Permutation entropy and statistical analysis of the historical evolution of the Mexican stock market index

The objective of this work is to analyze the Indice de Precios y Cotizaciones (IPC), which is the Mexican stock market index, by using several statistical tools in order to study the tendencies that can shed light on the evolution of the IPC towards a more efficient market. The methodology used is to apply the statistical tools to the Mexican index and compare the results with a mature and well-known market index such as the Dow Jones Industrial Average (DJIA). We employ an autocorrelation analysis, and the volatility of the indexes, applied to the daily returns of the closing price on a moving time window during the studied period (1980–2018). Additionally, we perform an order three permutation entropy analysis, which can quantify the disorder present in the time series. Our results show that there is evidence that the IPC has become more mature since its creation and that it can be considered an efficient market since around year 2000. The behavior of the several techniques used shows a similar behavior to the DJIA which is not observed before that year. There are some limitations mainly because there is no high frequency data that would permit a more detailed analysis, specifically in the periods before and after a crisis is located. Our conclusion is that since around the year 2000, the Mexican stock index displays the typical behavior of other mature markets and can be considered as one.

Dynamic Linkages among Saudi Market Sectors Indices

This study aims to test the causal relationship between Saudi stock market index (TASI) and sectoral indices throughout the period from 2016–2020. The study data were extracted through the main index of the Saudi market and the indices of the available data of 19 sectors out of 21 sectors. The unit root test was used along with the Granger causality test, in addition to multiple regression tests in order to analyze the study hypotheses. The study shows that all index series were stationary at the zero level I (0), and the results also show that there were bidirectional and unidirectional causal relationships between TASI and sectoral indices, and that TASI effectively mirrors all the changes that occur in the Saudi stock market.

Impact of Macroeconomic Variables, American Stock Market Index and Covid-19 Pandemic on Indonesia Capital Market Development (Time Series Study 1990-2020)

The purpose of this study is 1.) To analyze the influence of foreign investment on the development of the Indonesian capital market. 2).To analyze the influence of the Exchange Rate on the Development of the Indonesian Capital Market. 3).To analyze the influence of the Interest Rate on the Development of the Indonesian Capital Market. 4).To analyze the influence of the Dow Jones Stock Market Index on the Development of the Indonesian Capital Market. 5).To analyze the influence of the Covid-19 Pandemic (dummy variable) on the Development of the Indonesian Capital Market.6). In this study, secondary data and library research were used as a technique for collecting data, using semi-annual data for the period 1990-2020. The research was processed using the EViews 11 program with the multiple linear regression method. The results of the research are known if 1.) Foreign Direct Investment has a significant and positive effect on Capital Market Development. 2.) Exchange Rates have a significant and positive influence on the Development of the Indonesian Capital Market. 3.) Interest Rates have a significant and negative effect on the Development of the Indonesian Capital Market. 4.) The Dow Jones Stock Market Index has a significant and positive effect on the Development of the Indonesian Capital Market. 5.) The Covid-19 pandemic had a significant and negative effect on the Development of the Indonesian Capital Market in the period 1990 to 2020. The results of this study are expected to contribute to policy holders regarding the role of macroeconomic variables on the development of the capital market, so that in the future it can be one of the references in conducting the policy mix so as to improve the development of the Indonesian capital market.

Local Stock Market Integration with International Gold and Oil Price

We look for the integration of Bangladesh Stock Market with international gold and oil price using most recent monthly data set from January 2003 to December 2020 (2003m1-2020m12). We employ the bounds-testing approach to cointegration between stock market index (DSEX) and international gold and oil price and eventually find an integration and dynamic significant impact of international gold and oil price on DSEX in the long and short-run. We discuss the important policy implications of the dynamic impact of international gold and oil price on stock market index.

Is Bitcoin Price Driven by Macro-financial Factors and Liquidity? A Global Consumer Survey Empirical Study

This research aims to utilize macro-financial and liquidity elements as the factors that may affect the price of Bitcoin as the largest cryptocurrency in terms of market capitalization. The macro-financial factors analyzed in this study were foreign exchange, stock market index, interest rates, and gold, while liquidity ratio is the internal factor. This study applied a fixed-effect model (FEM) and Generalized Method of Moments (GMM) on gathered weekly data from 1 January 2017 to 29 December 2019 from 18 countries with the total of 2,826 observations. The analysis revealed that US Dollar amplifies Bitcoin trading; an increase in interest rate will decrease investors’ intention to invest in Bitcoin as a speculative asset, and gold could replace Bitcoin as a substitute asset. Moreover, Bitcoin was found to be highly liquid, which attracts many investors, while the stock market index proved to be insignificant.

ESG impact on financial corporate performance and portfolio returns: evidence of Australia and Japan

Environmental, Social, and Governance investing has undergone a radical shift; companies and investors have focused on the impact of the disclosure of the practices and policies related to the environment, social responsibility, and governance in their operational strategies and investment. The purpose of this paper is to demonstrate the impact that the ESG policies have on public companies' stock returns in Australia and Japan. Accounting and market-based measures are used to determine the impact ESG practices have on stock market index returns. The annual data used is of companies from Australia's S&P/ASX Index and Japan's Nikkei 225 Index, covering the period from 2005 to 2019. Fixed effect model regression was used to test the significant relationship between companies' stock returns and ESG score, accounting, and market-based measures. Portfolios were created to analyze the risk/return relationship between companies with and without ESG across countries. The findings indicate mixed results. Australia´s non-ESG portfolios outperform the S&P500 and ESG portfolios. Japan´s portfolio has positive returns but underperforms the benchmark. Low market capitalization portfolios with and without ESG outperform the higher capitalization portfolios.

The Stock Market Situation and Economic Growth – An Attempt to Assess the Dependence

The aim of the article: The main aim of the article is to analyze the relationship between the stock market situation and the real economy, measured by the strength of the correlation between the rate of return on the stock market and the rate of GDP growth in European capital markets. The next objective is to answer the question whether the stock market index changes are ahead of, and if so, by how much, GDP changes. The author’s hypothesis stipulates that the stock exchange situation precedes the change in economic activity and serves as its forecast. Methodology: The empirical research work was carried out on the basis of quarterly data value of the stock index and the GDP between 2010 and the first quarter of 2021 for 20 European countries. For indices and GDP, the quarterly dynamics of the rate of return and GDP were calculated. Data on the value of the stock exchange index was taken from the website www.stooq.pl, while data on GDP was taken from Eurostat. Subsequently, the analysis concerned the correlation relationships between the variables on the basis of the Pearson correlation coefficient. The correlation between the variables was calculated without delay, as well as with a delay of one, two or three quarters of the returns on stock indices. Results of the research: Changes in the value of the stock exchange index is in most cases positively correlated with the change in GDP and the correlation is pronounced, but it is low and moderate. The only market for which a significant correlation was observed, was the Polish market. At the same time, it can be stated that the rates of return on the stock exchange index precede a change in GDP by one or three quarters. No changes were observed for the analyzed countries for two quarters.

Sticky Stock Market Analysts

Technological progress in recent years has made new methods available for making forecasts in a variety of areas. We examine the success of ex-ante stock market forecasts of three major stock market indices, i.e., the German Stock Market Index (DAX), the Dow Jones Industrial Index (DJI), and the Euro Stoxx 50 (SX5E). We test whether the forecasts prove true when they reach their effective dates and are therefore suitable for active investment strategies. We revive the thoughts of the American sociologist William Fielding Ogburn, who argues that forecasters consistently underestimate the variability of the future. In addition, we draw on some contemporary measures of forecast quality (prediction-realization diagram, test of unbiasedness, and Diebold–Mariano test). We reveal that (a) unusual events are underrepresented in the forecasts, (b) the dispersion of the forecasts lags behind that of the actual events, (c) the slope of the regression lines in the prediction-realization diagram is <1, (d) the forecasts are highly biased, and (e) the quality of the forecasts is not significantly better than that of naïve forecasts. The overall behavior of the forecasters can be described as “sticky” because their forecasts adhere too strongly to long-term trends in the indices and are thus characterized by conservatism.

An Application of Hybrid Models for Weekly Stock Market Index Prediction: Empirical Evidence from SAARC Countries

The foremost aim of this research was to forecast the performance of three stock market indices using the multilayer perceptron (MLP), recurrent neural network (RNN), and autoregressive integrated moving average (ARIMA) on historical data. Moreover, we compared the extrapolative abilities of a hybrid of ARIMA with MLP and RNN models, which are called ARIMA-MLP and ARIMA-RNN. Because of the complicated and noisy nature of financial data, we combine novel machine-learning techniques such as MLP and RNN with ARIMA model to predict the three stock market data. The data used in this study are taken from the Pakistan Stock Exchange, National Stock Exchange India, and Sri Lanka Stock Exchange. In the case of Pakistan, the findings show that the ARIMA-MLP and ARIMA-RNN beat the individual ARIMA, MLP, and RNN models in terms of accuracy. Similarly, in the case of Sri Lanka and India, the hybrid models show more robustness in terms of forecasting than individual ARIMA, MLP, and RNN models based on root-mean-square error and mean absolute error. Apart from this, ARIMA-MLP outperformed the ARIMA-RNN in the case of Pakistan and India, while in the context of Sri Lanka, ARIMA-RNN beat the ARIMA-MLP in forecasting. Our findings reveal that the hybrid models can be regarded as a suitable option for financial time-series forecasting.

Dynamics and Determinants of Market Integration of Green, Clean, Dirty Energy Investments and Conventional Stock Indices

We examine market integration across and clean and green investments, crude oil, and conventional stock indices covering technology stocks, and United States and European stocks. Using daily data covering the period December 1, 2008—October 8, 2020, we first apply the dynamic equicorrelation (DECO) model and make inferences regarding the time-varying level of market integration. Then, we use several regression models and uncover the driving factors of market integration under lower and upper quantiles of the distribution of the equicorrelation. The results show that return equicorrelation varies with time and is shaped by the COVID19 outbreak. Various uncertainty measures are the main drivers of market integration, especially at high levels of market integration. During the COVID-19 outbreak period, the United States Dollar index, the term spread, and the Chinese stock market index have significantly increased market integration.