Showing papers on "Market capitalization published in 2023"

Stakeholder-Centered Corporate Governance and Corporate Sustainable Development: Evidence from CSR Practices in the Top Companies by Market Capitalization at Shanghai Stock Exchange of China

Abstract: This study aims to investigate the nature and intensity of changes in corporate sustainable development as a result of certain relationships between stakeholder-centered corporate governance (CG) and corporate social responsibility CSR practices in the leading firms with respect to their market capitalization (MC) in the Shanghai stock exchange (SSE) of China. This study selected the top 100 companies from the manufacturing sector at the Shanghai Stock Exchange by (MC) for a period of 10 years (2012–2021). For this quantitative study, financial and CSR performance data were collected from the China Securities Market and Accounting Database (CSMAR), a reliable database for examining research on Chinese listed companies. For the data analysis, we applied different statistical tools that include descriptive statistics; a correlation matrix, fixed effect regression analysis, and moderation analysis of the effect of government subsidies on the relationship between explanatory variables and the dependent variable (firm performance) were applied. The result of the adjusted R-square values suggests that there has been a considerable change in the value of explained variable Firm Performance (FP), represented by ROA, TbQ, and Grow caused by the explanatory variables of the study, including Government-centered responsibility (GCR), community-centered responsibility (COMCR), firm age (FA), firm size (FS), and leverage (LV). Supplier-centered responsibility (SCR), customer-centered responsibility (CCR), creditor-centered responsibility (CRCR), and total risk (TR) were, respectively, at a 1% and 5% level of significance. The values extracted from the moderation effect show that Sub is a key factor in motivating the well-established large firms to focus on stakeholders-centered CSR practices, which ultimately improves the FP in the short and long run.

Age and market capitalization drive large price variations of cryptocurrencies

Abstract: Cryptocurrencies are considered the latest innovation in finance with considerable impact across social, technological, and economic dimensions. This new class of financial assets has also motivated a myriad of scientific investigations focused on understanding their statistical properties, such as the distribution of price returns. However, research so far has only considered Bitcoin or at most a few cryptocurrencies, whilst ignoring that price returns might depend on cryptocurrency age or be influenced by market capitalization. Here, we therefore present a comprehensive investigation of large price variations for more than seven thousand digital currencies and explore whether price returns change with the coming-of-age and growth of the cryptocurrency market. We find that tail distributions of price returns follow power-law functions over the entire history of the considered cryptocurrency portfolio, with typical exponents implying the absence of characteristic scales for price variations in about half of them. Moreover, these tail distributions are asymmetric as positive returns more often display smaller exponents, indicating that large positive price variations are more likely than negative ones. Our results further reveal that changes in the tail exponents are very often simultaneously related to cryptocurrency age and market capitalization or only to age, with only a minority of cryptoassets being affected just by market capitalization or neither of the two quantities. Lastly, we find that the trends in power-law exponents usually point to mixed directions, and that large price variations are likely to become less frequent only in about 28% of the cryptocurrencies as they age and grow in market capitalization.

Forecasting Cryptocurrency Prices Using LSTM, GRU, and Bi-Directional LSTM: A Deep Learning Approach

Abstract: Highly accurate cryptocurrency price predictions are of paramount interest to investors and researchers. However, owing to the nonlinearity of the cryptocurrency market, it is difficult to assess the distinct nature of time-series data, resulting in challenges in generating appropriate price predictions. Numerous studies have been conducted on cryptocurrency price prediction using different Deep Learning (DL) based algorithms. This study proposes three types of Recurrent Neural Networks (RNNs): namely, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Bi-Directional LSTM (Bi-LSTM) for exchange rate predictions of three major cryptocurrencies in the world, as measured by their market capitalization—Bitcoin (BTC), Ethereum (ETH), and Litecoin (LTC). The experimental results on the three major cryptocurrencies using both Root Mean Squared Error (RMSE) and the Mean Absolute Percentage Error (MAPE) show that the Bi-LSTM performed better in prediction than LSTM and GRU. Therefore, it can be considered the best algorithm. Bi-LSTM presented the most accurate prediction compared to GRU and LSTM, with MAPE values of 0.036, 0.041, and 0.124 for BTC, LTC, and ETH, respectively. The paper suggests that the prediction models presented in it are accurate in predicting cryptocurrency prices and can be beneficial for investors and traders. Additionally, future research should focus on exploring other factors that may influence cryptocurrency prices, such as social media and trading volumes.

What Is Mature and What Is Still Emerging in the Cryptocurrency Market?

Abstract: In relation to the traditional financial markets, the cryptocurrency market is a recent invention and the trading dynamics of all its components are readily recorded and stored. This fact opens up a unique opportunity to follow the multidimensional trajectory of its development since inception up to the present time. Several main characteristics commonly recognized as financial stylized facts of mature markets were quantitatively studied here. In particular, it is shown that the return distributions, volatility clustering effects, and even temporal multifractal correlations for a few highest-capitalization cryptocurrencies largely follow those of the well-established financial markets. The smaller cryptocurrencies are somewhat deficient in this regard, however. They are also not as highly cross-correlated among themselves and with other financial markets as the large cryptocurrencies. Quite generally, the volume V impact on price changes R appears to be much stronger on the cryptocurrency market than in the mature stock markets, and scales as R(V)∼Vα with α≳1.

Fractal dimension analysis of stock prices of selected resulting companies after mergers and acquisitions

Abstract: This study focuses on the short-run wealth of listed firms' shareholders. Currently, all of the resulting organizations offer competitive pricing tactics to create a superior environment for our ongoing establishment. Some time ago, it was noted that a merger occurred, although some functions and technology integration remained with the previous structure. In this paper, it has been discovered that merger and acquisition deals have an impact on the firm's value; in other words, we can view it as shareholders' wealth or unit depending on the stock price after the announcement of merger and acquisition deals in the short term. Furthermore, we focused on influencing variables on stock prices after the announcement of merger and acquisition transactions, which is measured as a percentage change in the stock prices of the listed resulting firms. Furthermore, this research is based on secondary data sources from reputable organizations. It primarily uses the NSE database and website to evaluate announcements and stock prices of the twenty-nine publicly traded companies. Markets respond to investors' emotions and market expertise. When acquirers have a strong market position, market capitalization rises in other segments. However, it is declining due to a lack of supportive finances. To determine the impact of merger and acquisition announcement deals on stock price changes, average abnormal return and cumulative average abnormal return with the capital asset pricing model (CAPM) (CAPM reaction to changes) were used to identify the acquiring company's stock price reaction. We investigated its impact on the fluctuation of share prices posted on stock exchanges using fractal interpolation functions. This is due to greater investment by acquirer businesses in target companies as well as investor expectations for specific stock market strongholds.

Capital Structure Determinants: New Evidence from the MENA Region Countries

Abstract: The objective of this paper is to investigate empirically the determinants of capital structure for a sample of 1101 firms from 11 MENA region countries over the period 2003-2017. Using a comparative approach, we find that firm-specific determinants explain better differences in capital structure choices than other country-specific determinants. Comparisons between countries, sub-regions (GGC and non-GCC countries) and legal origin (Common and Civil law countries) show furthermore that there are differences in terms of significance and importance of capital structure determinants. The most important determinant in the MENA region is profitability. The firm’s capital structure is positively impacted by size, tangibility of assets and private credit and it is negatively impacted by profitability, growth opportunities, GDP growth rate and stock market capitalization as a proportion of GDP. Moreover, we find that total leverage ratio, expressed in market values, give better results than leverage ratio expressed in book values and long-term leverage ratios expressed in book and/or market values. Finally, there is some evidence that the “Jasmine Revolution” has had an impact on firms’ capital structure determinants. Specific-level determinants play a much more prominent role after the revolution than in the past.

The Effect of Business Strategy and Firm Reputation on Financial Performance and Its Implications for Shipping Companies' Stock Returns

Abstract: The purpose of this research is to analyze the impact of business strategy and firm reputation on financial performance and its implication for stock return shipping companies. Important stock return to investors requires improvement through the business strategy, firm reputation, and financial performance. The research used a quantitative method and the data analysis used descriptive statistics and path analysis with the SmartPLS3 application. The total sample is 45 consisting of 9 companies with a 5-year observation period taken by purposive sampling technique and was listed on the Indonesian Stock Exchange between 2015 and 2019. The result of the research shows, that there is a direct impact of business strategy on financial performance, there is no direct impact of firm reputation on financial performance, there is no impact of business strategy on stock return, there is a direct impact of firm reputation on stock return, and there is no direct impact of financial performance on stock return. Companies must be able to implement appropriate business strategies by taking into account their internal and external conditions to improve their financial performance. They also have to consistently maintain and enhance their firm reputation by continuously improving the whole organization's performance so that the capitalization of the stock market will increase as well.

Peculiarities of Capitalization of the Securities Market in Ukraine

Abstract: The purpose of the article is a theoretical and methodological substantiation together with elaboration of recommendations for increasing the capitalization of the domestic securities market. The article is concerned with studying the level of development of the securities market and the directions of increasing its capitalization, which will provide favorable conditions for the formation of an appropriate level of economic development of the country. Emphasis is placed on the fact that the concept of «capitalization» is interpreted as a complex dynamic process of forming prospects for the development of the Ukrainian economy, which varies depending on the outlined tasks. It is identified that the capitalization of the stock market testifies to the intensity of the national economy and reflects the dynamics of changes in its various industries. The development tendency of the world stock market is analyzed and the experience of world leading companies with the highest level of market capitalization is adapted. The volumes and structure of trading on operators of organized capital markets by type of market are considered and the main obstacles to the further development of the Ukrainian stock market are substantiated. The need to integrate the domestic securities market into the world stock market is accentuated. Based on the carried out correlation analysis, it is found that the closest relationship between the volume of trading in shares on the Ukrainian securities market and the aforementioned factors occurs with the total trading volume in the securities market, namely: the more transactions are carried out on the market, the higher the volume of transactions with shares. It is noted that the domestic securities market in order to improve the efficiency of further functioning requires: improvement of the legislative framework; increasing the level of motivation; minimization of financial risks; improving infrastructure development, etc. Further research will be aimed at developing promising directions for the integration of the domestic stock market into the global financial space.

Impact of Capital Market on GDP Growth in Nepal

Abstract: This study explores the connection between the capital market and Nepal's GDP growth from 1994 to 2002. The study examines how capital market performance affects the GDP growth of Nepal. The ARDL approach was used to examine the capital market's long-term effect on economic growth. To this extent, variables like market capitalization, gross fixed capital formation as investment, broad money supply, the NEPSE Index, the number of listed companies in NEPSE, and recurring expenditures were used in the system, affecting GDP growth. According to the study, the correlation shows the presence of a strong linkage between the capital market and GDP growth in Nepal. Findings show that the capital market has a significant influence on GDP growth. Negative and significant error correction terms indicate how quickly shocks and equilibrium are corrected. Some of the variables are insignificant in the short and long run, indicating the presence of structural and institutional lacks in Nepal's capital markets.

Capital market capitalization and economic growth in Nigeria: an econometrics analysis

Abstract: There is no doubt that capital market capitalization plays an essential role in economic growth of any nation and increasing access to a developed capital market is essential to unlocking rapid economic growth in Nigeria. Consequently, this paper has empirically examined the nexus between capital market capitalization and economic growth in Nigeria using annual time series data for the period 1990-2021. By applying Augmented Dickey Fuller, OLS, co-integration and causality tests the results indicate that there is a positive and significant relationship between capital market capitalization and economic growth, there is a long-run relationship between the variables and also unidirectional causality was found from MCAP to GDPG. Subsequently, the paper recommends that policy makers should concentrate on implementing short-term and long-term policies that will develop the Nigerian financial system especially the capital market since it is capable of boosting economic growth in Nigeria.

Is it worth limiting the ownership and investment of foreign companies? (Stock market case)

Abstract: To identify possible equity market implications of restrictions on foreign ownership and investment in Russia; as well as against Russian ownership abroad; we reviewed data from 38 countries and applied fixed effects models to panel data. We show that restrictive measures against foreign ownership and investment will have a negative impact on the capitalization of the domestic stock market. The effect will be amplified under the influence of such factors as corruption; freedom of investment; financial; trade and business freedoms. The quality of the judiciary is most important when examining the share of the domestic stock market in the world stock market. Tax incentives and increased fiscal freedom will not be able to have a positive impact in the face of restrictive measures against foreign ownership and investment.

Impact Of dividend decision on the market capitalization of the firm: Evidence from Indian large cap companies

Abstract: The percentage of the profit distributed to the shareholders is known as the dividend. The decision at hand is how much of the company's profit should be divided to the shareholders after taxes have been paid. It also contains the portion of the profit that needs to be invested back into the company. The retained earnings boost the company's potential for future earnings when the present income is reinvested. The amount of retained earnings has an impact on the company's choice of financing as well. The decision to declare a dividend should be made with the goal of maximizing shareholder value in mind. The present study attempted to evaluate the impact of dividend decision on the market capitalization using regression model. The regression analysis model revealed the significant impact of the independent variable on the market price of the share as well as the dividend policy determinants on the subsequent market price variable.

Market Capitalization Research of Companies

Abstract: Accelerating growth of online-services expanding into the post-COVID world has strengthened competing for leadership in the key areas and changed the infrastructure of global economy’s capitalization. A study of system of economic relations enables better and more comprehensive understanding of the MNC’s place and role in the modern global economy. For the third consecutive year technology become a major industry from the point of view of market capitalization. However, from the point of view of an growth in the interest value such areas as healthcare, telecommunications and household services increased by 15% each in comparison with technological industry which growth in 2020 constituted only 6%. The last place among the leading global MNC from the industrial perspective is occupied by the financial area. In the mentioned segment multinational companies have undergone contraction of the market capitalization cost by 3% in total. Nevertheless, MNC among the Top-100 have managed to succeed much more than another companies in the mentioned sector. Changes in the global market in the 21st century have significantly increased the role of MNCs in sustainable infrastructure of the global economy.

The Impact of Sino-US Trade War on The Stock Markets of The Two Countries

Abstract: This paper analyzes the parallels and variances between the stock markets of the US and China, and the impacts of Sino US Trade War on stock markets in the same countries. The findings are showing that the US and China exchange stock markets are divided into different stock markets and play a critical role in each country’s economy. The stock markets have some differences in the level of development of the accessibility to funds, with the US stock economy being more developed and more integrated into the economy than China's economy. The findings show the Sino-US trade war has been affecting China and the US stock markets negatively. The adverse effects reflect in stock market fluctuations, decline in market capitalization, market equity loss, reduction in prices, and the returns from the stock markets. These adverse effects imply that the Sino-US trade war created more negative impacts than the intended implementation goal.

Predicting Top Five Cryptocurrency Prices via Linear Structural Time Series (STS) Approach

Abstract: Predicting cryptocurrency prices are difficult due to dynamic data. At the same time, the hidden market behavior of trend and seasonal components in the history data is also critical as it provides an idea of what the price pattern will be in the future. Hence, this research proposes to identify and model the hidden pattern behavior in terms of component time series instead of removing it via the linear structural time series (STS) model approach. This study focuses on the top five cryptocurrencies relying on the highest market capitalization. From the results obtained, the top five cryptocurrencies have a different trend model, either deterministic or stochastic, which relies on the behavior of data. The five cryptocurrencies also show the crypto winter event, where the trend is downward after six months every year. The linear STS is the best model for predicting three cryptocurrencies’ prices for nonstationary and volatility data behavior. It can also handle the hidden component behavior and is easy to interpret. Since the linear STS model can indirectly retain the information of data, it will assist investors and traders in accurately predicting cryptocurrency prices.

A Cointegration and Clustering-based Approach to Pair Trading of Stocks from Selected Sectors of the Indian Stock Market

Abstract: <p>This work presents a cointegration-based pair-trading strategy for identifying stock pairs with substantial cointegration in their prices across four years (January 1, 2018, to December 31, 2021). After the Cointegrated pairs are determined, pair-trading portfolios are created, and portfolio performance is tracked during a one-year test period (January 1, 2022, to December 31, 2021). Suitable trigger points are determined utilizing a very powerful spread detection system, allowing both stocks' short and long positions to be precisely recognized. The yearly return of a portfolio is used to assess its performance. First, twelve sectors of stocks from the National Stock Exchange (NSE) of India are selected. According to the NSE's monthly report for the month of December 31, 2022, the top ten stocks in terms of their free-float market capitalization from the twelve sectors are selected. Pair trading portfolios are built using pairs from each sector that demonstrated cointegration of close prices from January 1, 2018, to December 31, 2021. The portfolios are evaluated based on their return from January 1, 2022, to December 31, 2022. Furthermore, clustering-based techniques were used to identify stocks that behaved similarly for the period of four years i.e., January 1, 2018, to December 31, 2021. This was performed by using three clustering techniques and the best technique, based on their respective results, was chosen to identify the clusters to verify the cointegrated pairs. Henceforth, the pairs which were common in both cointegration, and clustering techniques were regarded as the most recommended pairs for trading. The work makes three distinct contributions. First, the paper provides a cointegration-based pair trading strategy for stock portfolio creation, that can be used to earn profit by the investors in the stock market. Second, the pair-trading models are trained and tested on real-world stock market data, with the results displayed to illustrate the models' efficacy. Finally, since the stocks utilized in the pair trading portfolio designs are drawn from various NSE sectors, the outcomes of the pairings are an excellent signal of the possible profit that investors could make if they invest in those sectors using the recommended pair-trading technique. </p>

The impact of capital market on the economic growth of Nigeria

Abstract: The study assessed how the capital market affected Nigeria's economic expansion. Specifically, the impact of the Nigeria stock exchange's total value of transactions (TVTs), all-shares index (ASIs) and stock market capitalisation (MCAP) on Nigeria's economic development was evaluated. Time-series data covering 1986–2021 was obtained in the study. Estimation methods used in the study’s analysis include descriptive statistics correlation analysis, ARDL co-integration analysis, parsimonious error correction model, variance decomposition and other post-estimation tests. Discoveries from the study showed that MCAP positively impacts economic growth in the long and short run. The ASI affects economic growth positively and insignificantly in the long and short runs, and the TVTs exerts a significant positive effect on the economic growth of Nigeria. Hence, the study suggested that the Security and Exchange Commission should explore measures, including technological integration in trading activities, to deepen development in the capital market. Keywords: All-share index, gross fixed capital formation, market capitalisation, real gross domestic product, total value of transactions;

Sustainability Reporting in Energy Companies—Is There a Link between Social Disclosures, the Experience and Market Value?

Abstract: As a result of the dissemination of the sustainability concept, social disclosures have become an important area of non-financial reporting, and the energy sector is no exception. The purpose of our article is a multi-faceted evaluation of sustainability reports published by companies operating in the Polish energy sector, from the perspective of social disclosures. The study involved the Polish listed companies that made up the WIG-Energia index. The time scope of the study covers the 2017–2021 period. In total, 54 non-financial reports were analyzed. In the first place, a comparative analysis was carried out to assess the social disclosures made by the WIG-Energia companies against the background of the biggest and the most liquid (blue chip) WIG20 companies. All the applied tools: ESG rating, NFR_S index, and multidimensional data visualization, have confirmed that the energy companies year by year have been presenting larger and larger extents of social disclosures. At the same time, it was observed that the companies appearing for the first time in the WIG-Energia index showed a very small extent of disclosures, whereas the companies which figured in the index throughout the studied period presented a relatively large extent of disclosures, due to their experience in preparing sustainability reports. Next, using the Pearson correlation coefficient (r), we examined the relationship between the energy companies’ market values and the extent of their social disclosures. The results of the statistical analyses have validated the strong and very strong correlation between capitalization and extent of disclosures. It is therefore possible to state that companies with higher market values are characterized by larger extents of social disclosures.

Assessment of the relationship between market-based financial system and gross domestic product par capita, kenya.

Abstract: This study assessed the relationship of market-based financial system development indicators and Gross Domestic Product par capita in Kenya. for the period running from 1997 to 2007. The Gross Domestic Product was as low as 1.2% in the first macroeconomic stability in the period running from 1997 to 2001 and was as high as 7.0% in the second macroeconomic stability in the period running from 2002 to 2007. Data capture was by census technique and checking of secondary material on Kenya National Bureau of Statistics(KNBS), Nairobi Security Exchange(NSE), and Capital Market Authority(CMA), Data analysis and interpretation was through descriptive statistics and inferential statistics. The financial indicators of a market-based financial system were characterised as size, activity and efficiency indicators. Stock market capitalization/GDP, private bond market capitalization/GDP, public bond market capitalization/ GDP were size indicators. Stock market total value traded / GDP was activity indicator. Stock market turn- over ratio was efficiency indicator. This study was in relation to literature review which depicts some financial indicators as being counterproductive to each other and in their contribution to GDP per capita. In the first macroeconomic stability (1997-2001), the bank based financial system was79% against 21% of the market based financial system. In the second macroeconomic stability (2002-2007), the bank based financial system was 54% against 46% of the marked based financial system. Financial indicators (Public bond capitalization Ksh.bn/GDP, Market Capitalization Ksh.bn/GDP, turnover ratio and total value traded) as significant predictor of GDP per capita and significantly correlated to GDP par capita in Kenya.

The study of government policy on stock market development and economic growth in nigeria (1984-2020)

Abstract: This study explored the relationship between stock market development and Nigerian economic growth. This was done to look at Nigeria's stock market and economic growth from 1984 to 2020. The analysis relied on secondary data. The Central Bank of Nigeria statistical bulletin for 2021 presented data on stock turnover ratio, stock market capitalization ratio, total value of shares exchanged ratio, all share index, and GDP. Granger causality, Augmented Dickey Fuller Unit root test, Johansen cointegration test, and error correction model were used to analyze the data. Granger causality was shown. There is no reverse causality between stock market development metrics such as stock market capitalization ratio, turnover ratio, or total value of shares exchanged ratio and economic growth. All share index, stock market capitalization ratio, turnover ratio, and economic growth were integrated of order 1, while total value of shares traded ratio was integrated of order zero, according to unit root test results. The Johansen cointegration test showed that the All-Share Index, Stock Market Capitalization Ratio, Turnover Ratio, and Economic Growth all have four cointegrating relationships. Changes in the all-share index have a positive and significant impact on changes in economic growth, whereas changes in the stock market capitalization ratio and its lag have a negative but insignificant impact on changes in economic growth (p>0.05). Changes in the turnover ratio have a positive but insignificant impact on changes in economic growth (p>0.05), while its lag has a negative but insignificant impact on changes in economic growth (p>0.05). Changes in lagged GDP have a positive and important effect on changes in economic present-period growth (p0.01), and economic growth and the independent variables in our model have a long-run relationship as indicated by the negative and statistically significant error correction term in the model (p<0.01). Based on the results, the study recommends that the Federal Government intervene through the Asset Management Corporation of Nigeria (AMCON)/Ministry of Finance Incorporated, that more indigenous quotable companies be encouraged to pursue listing by offering incentives such as tax holidays, tax rebates, and other incentives, and that stock broking firms be encouraged to join forces, either through mergers or outright acquisition amongst other recommendations.

Bubble or Not: Measurements, Analyses, and Findings on the Ethereum ERC721 and ERC1155 Non-fungible Token Ecosystem

Abstract: The non-fungible token (NFT) is an emergent type of cryptocurrency that has garnered extensive attention since its inception. The uniqueness, indivisibility and humanistic value of NFTs are the key characteristics that distinguish them from traditional tokens. The market capitalization of NFT reached 21.5 billion USD in 2021, almost 200 times of all previous transactions. However, the subsequent rapid decline in NFT market fever in the second quarter of 2022 casts doubts on the ostensible boom in the NFT market. To date, there has been no comprehensive and systematic study of the NFT trade market or of the NFT bubble and hype phenomenon. To fill this gap, we conduct an in-depth investigation of the whole Ethereum ERC721 and ERC1155 NFT ecosystem via graph analysis and apply several metrics to measure the characteristics of NFTs. By collecting data from the whole blockchain, we construct three graphs, namely NFT create graph, NFT transfer graph, and NFT hold graph, to characterize the NFT traders, analyze the characteristics of NFTs, and discover many observations and insights. Moreover, we propose new indicators to quantify the activeness and value of NFT and propose an algorithm that combines indicators and graph analyses to find bubble NFTs. Real-world cases demonstrate that our indicators and approach can be used to discern bubble NFTs effectively.

The Effect of Market Capitalization, Trading Volume, Book Value, and Capital Structure on Share Prices

Abstract: The share price represents the company's value on the share market; buyers and sellers establish the company's value based on the quantity of demand and supply of shares. This research looks at how market capitalization, trading volume, BV, and DER are used to analyze share price variations. The research aims to understand investor behavior in fluctuating market situations. The method used is to analyze multiple linear regression, and the data collection method is secondary data. This study's results indicate a relatively significant correlation between market capitalization, trading volume, BV, DER, and share prices, implying that predictor variables may adequately describe the reasons for price fluctuations. The conclusion of the research results reveals that from 2019 to 2021, investors act rationally in making judgments while conducting transactions or preserving their cash in the Bank and Insurance Sub-Sector. JEL, classification： G11 G12 Keywords: Market Capitalization; Trading Volume; BV; DER; Share Stocks