories of boxes which indicate different stock status. And then, some machine learning techniques are used to classify these boxes so as to measure whether the states of each box coincides with the stock price trend and forecast the stock price trend based on the states of the box. These results would support us to make buying or selling strategies. Comparing with the turning points prediction that only considered the features of one day, each status box contains a certain amount of points which represent the stock price trend in a certain period of time. So, the status box reflects more information of stock market. To solve the classification problem of the status box, a special features construction approach is presented. Moreover, a new ensemble method integrated with the AdaBoost algorithm, probabilistic support vector machine (PSVM), and genetic algorithm (GA) is constructed to perform the status boxes classification. To verify the applicability and superiority of the proposed methods, 20 shares chosen from Shenzhen Stock Exchange (SZSE) and 16 shares from National Association of Securities Dealers Automated Quotations (NASDAQ) are applied to perform stock trend prediction. The results show that the status box method not only have the better classification accuracy but also effectively solve the unbalance problem of the stock turning points classification. In addition, the new ensemble classifier achieves preferable profitability in simulation of stock investment and remarkably improves the classification performance compared with the approach that only uses the PSVM or back-propagation artificial neural network (BPN).

Journal ArticleDOI
TL;DR: In this paper, the authors examined volatility spillover effects between stock market and foreign exchange market in selected Asian countries; Pakistan, India, Sri Lanka, China, Hong Kong and Japan.
Abstract: The purpose of this study is to examine volatility spillover effects between stock market and foreign exchange market in selected Asian countries; Pakistan, India, Sri Lanka, China, Hong Kong and Japan. This study considered daily data from 4th January, 1999 to 1st January, 2014. This study opted EGARCH (Exponential Generalized Auto Regressive Conditional Heteroskedasticity) model for the purpose of analyzing asymmetric volatility spillover effects between stock and foreign exchange market. The EGARCH analyses reveal bidirectional asymmetric volatility spillover between stock market and foreign exchange market of Pakistan, China, Hong Kong and Sri Lanka. The results reveal unidirectional transmission of volatility from stock market to foreign exchange market of India. The analysis reveals no evidence of volatility transmission between the two markets in reference to Japan. The result of this study provide valuable insights to economic policy makers for financial stability perspective and to investors regarding decision making in international portfolio and currency risk strategies.

Journal ArticleDOI
TL;DR: In this article, the authors investigated the presence and changes in, long memory features in the returns and volatility dynamics of S&P 500 and London Stock Exchange using ARMA model.
Abstract: We investigated the presence and changes in, long memory features in the returns and volatility dynamics of S&P 500 and London Stock Exchange using ARMA model. Recently, multifractal analysis has been evolved as an important way to explain the complexity of financial markets which can hardly be described by linear methods of efficient market theory. In financial markets, the weak form of the efficient market hypothesis implies that price returns are serially uncorrelated sequences. In other words, prices should follow a random walk behavior. The random walk hypothesis is evaluated against alternatives accommodating either unifractality or multifractality. Several studies find that the return volatility of stocks tends to exhibit long-range dependence, heavy tails, and clustering. Because stochastic processes with self-similarity possess long-range dependence and heavy tails, it has been suggested that self-similar processes be employed to capture these characteristics in return volatility modeling. The present study applies monthly and yearly forecasting of Time Series Stock Returns in S&P 500 and London Stock Exchange using ARMA model. The statistical analysis of S&P 500 shows that the ARMA model for S&P 500 outperforms the London stock exchange and it is capable for predicting medium or long horizons using real known values. The statistical analysis in London Stock Exchange shows that the ARMA model for monthly stock returns outperforms the yearly. ​A comparison between S&P 500 and London Stock Exchange shows that both markets are efficient and have Financial Stability during periods of boom and bust.

Journal ArticleDOI
TL;DR: In this article, the authors focus on the corporate governance and sustainability disclosure practices in one of the emerging economies, Indonesia, and assesses the relationships between corporate governance variables and the extent of environmental disclosures made by the mining companies listed in the Indonesia Stock Exchange (IDX) in their annual reports.
Abstract: Sustainability and corporate governance issues are now considered to be important and integral aspects of company performance. Both have established themselves as well-studied topics in the organisational and accountability areas. While there has been a growing interest to study the relationship between these two areas, research publication in this topic is still mainly focused on the Western societies. This study focuses on the corporate governance and sustainability disclosure practices in one of the emerging economies, Indonesia, and assesses the relationships between corporate governance variables and the extent of environmental disclosures made by the mining companies listed in the Indonesia Stock Exchange (IDX) in their annual reports. The main findings of this study show that the extent of environmental disclosure made by these companies was moderate, and that there is a significant positive relationship between the size of board of directors and the extent of environmental disclosure.