Performance Of Stock Indices Research Articles

THE IMPACT OF THE PRESIDENTIAL ELECTION ON IDX COMPOSITE PREDICTIONS USING LONG SHORT TERM MEMORY

An analysis of the performance of Indonesia's capital market, or Indonesia Stock Exchange (IDX), shows significant growth in recent years, with market capitalization increasing dramatically from IDR 679.95 trillion in 2004 to IDR 11,674.06 trillion by 2023. The IDX plays an important role in the Indonesian economy by facilitating capital formation and providing opportunities for investors to diversify their portfolios. However, the capital market is vulnerable to political events, such as presidential elections, which can affect national stability and economic performance. An analysis of the stock index performance before the presidential election showed a significant bullish trend. Still, given the considerable impact of political events, such as presidential elections, on financial markets, this study aims to analyze and forecast the performance of the IDX Composite by examining historical data from past election years, we provide insights and predictions in highlighting how the LSTM model accommodates these political factors in its forecasts. IDX Composite closing price forecasting was conducted using the bidirectional LSTM model to anticipate the impact. The analysis results show that this model can predict the weekly closing price of the IDX Composite with an error of 1.04%, with estimated stock price fluctuations in the next 8 weeks in the range of 6619.755 to 6812.722

Comparative Analysis of Indonesia and Malaysia Sharia Stock Index Performance Using Sharpe, Treynor, and Jensen Methods

Comparative Analysis of Indonesia and Malaysia Sharia Stock Index Performance Using Sharpe, Treynor, and Jensen Methods

Oil and Stock Markets in Ongoing Flux: Impact of Current Events on Oil Price and Stock Market Performance

Abstract The price of oil and, indirectly, the performance of stock indices have been significantly affected by the events of recent years, with a negative impact on the global economy, including the evolution of the energy market in the context of the transition to renewable energy sources and changes in global energy policy. This paper proposes a comprehensive analysis of the evolution of stock indices, oil market volatility and investors' response to the "black swan" events that have recently caused changes in the global economy. Using advanced econometric and statistical models, the paper presents the complex relationship between the analyzed stock indices, the trends and changes that occurred within them and the relevant influencing factors, such as the price of Brent Oil and the Baltic Dry Index. The results obtained, based on univariate GARCH models (GJR-GARCH) and multivariate DCC-GARCH models are in accordance with specialized studies in the field and show that oil price fluctuations were higher at the beginning of the Covid-19 pandemic compared to the period after the military conflicts (stage in which no significant influence of the oil price on the stock market is observed). Also, using the Chow test, in the analyzed period there are 3 important breaking points that coincide with the dates when the COVID-19 pandemic began, the military conflict between Russia and Ukraine as well as the military conflict between Israel and Gaza, events with a strong impact on the economy. The obtained results also show another important aspect, namely that, during the selected period January 2019-November 2023, the price of oil and the stock market were much more affected by the COVID-19 pandemic than by military conflicts, which cannot be also stated in the case of the price of the Baltic-Dry Index.

Environment and Digitalization: The New Paradigms in the European Stock Markets

In a European context in which the objectives of climate neutrality and digitalization appear fundamental, the work analyzes the relationships between the price of the main stock market indices and the most representative variables such as carbon emissions, digitalization, use of renewable energy, research and development expenses, environmental taxes, and all economic and management activities aimed at reducing or eliminating any form of pollution. The analysis was developed through three different regressions involving the long period 1995–2020 and the short period 2017–2020. The results show how increasing carbon emissions and environmental taxes positively impact stock indices. The former is linked to an increase in production and, therefore, economic growth, and the latter encourages sustainability. Taxes on transport and energy in the long term generate higher costs, which damage profitability and negatively impact the performance of stock indices. Finally, in the short term, implementing environmental protection measures or the sustainable management of resources may lead to higher operating costs for the companies involved. These cost increases can negatively impact profit margins and reduce the value of companies. These results, therefore, show us how environmental sustainability has a significant impact on European stock markets; consequently, the relevant regulations and policies should also consider the economic and managerial impacts that companies implement to achieve their objectives of the Green Deal.

Volatility and Liquidity Comparison of Indonesian and Singapore Stock Market in COVID-19 Mobility Restrictions Era

The COVID-19 case found at the end of December 2019 became a pandemic in March 2020. The research aimed to see and understand the differences in the performance of the Indonesian and Singapore stock indices represented by the Indeks Harga Saham Indonesia (IHSG) and Straits Times Index (STI) before and after the implementation of community mobility restrictions (Pembatasan Sosial Berskala Besar (PSBB) in Indonesia and Circuit Breaker in Singapore). The stock index data were stock index prices at closing and stock trading volume. The stock index performance was measured by its volatility and liquidity. Meanwhile, data volatility with heteroscedasticity symptoms was measured using the GARCH (1,1) model. Meanwhile, the standard deviation was used to measure homoscedastic data. The results show differences in return volatility and stock index liquidity before and after restrictions on community mobility. The return volatility of the IHSG and STI is higher before the community mobility restrictions compared to the period after. IHSG experiences liquidity after PSBB I and before PSBB II. The conclusion that can be drawn from these results is that liquidity in Indonesia does not improve when PSBB I is implemented, but liquidity improves in PSBB II. Meanwhile, STI’s liquidity is higher in the period after the implementation of Circuit Breaker. These results indicate that implementing the Circuit Breaker helps to improve the stock index’s performance in Singapore because volatility decreases when the policy is implemented. The policy also reduced the liquidity of the Singapore stock index.

How did gold prices respond to the COVID-19 pandemic?

ABSTRACT This paper investigates the asymmetric impact of COVID-19 on gold prices by making use of high frequency data and a recently developed nonlinear estimation approach. The analysis considers three main dimensions of COVID-19: daily new cases, recoveries and deaths. The findings reveal that decreases in COVID-19 new cases and increases in recoveries cause an upswing in gold prices. These evidences imply that the reduction in new COVID-19 cases or more recoveries from COVID-19 improves both investors’ and consumers’ psychological confidence. In other words, the investors and consumers become more optimistic about their future and tend to demand more gold. On the other hand, the increases (decreases) in policy uncertainty, oil prices, and world stock index performance elevate (reduce) gold prices. The study also establishes a positive nexus between equity market uncertainty and gold prices.

Comparison Performance of Environmental, Social, and Governance Stock Index with Sharia Stock Index Before and During the Covid-19 Pandemic in Southeast Asia

Covid-19 is a pandemic event with a global impact from a health and economic point of view. The number of confirmed cases of Covid-19 that continues to grow has caused several countries to implement lockdown policies. However, this has implications for an increasingly depressed stock market. Thus, it can affect the performance of stock indexes in various countries. This research aims to examine the effects of Covid-19 on the Islamic stock index and the environmental, social, and governance stock index in Southeast Asia, and then compare the two indexes when responding to the Covid-19 pandemic. The models used in this research are event study and Vector Error Correction Model (VECM). This study utilizes time-series data with a five-month daily period starting from December 2019 to April 2020. The results of the event study model show that the number of positive cases of Covid-19 has a significant effect on the performance of the stock index studied, except for the ESG stock indexes in Singapore. Meanwhile, the results from the VECM show that the number of positive cases of Covid-19 has a significant effect on the stock index’s performance in the long and short term, except for the sharia stock index which does not have a significant impact on the short term in Singapore, and does not have a significant impact on the long term in Malaysia namely HIJRAH index.

The Effect of Corporate Governance on Company Value in The Indonesia Stock Exchange and Sharia Stock in Indonesia

This study analyzes the effect of corporate governance on a firm value on the Indonesian stock exchange and Islamic stocks in Indonesia. We conducted this study because it is still very rare to research by adding Islamic stock variables as a moderating variable. Many studies on the influence of corporate governance on firm value have been carried out, but there are inconsistencies in the results. Corporate governance, in this case, the ownership structure is assessed by the ownership structure. This study uses 150 manufacturing companies listed on the Jakarta Stock Exchange during 2002 - 2005 as a sample with 600 observations. The hypothesis is tested using regression analysis. Firm value is measured using Tobin's Q. The results show that institutional ownership has no significant effect on firm value. significant effect on firm value due to the development of the Indonesia Stock Exchange in terms of the development of the LQ45 stock index performance increasing, not proven. However, managerial ownership has a significant and positive effect on firm value. What is known from the analysis of this research is (1) the development of the Indonesia Stock Exchange as seen from the growth in the performance of the LQ45 stock index, (2) the growth of sharia shares, (3) the comparison of the LQ45 stock index performance scheme with the JII stock index performance is known to have a slight difference in the growth of the Stock Exchange. Indonesia is seen from the growth in the performance of the LQ45 stock index. And in terms of the development of the JII stock index performance. Keywords: corporate governance, institutional ownership, managerial ownership, LQ45, sharia shares

Permutation Tests for Stock Index Performance: Evidence from ESG Indices

Permutation Tests for Stock Index Performance: Evidence from ESG Indices

Machine learning applied to stock index performance enhancement

The project constructs a stock selection model by machine learning methods to enhance the performance of the benchmark index for individual investors. Stock returns prediction is a highly researched topic. However, it is a difficult problem because the stock prices are complex, non-linear, and chaotic. Moreover, overfitting is always an important issue in machine learning field. In this article, it shows that how to solve these problems by dealing with time series data, feature engineering, and model construction. We apply the stock selection model on S&P 500 index and FTSE 100 index. The result shows that the portfolios with stock selection model outperform the benchmarks, and 2% of the number of constitution stocks is the best choice for the stock selection model. Besides, feature importance analysis shows that the stock selection model can measure import features appropriately, which means it has the ability to adapt to different economic environments. In addition, the portfolios with fewer stocks usually outperform the portfolios with more stocks shows the good prediction of the stock selection model. The results imply that machine learning techniques have a good application in stock markets.

Stock Index Performance of SRIKEHATI 2014: Case Study of ISAT and MEDC

This study analyzes the returns volatility of ISAT and MEDC in context of green investment. These two stocks are member of SRIKEHATI index. SRIKEHATI is an index containing stocks that concern on environment, social and governance. The period of analysis cover 2009-2014 the focus of the study is on three measures of price earning ratio (PER) and fundamental performance indicator, environment activities disclosure in sustainability report was done. Results show that return volatility of ISAT affects return index of SRIKEHATI significantly, but not for MEDC. ISAT has experienced decreasing profit that continued to a loss, inconsistent reporting environment activities in the sustainability report. MEDC has experienced decreasing of profit but did not lead into a loss. MEDC is also consistent in reporting environment-related activities through publishing sustainability reports.
 Keywords: green finance; green investment; SRI-KEHATI index; ISAT; MEDC

Utilization of Artificial Intelligence for Sensitivity Analysis in the Stock Market

The main contribution of this paper is to perform sensitivity analysis using artificial intelligence methods on the US stock market using alternative psychological indicators. The Takagi-Sugeno fuzzy model applies investor sentiment represented by VIX index and monitors the impact of economic optimism, political stability and control of the corruption index on the S&P 500 stock index. Alternative psychological indicators have been chosen that have not been explored in the context of stock index performance sensitivity. Investors primarily use fundamental and technical analysis as a source to determine when and what to buy into an investment portfolio. However, psychological factors that may indicate the strength of reaction to the market are often neglected. Fuzzy rules are determined and tested using a neuro-fuzzy inference system and then the rules are reduced by fuzzy clustering to improve performance of ANFIS. The membership function is defined as a Gaussian function because it has the least RMSE value. The sensitivity analysis confirmed that there is a significant impact of the political stability index and the economic optimism index on the S&P 500 performance. Conversely, the sensitivity analysis, unlike the previous study, did not confirm the strong impact of VIX on equity index performance. Results indicate that incorporating psychological indicators in macroeconomic models leads to better supervision and control of the financial markets.

Cointegration of Stock Market and Exchange Rate in Indonesia

This study aims to determine the long-term relationship between stock market and exchange rate in Indonesia. The research method used is Johansen cointegration test. The results of this study found no cointegration between the variables tested. Thus the exchange rate, JII, and IHSG have no relationship in the long term. The fluctuation of the rupiah exchange rate in recent years did not generally affect the performance of stock indices especially after the global financial crisis of 2008. This shows the capital market in Indonesia has a good performance so that it is not so sensitive to the sentiment of the decline in the rupiah against the US dollar. This finding is in line with the findings of Syahrer (2010) which states the exchange rate has no effect on the stock market.

Rating of LQ-45 stock index performance credibility in Indonesia Stock Exchange

This study aims to analyze stock performance credibility using the Capital Asset Pricing Model (CAPM) method, the Arbitrage Pricing Theory (APT) method, the Fama-French Three-Factor Model (FFTFM), and the 2013-2017 LQ-45 Stock Performance rating. The technique used for sampling is purposive sampling. The samples in this study are 23 companies. The results show that the CAPM model is more accurate in stock credibility assessment than the APT model and the FFTFM.

The Impact of Exchange Rate Volatility on Stock Index: Evidence from Pakistan Stock Exchange (PSX)

The exchange rate Volatility is considered to be the most important and persuasive variable that affects the performance of stock index. The stock market plays an imperative role in the growth and development of a country. This study mainly aimed at to empirically examines the Impact of Exchange Rate Volatility on Pakistan Stock Index (PSX). The correlational research design is used in order to demonstrate cause and effect relationship between the variable under studied. The nature of this study was explanatory. Macroeconomies variables have the problem of stationary, autocorrelation and heteroskedasticity, diagnostic test is paramount important while applying regression in order to reach meaningful results so it was necessary to fulfill the assumptions of regression. Augmented Dickey-Fuller test statistic is employed. Two financial variables have been studied where Exchange rate Volatility is used as an independent variable whereas stock index is worked out as dependent variable. Twelve years monthly data from secondary sources, starts from 31st of January, 2003- 31st December, 2015 have analyzed. The study results found that there is positive and statistically significant relationship between Exchange Rate Volatility on Stock Index of Pakistan. Based upon key findings, this study particularly postulates that countries like Pakistan which has an emerging economy the macroeconomics variables i.e. exchange rate Volatility and stock index of Pakistan are associated, thus the public who desire to invest must utilize the information of important macro-economic variable in particular exchange rates volatility in order to predict the behaviour of stock market index.

Risk and return characteristics of environmentally and socially responsible firms in Spain during a financial downturn: 2008–2011

The onset of the global financial crisis in 2008 undermined trust in financial markets, with immediate damages to businesses and enduring negative effects for numerous national economies. The situation also has endangered progress in terms of investments in environmental and social management (ESM) issues, because managers may be more likely to embrace the misguided notion that such investments represent a non-returnable costs that will hinder firms’ financial performance. Yet ESM is needed now more than ever, because “doing good and doing well” messages are highly appreciated by stakeholders and can substantially improve a firm’s competitiveness. This article analyzes the performance of the Spanish FTSE4Good IBEX index, compared with that of the Spanish IBEX 35 index, during the financial crisis and reveals slightly better performance for the former. Thus, considering the difficult financial context, indicators of good environmental and social performance, among other factors, might have positive effects on stock index performance. The findings offer some key implications for managerial practice.

Analysis of Stock Indices and Their Impact on Market Index

This study attempts analyse the different indices of ‘Bombay Stock Exchange’ (BSE) of India, in terms of risk return characteristics and their relatedness and predictibility to address the relavite neglect of past studies. Further it investigates the volatility impact of different sub indices of BSE on market index (BSE 30). By applying the mean variance approach and different performance ratios the risk return characteristics and performance of different indices is analyzed. ARIMA modelling is performed to forecast the market return at varying time lag. Further we analyse the volatility impact of different indices on the market index (BSE 30) with GARCH Modelling. The results indicate that medium cap indices perform better in terms of risk and return. We find a significant volatility impact of other indices on market index. The return of different indices are significantly related and it can be forecasted with help of ARIMA Model with one period time lag. Our study provides interesting insights to researchers and investors alike in the context of performance of stock indices in India.

Investment Strategies of Constructing FTSE 100 IndexFunds with Exchange-Traded Derivative Instruments

The author designed and analyzed investment strategies of constructing the FTSE-100 index funds with derivative instruments (futures and options respectively) as the return enhancement techniques. The portfolios of stock index derivatives combined with Treasury bills holdings, amounting to the respective derivative contracts’ underlying value, showed remarkable ability to limit the market downside risk. Excess returns, which could be achieved by derivative funds above the stock index performance, were found. The author distinguished factors contributing to the observed outperformance. The results of the research are very encouraging and strongly advocate for the use of futures and options as investment vehicles instead of constructing index tracking portfolios with stocks. <b>TOPICS:</b>Options, futures and forward contracts, VAR and use of alternative risk measures of trading risk

Two Russian Stock Exchanges: Analysis of Relationships

Development of Russian financial markets is gradually becoming a subject for standard economic analysis. Accumulated statistics make it possible to pose some questions about features of development and operation of financial markets in Russia. This paper analyses relationships between the two leading Moscow stock exchanges, as well as analysing performance of their indices and trading volumes, and factors determining index changes. The authors are far from thinking that their work is comprehensive or gives final answers to the questions posed. On the contrary, the authors hope that the paper will be a starting point for development of a fruitful scientific discussion of the issues concerned.Russian stock exchanges, their trading volumes and share prices, offer material which makes it possible to search for clear and steady patterns of performance. Although the period of organised stock trading in Russia is quite short, the combined use of monthly, daily and hourly observations allows a variety of questions to be posed. For example, what is the relationship between the performance of the two exchanges as regards indices and trading volumes, and how are those related to international indices and important factors traditionally affecting levels of market activity, such as economic activity in Russia, commodity prices, etc.? One interesting aspect of stock index performance is the slow rate of index growth despite the relatively long‐lasting economic recovery (Figure1).