KSE-100 Index Research Articles

THE IMPACT OF GREEN BANKING PRACTICES ON BANKS’ COST OF CAPITAL; EVIDENCE FROM A DEVELOPING COUNTRY

Purpose: This study aims to explore whether green banking practices by Pakistani banks have any impact on their cost of equity and cost of debt. Design/Methodology: We constructed a specifically designed composite green banking index to measure the extent of green banking practices from banks within the sample. Cost of capital is represented by the cost of debt and cost of equity. Banks listed on Pakistan’s KSE-100 Index over a period of the 10 years i.e. from 2010 to 2019 is used as our study sample. Panel Data Regression analysis is used to test the hypothesized relationships. Findings: Green banking is still in its evolution phase among Pakistani banks. While the debt market is stricter and is incorporating these practices in advancing financing to the banks, there is still a need for investor education and awareness at the equity market level, which has not yet been incorporated in the pricing of the banking stocks. Originality: Green banking is still in its evolution phase among Pakistani banks. While the debt market is stricter and is incorporating these practices in advancing financing to the banks, there is still a need for investor education and awareness at the equity market level, which has not yet been incorporated in the pricing of the banking stocks.

Capital Asset Pricing Model for the Stock Market in Pakistan

The Capital Asset Pricing Model (CAPM), within modern financial theory, offers a theoretical framework for pricing assets with uncertain returns. CAPM assesses systematic risk and proposes a linear relationship between risk and expected returns for any asset. It serves as a potent tool for pricing risky assets. In this present study, the trade-off between risk-return was investigated within the framework of CAPM and its validity was tested on the daily returns of companies listed in the chemical, textile and food sectors of the Pakistan stock market during the period July 2004- Feb 2014. The results of empirical testing by regression analysis supported the CAPM’s validity for these sectors in Pakistan and found CAPM β as a single factor which was priced by the market. The KSE-100 index was used as a market, and the year treasury-bills return rate was taken as a risk-free rate.

Stock Price Prediction Using Machine Learning: Evidence from Pakistan Stock Exchange

This research investigates the utilization of machine learning methodologies for the purpose of forecasting the fluctuations in stock values inside the financial market. The application of a Random Forest classifier is utilized on a dataset including historical stock prices (namely, the KSE-100 Index) to generate predictions regarding the future movement of stocks, specifically whether they would experience an increase or decrease. The model is trained via a sliding window methodology and is assessed through the utilization of precision, recall, and F1-score criteria. The study furthermore incorporates the utilization of back testing and hyper-parameter tweaking techniques in order to enhance the performance of the model. The findings indicate that the model demonstrates a precision score of 58%, representing an enhancement compared to the previous score of 48%. Nevertheless, the model's total accuracy stands at a mere 58%, underscoring the need for future enhancements. The report additionally proposes potential avenues for future research, such as exploring alternate data sources, employing sentiment analysis techniques, and developing more advanced algorithms. The findings of this study hold significant significance for investors and financial institutions, as they highlight the potential of machine learning in facilitating informed investment decisions and improving financial forecasts and analysis.

Examining the Impact of Capital Structure and Board Diversity on Firm Performance: Evidence from Pakistan Stock Exchange

This study aims to investigate the relationship between capital structure, board diversity, and firm performance among KSE-100 index firms listed on the Pakistan Stock Exchange. We use a panel data approach and STATA MP-14 to analyze the impact of two capital structure measures (debt-to-equity ratio and debt-to-total assets) and three board diversity measures (female representation, female executive presence, and male executive presence) on three financial performance indicators (firm size, firm age, and return on equity). Our findings reveal a significant positive association between debt financing and female board representation, as well as a positive relationship between capital structure and female executive presence. However, we find an insignificant and negative relationship between capital structure and managerial ownership. This study contributes to the existing literature on corporate governance and capital structure by highlighting the importance of board diversity in emerging markets. Future studies can build on our findings by exploring the relationship between capital structure and board diversity in other developing countries and comparing the results to identify potential variations.

Intellectual capital and firm risk: evidence from an emerging economy

Purpose Intellectual capital (IC) plays a pivotal role in determining corporate risk profiles in the contemporary knowledge era. Consequently, this study aims to analyze the impact of IC on firm risk (FR) among the manufacturing companies listed on the Pakistan Stock Exchange (PSX). Design/methodology/approach The authors have adopted the modified value-added intellectual model which combines human capital efficiency, structural capital efficiency, efficiency of capital employed and relational capital efficiency. FR has been used as the dependent variable, measured as the standard deviation of the daily stock prices. The study has used panel data from a sample of 40 manufacturing companies listed in the KSE-100 Index from 2015 to 2021. Findings The results suggest that IC has a significant impact on the FR of manufacturing companies listed on the benchmark index of PSX. Moreover, this relationship is direct; thus, an increase in IC would also increase FR measured by the change in stock prices. Research limitations/implications The current study has only used linear techniques. Future researchers may consider investigating the impact of IC at varying levels of FR using nonlinear techniques. Practical implications This study provides corporate managers and policymakers valuable insight into the need to strike a balance between investment in IC and their FR, particularly in an emerging market context. Originality/value IC is frequently associated with firm performance. However, the relationship between IC and FR has generally been underexplored. This study adds to the strand of limited IC literature by investigating the impact of a modified IC model on FR in an emerging economy.

Intellectual Capital, Financial Performance, and the Mediating Role of Financial Vulnerability

This study investigates the contribution of intellectual capital in enhancing firms' financial vulnerability and performance in Pakistan's emerging economy. This research considered ten years of data from 2011 to 2020 of non-financial firms listed on the stock exchange of Pakistan (PSX) and falls in the KSE-100 index. This research successfully applied a previously defined regression methodology to test the hypothesis investigating the significance of intellectual capital. Empirical investigation successfully reveals IC's significance in improving firms' financial vulnerability and performance using an aggregate measure of IC called value-added intellectual coefficient (VAIC) and its components human capital, structural capital, and capital employed efficiency. Financial Vulnerability mediates between intellectual capital and financial performance. The results of this study prove VAIC significance in developing countries like Pakistan. The study also shows that Pakistani investors and firms give IC weight in their investment decisions and must focus on IC for success in a competitive world. Accounting bodies should also focus on developing standards that incorporate IC as an asset. This study considered firms of multiple sectors to examine the significance of IC in Pakistani firms successfully. Along with enhancing IC literature, the VAIC model is significant in measuring IC in developing economies. This study also tried to extend IC literature in the context of the financial Vulnerability of firms and its indirect impact on financial performance.

Measuring the Performance of KSE100: The Impact of Demutualization

The purpose of this study is to assess how the demutualization process has affected the performance of the KSE100 Benchmark Index. The study utilized Descriptive Statistics and a Paired sample t-test, as well as daily data from KSE-100 spanning 2009 to 2019. This data was analysed in terms of market capitalization, traded value, daily stock returns, and trading volume. Our results show that, overall, market capitalization increased significantly during the period, except in the second phase. Daily stock returns for the KSE100 Index did not improve over the entire period, though the decrease was not statistically significant. Trading volume did not improve and decreased significantly in both the first and second phases, but increased after the listing of the Pakistan Stock Exchange on its own exchange. The overall conclusion is that the performance of the Index improved, which is a crucial finding for foreign investors looking to invest in the Pakistani stock market. The study is also significant for institutional investors, local investors, potential investors, and portfolio managers who are interested in the growth and development of the stock market. This study is a valuable addition to existing literature, as a significant portion of the existing literature on the demutualization of the Pakistan Stock Exchange is qualitative.

The Spill-over Effects between Oil and Gas Marketing and Exploration Firms of Pakistan Stock Exchange (PSX) KSE-100 index: During the Times of COVID-19 and Russian-Ukraine War

This study aims to trace the mean and volatility spillover effects between oil and gas marketing and exploration firms registered in KSE-100 index in the Pakistan Stock Exchange (PSX). Daily data of 8 firms (MGAS, PPL, PKOL, APL, HITE, HASC, PSO, and SHEL) for the period of 30th November 2019 to 30th November 2022. The whole data set is divided into two subsets, one is after COVID-19 (after 26th February2020) and the other is after the start of Russian-Ukraine war (after 24th February 2022). After that Hamao et.al (1990) uni-variate ARCH-GARCH type modeling is employed to the data in order to explore the dynamic linkages between the Marketing and Exploration firms (oil and gas) registered in KSE-100 index (PSX). The results from the data sets are indicating that there is mix movements between the oil and gas marketing and exploration firms in the KSE-100 index (PSX). The results are providing evidence there is Mean spill over from MGAS to APL, HASC, HITE, PSO, and SHEL. From PKOL to APL, HASC, HITE, PSO, and SHEL. From PPL to APL, HITE, PSO. And there is Volatility spill over from MGAS to APL, HITE, PSO and SHEL. From PKOL to APL, HITE, PSO, and SHEL. From PPL to APL, HASC, HITE, PSO, and SHEL. This linkage is developed between MGAS, PPL, and PKOL to APL, HASC, HITE, PSO, and SHEL due to the co-movements among the mentioned firms. The Augmented Dickey-Fuller Test is run on the return series and the test is insignificant in all series which is indicating that our return series are stationary at level, ARCH-LM test is run on return series and ARCH-LM test is also insignificant in all the return series means that there is no heteroskedasticity present in the return series.

Technological advancements and noise trading: A case of investors’ sentiments at the Pakistan Stock Exchange

This study uses data from the KSE-100 stock index from 2009 to 2021 to investigate the influence of technological advancements, investors' sentiments, and behavioral factors on stock market inefficiency. The study employs a threshold regression model to distinguish between different thresholds of these factors and a Wald test is used to determine the significance of the variances among thresholds. The results indicate that technological advancements, investors' sentiments, and behavioral factors significantly affect the predictability of returns in the KSE-100 index. This study is unique in the context of Pakistan and provides a comprehensive framework for understanding stock market operations. The findings have practical applications for individuals, researchers, managers, institutions, and policymakers seeking to better understand the impact of technology, society, and behavioral biases on stock markets. Furthermore, this study provides unique insights into addressing the issue of market inefficiency by identifying the factors responsible for such behavior.

A Small Club: Distribution, Power and Networks in Financial Markets of Pakistan

1. THE STOCK MARKET THAT DOES NOT GROW!
 Pakistan’s stock market tends to make headlines, sometimes because of record highs * that make it the ‘best performing market of the region’, and sometimes because of the crashes. However, the degree to which it contributes to capital formation in the country is not a topic of study, while the ensuing ownership and governance structure is hardly ever made a part of public discourse.
 One such study concluded that “around 64 percent of the 44 selected sample companies are controlled by prominent business groups and families of Pakistan”. This paper extends the aforementioned research to cover the top 100 companies that constitute the benchmark KSE-100 index at the Pakistan Stock Exchange (PSX). It also analyses the structure of ownership and sponsor control of companies constituting the KSE-100, and their impact on the functioning and transparency of the stock market.
 Pakistan’s corporate governance and human resource management practices are frequently questioned in the media and academic circles. A common phenomenon is companies managed as family enterprises despite being listed on the stock exchange. The offspring of the owners tend to be absorbed into the management of these companies, which are referred to as ‘seth companies’, seth being the founder/owner of the company.
 The objective of this paper is twofold. The first is to shed light on corporate groups and their ownerships in the stock market. We review the ownership structures of the large conglomerates to examine the extent of diversification in the stock market. This also gives us an idea of the kind of power that large houses wield in the market, and the choices available to the small shareholder. Secondly, we look at corporate governance by looking at how company boards are structured and examine the influence of the owner and his family on the structure and professional management of the company.

Uncovering the Effect of News Signals on Daily Stock Market Performance: An Econometric Analysis

The stock markets in developing countries are highly responsive to breaking news and events. Our research explores the impact of economic conditions, financial policies, and politics on the KSE-100 index through daily market news signals. Utilizing simple OLS regression and ARCH/GARCH regression methods, we determine the best model for analysis. The results reveal that political and global news has a significant impact on KSE-100 index. Blue chip stocks are considered safer investments, while short-term panic responses often overshadow rational decision-making in the stock market. Investors tend to quickly react to negative news, making them risk-averse. Our findings suggest that the ARCH/GARCH models are better at predicting stock market fluctuations compared to the simple OLS method.

Exploring Asymmetric Linkages and Volatility Transmission between Stock Market and Foreign Exchange (FOREX)

This study examines the direction and nature of volatility transmission between the stock market and the foreign exchange market (FOREX) of Pakistan. For this purpose, daily data is gathered to conduct the analysis for both markets. Stock market returns are measured by using the KSE-100 index and the daily Pakistan Rupee-PKR to the United States Dollar-USD exchange rate is used for the foreign exchange market. Noticeably, both the variables are stationary at their first difference. Normality is examined through Skewness and Kurtosis, Autocorrelation through Correlogram Q-statistics, and the ARCH effect through the ARCH-LM test. Volatility transmission between the two markets is examined by using bivariate diagonal BEKK-GARCH and bivariate E-GARCH models. The results of the study indicate that bi-directional volatility transmission exists between the stock market and the foreign exchange market (FOREX) of Pakistan. Results from the E-GARCH model further indicate that the nature of volatility transmission between these two markets is asymmetric, which means bad news of one market has a greater impact on the volatility of another market than the good news. Hence, the results of this study also indicate that past variances of the stock market and foreign exchange market has a significant effect on their own current volatility.

Do good and bad news affect the day of the week effect? An analysis of the KSE-100 Index

Do good and bad news affect the day of the week effect? An analysis of the KSE-100 Index

Dividend Policy and Firm Performance with Moderating Effect of Ownership Structure: Evidence from The Manufacturing Firms in Pakistan

The objective of this paper is to check the impact of dividend policy and firm performance with a moderating effect of ownership structure. Many studies have been made to check the impact of dividend policy on firm performance but there is not a single study that has been made yet to check the impact of dividend policy and firm performance with moderating effect of ownership structure. This research had been carried out on different non-financial sectors of Pakistan covering the firms of automobile assembler and parts manufacturing, cement and chemical manufacturing, fertilizer manufacturing, pharmaceuticals, and textile manufacturing etc. The data used in carrying out this research was taken from the companies that was paying dividends and were listen in KSE-100 index of Pakistan Stock Exchange. Ownership data of the firms were collected by the company’s pattern of shareholding which are published or mentioned in the company’s annual report as per Securities and Exchange Commission of Pakistan (SECP) requirements that can be taken from the company’s website. The study shows significant positive relationship between dividend policy and firm performance. The study also shows that there is positive significant relationship between dividend policy and firm performance with moderating effect of ownership structure. Dividend policy can also have implications for a company's investment and growth prospects. In general, firms that retain more of their earnings for reinvestment are likely to have higher levels of capital expenditures and research and development spending. However, dividend payments can also signal to investors that a company has confidence in its future growth prospects.

Revisiting the relationship between idiosyncratic risk and stock returns: a quantile regression analysis in the context of an emerging market

PurposeThe relationship between idiosyncratic risk and stock return has been debated for decades; this study reexamined this relationship in the Pakistani stock market by using the quantile regression approach along with the prospect theory.Design/methodology/approachThe present study is quantitative, and secondary data obtained from an emerging market are used. The quantile regression method allows the estimates of idiosyncratic risk to vary across the entire distribution of stock returns, i.e. the dependent variable. In this study, the standard deviation of regression residuals from the Fama and French three-factor model was used to measure idiosyncratic risk. Convenience sampling is employed; the sample consists of 82 firms listed on the KSE-100 index, with 820 annual observations for the ten years from 2011 to 2020. After computing results by using quantile regression, the study's findings, ordinary least squares (OLS) and least sum of absolute deviation (LAD) regression techniques are also compared.FindingsThe quantile regression estimation results indicate that idiosyncratic risk is positively correlated with stock returns and that this relationship is contingent on whether prices are rising or falling. Consistent with the prospect theory, the finding suggests that stock investors tend to avoid risk when they anticipate a loss but are more willing to take risks when they anticipate a profit. The results of the OLS and LAD regressions indicate that the method typically employed in previous studies does not adequately describe the relationship between idiosyncratic risk and stock return at extreme points or across the entire distribution of stock return.Originality/valueThese empirical findings shed new light on the relationship between idiosyncratic risk and stock return in Pakistani stock market literature.

A Comparison of Competing Asset Pricing Models: Empirical Evidence from Pakistan

In recent years, the rapid and significant development of emerging markets has globally led to insight from potential investors and academicians seeking to assess these markets in terms of risk inheritance. Therefore, this study aims to explore the validity and applicability of the capital asset pricing model (henceforth CAPM) and multi-factor models, namely Fama–French models, in Pakistan’s stock market for the period of June 2010–June 2020. This study collects data on 173 non-financial firms listed on the Pakistan stock exchange, namely the KSE-100 index, and follows Fama-MacBeth’s regression methodology for empirical estimation. The empirical findings of this study conclude that small portfolios (small-size companies) earn considerably higher returns than big portfolios (large-size companies). Ultimately, the risk associated with portfolio returns is reported to be higher for small portfolios (small-size companies) than for big portfolios (large-size companies). According to the regression output, the CAPM was found to be valid for explaining the market risk premium above the risk-free rate. Similarly, the FF three-factor model was found to be valid for explaining time-series variation in excess portfolio returns. Later, we added human capital into FF three- and five-factor models. This study found that the human capital base six-factor model outperformed the other competing asset pricing models. The findings of this study indicate that small portfolios (small-size companies) earn more returns than big portfolios (large-size companies) to reward the investor for taking extra risks. Investors may benefit by timing their investments to maximize stock returns. Company investment in human capital adds reliable information, replicates the value of the company and, in the long term, helps investors make rational decisions.

Impact of Managerial Entrenchment on Firm Performance

This research attempts to analyze the impact of managerial entrenchment on firm performance in the context of KSE-100 index companies in Pakistan. The given study engages the CEO share as the measure of managerial entrenchment and investigate its impact on financial performance of companies. In pertinent to this, regression analysis has been utilized by employing the top performing corporations listed on KSE-100 index. For measurement of firm performance, this study employs the two variables used to quantify firm performance as “return on assets (ROA)” and “Tobin's Q”. This study comprises 318 observations, from 53 non-financial companies of Pakistan Stock Exchange (PSX), over 6 years period (2015-2020) from annual reports. The results of this study indicate that there is a significant negative relationship between the managerial entrenchment measured through CEO share and financial performance measured through ROA and Tobin’s Q. The study has some limitations. The future researchers can add other parameters of managerial entrenchment such as board independence, board compensation, tenure and management duality to get more insights on this association. The research findings are giving implications for managers, investors and shareholders. Managers may adopt techniques that allow them to strengthen their position thus gaining investors’ confidence. This research extends the literature by comprehensively employing the impact of managerial entrenchment on financial performance of companies in KSE-100 index companies that was predominately neglected by the previous researchers in context of Pakistan

Nexus between Investor Sentiment and Equity Returns in Pakistan Stock Exchange

The term Investor Sentiment (IS) depicts the mental activities of investors and reflects their expectations towards the market. It plays a crucial role in their decision making process, which ultimately affects the stock market. The current research attempted to examine the nexus between IS and Equity Returns (ER) of 61 financial and non-financial firms of the KSE-100 index of Pakistan Stock Exchange (PSX). Data was collected from the official website of PSX and the published annual reports of the companies for the period 2008–2019. Vector Auto Regression Model (VAR) was used to determine the relationship between dependent and independent variables. The findings revealed that the Share Turnover (SHT) and Money Flow Index (MFI) indicated a significant positive relationship with ER for the KSE-100 index. Similarly, the Price Earnings Ratio (PER) was found to be significantly inversely related to ER. The current study is important both for investors to predict stock trends and for the government's formulation of policies to prevent excessive stock market volatility. It also suggests some important implications for policymakers and investors in order to improve investment policies and make good investment decisions.
 
 Keywords: Investor Sentiment, price earnings ratio, share turnover, money flow index. 
 JEL Codes: E41, E43, E42, E31

Prediction of Complex Stock Market Data Using an Improved Hybrid EMD-LSTM Model

Because of the complexity, nonlinearity, and volatility, stock market forecasting is either highly difficult or yields very unsatisfactory outcomes when utilizing traditional time series or machine learning techniques. To cope with this problem and improve the complex stock market’s prediction accuracy, we propose a new hybrid novel method that is based on a new version of EMD and a deep learning technique known as long-short memory (LSTM) network. The forecasting precision of the proposed hybrid ensemble method is evaluated using the KSE-100 index of the Pakistan Stock Exchange. Using a new version of EMD that uses the Akima spline interpolation technique instead of cubic spline interpolation, the noisy stock data are first divided into multiple components technically known as intrinsic mode functions (IMFs) varying from high to low frequency and a single monotone residue. The highly correlated sub-components are then used to build the LSTM network. By comparing the proposed hybrid model with a single LSTM and other ensemble models such as the support vector machine (SVM), Random Forest, and Decision Tree, its prediction performance is thoroughly evaluated. Three alternative statistical metrics, namely root means square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE), are used to compare the aforementioned techniques. The empirical results show that the suggested hybrid Akima-EMD-LSTM model beats all other models taken into consideration for this study and is therefore recommended as an effective model for the prediction of non-stationary and nonlinear complex financial time series data.

Impact Of Retrenchment Generalship on Firm Performance: Pakistan's Listed Companies as Evidence

Retrenchment refers to a business strategy that reduces the company's Size by decreasing its level of diversity. When a business experiences losses, cutting costs and slowing operations is one ways to ensure the company can continue operating. The study's goal is to learn more about how Retrenchment Strategy and financial indicators affect the success of Pakistan's publicly listed companies. Secondary data from the yearly financial statements of 76 non-financial businesses listed on the KSE-100 Index between 2015 and 2021 has been utilized to analyze Retrenchment and performance characteristics. We tested whether or not any of our research assumptions held using Panel Regression Analysis (ROE model) and Fixed Effects Panel Regression Analysis (ROA model). Based on the results of the panel regression analysis, it is clear that the Retrenchment Strategy has a significant and favourable impact on the success of Pakistani businesses. In support of the company's Retrenchment practices, the study provides evidence from Resource Basis View Theory and the Agency Theory. Using retrenchment as the primary dependent variable, it first examines how this strategy relates to the success of businesses. In addition, it will add to the canon by shedding light on the rising markets in Pakistan. The findings might serve as a benchmark for similar studies to be conducted in the future in Pakistan