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Background This study aims to gain insight into the effect of banks' financial performance on their market performance. We conceptualized the research subject on the assumption that the financial performance of an organization is the most important criterion for triggering movement in its stock price. We explored various models and parameters to evaluate financial performance of banks and found CAMELS being one of the most comprehensive and appropriate model. We considered share price growth of banks to measure their stock market performance Methods We collected financial and stock market data pertaining to 32 listed Indian banks for the period 2018 to 2022. The study has employed multiple linear regression analysis of panel data for evaluating the relationship between independent and dependent variables. We adopted panel regression for data analysis and used the Prais- Winsten regression with panel corrected standard errors, as the data suffers from contemporaneous cross-sectional correlation. Results The results show that net non-performing assets, net interest margins, and return on capital have a significant negative impact on share price growth. The capital adequacy ratio and the current and savings account deposit ratios have a positive insignificant impact. The liquid asset-to-total asset ratio has a negative, insignificant impact. The coefficient of determination indicates that the share price growth of banks is more dependent on other factors which are not included in the regression analysis of this study. Conclusion This study helps investors and bankers understand the limited impact of financial parameters on banks'stock prices and to look for other parameters which explain the stock price movement better.

We test for firm-level asset investment effects in returns by examining the cross-sectional relation between firm asset growth and subsequent stock returns. Asset growth rates are strong predictors of future abnormal returns. Asset growth retains its forecasting ability even on large capitalization stocks. When we compare asset growth rates with the previously documented determinants of the cross-section of returns (i.e., book-to-market ratios, firm capitalization, lagged returns, accruals, and other growth measures), we find that a firm's annual asset growth rate emerges as an economically and statistically significant predictor of the cross-section of U.S. stock returns.

This paper examines the significance and robustness of four measures of growth of the firm with respect to firm-level Total Factor Productivity (hereinafter TFP). These four measures are (a) growth of total assets, (b) growth of sales, (c) growth of fixed assets, and (d) weighted growth of fixed assets. The four measures are examined in the business and economics literature in different contexts. The results of related studies do not include a consensus regarding the validity of a certain measure. The ultimate objective of this paper is to present a realistic view of growth of the firm.The data used in this paper represent the non-financial firms listed on DJIA30 and NASDAQ100. These data were obtained from Reuters Finance database© (https://www.reuters.com/markets/) and cover the quarterly periods from June 1992 till March 2018The results of the robustness test show that (a) firm-level TFP is positively associated with weighted growth of fixed assets, (b) the estimates of weighted growth of fixed assets are robust which is an indication to the intrinsic relationship with firm-level TFP, (c) the significance of weighted growth of fixed assets varies across industries which reflects an industry effect. This paper contributes to the related literature by examining the robustness of the common measures of growth of the firm. As far as growth of the firm and size are exchangeable, the lack of conformity in the literature raises a controversy regarding the search for a reliable measure of size and growth of the firm.

Company value plays a significant role in investment decisions, company performance assessment, and risk analysis. In addition, there is uncertainty or inconsistency in the relationship between factors such as sales, assets, and leverage that can affect company value. The study aims to analyze the effect of sales growth, asset growth, and leverage on company value in companies listed on the Indonesia Stock Exchange, especially in the LQ-45 index during the 2021–2022 period. The research method uses a quantitative approach with statistical tools and hypothesis testing. Regression analysis through path analysis models is used to test the proposed hypothesis. The results showed asset growth of 15.42%, debt-equity ratio of 1.7797, and high Price to Book Value (36.2721). Nonetheless, leverage does not act as a mediator in the relationship between asset growth and company value, defying the Modigliani-Miller theory. The finding highlights the complexity of such factors in the context of LQ-45 companies, emphasizing the need for prudent asset management and debt policy to enhance competitiveness. The findings have important implications for financial management and business strategy in a dynamic and competitive environment.

The purpose of this study is to present a literature review of market microstructure research to identify the impacts of investment decision and asset growth. It seeks to come up with a conceptual framework related to market microstructure that can promote sustainable investment practices and long-term asset growth towards economic prosperity. An infometric analysis has been conducted based on data extracted from Scopus using VosViewer to generate themes from the literature. Furthermore, a lexicometric analysis is undertaken using an open-source software named Iramuteq to analyze the overall structure of the textual corpus analyzed through infometric analysis. The most important contribution of this research is a comprehensive conceptual framework with a focus on the importance of financial literacy to affect sustainable investment decisions via market microstructure. In addition, the framework posits sustainable investment and investment channels as moderating variables. The study provides a conceptual framework with future direction and scope to work on. In addition, the study is inclusive of unexplored research themes on which future studies can be based. It acts as a base for examining the interplay of market microstructure in shaping informed and sustainable investment decision-making. The study provides a thorough review of the existing body of literature through infometric and lexicometric analysis. Followed by this, the research develops a novel conceptual framework linking market microstructure with investment decision, asset growth and financial literacy.

This study examines whether the growing disparity in labor productivity between firms in Canada is associated with the ability of these firms to grow in the Canadian economy. Using Canada’s Corporate Tax Statistics Universal File, we identify an inverted U-shaped relationship between labor productivity and fixed-asset growth rates, which subsequently results in a negative association between growing dispersion and lower growth rates. Econometric analyses reveal that a 1% increase in productivity dispersion leads to a 0.06 percentage point reduction in industry-level growth rates. We consider Schumpeterian and other evolutionary approaches for explaining this phenomenon and propose a simple population dynamics model.

PurposeIn today's competitive business environment, understanding how leadership traits shape outcomes is critical. Chief executive officer (CEO) narcissism, an intriguing and debated trait, raises questions about its impact on organisational behaviour, particularly regarding entrepreneurial orientation (EO). This study aims to examine how CEO narcissism affects EO, both as aggregate and specific measures, encompassing internal and external growth. It also considers the organisational context by examining how factors such as capital intensity, firm ownership and CEO duality moderate this relationship.Design/methodology/approachTo test the hypotheses, the authors used a sample of firms drawn from China's ChiNext database (2008–2017). After an initial screening, the final sample consists of 251 CEOs from 239 companies. Data on CEO narcissism are collected from the firm's official website and major online sources, whilst additional data are extracted from the WIND daabase. The authors use multiple regression and ordinary least squares (OLS) for data analysis.FindingsThe results show that CEO narcissism leads to external asset growth investments but not internal research and development (R&D). There is a positive relationship between CEO narcissism and EO as an aggregate measure and also different managerial discretions play varying roles in the relationship. Specifically, capital intensity weakens this relationship, but state ownership strengthens it.Originality/valueThis study helps to clarify the relationship between CEO narcissism and EO and advances the literature by showing that firms' EO actions may take various forms of innovation and venturing as new entry initiations of EO. The study findings have important implications for firms to capitalise on narcissistic CEOs' entrepreneurial tendencies, balance internal R&D and external asset growth and leverage various managerial discretions.

Our research addresses the gap in investigating how political connections and financial constraints affect asset growth anomalies before and during the Covid-19 pandemic. Our sample includes listed non-financial firms in the Vietnam stock market from 2008 to December 2020. We employ Fama and MacBeth regressions and portfolio sorting methodology to analyze a sample with 34,441 monthly observations, including 478 firms. Our findings indicate a negative relationship between asset growth and subsequent stock returns in all periods. While the asset growth anomaly existed in the Vietnam stock market before the pandemic, it disappeared during the pandemic. The average raw return difference between stocks in the highest and lowest asset growth terciles was −0.26% per month before the pandemic. Our robustness tests show that asset growth anomaly exists in firms with political connections during the pandemic. In addition, the asset growth anomaly only persists in larger firms before the pandemic. Our findings support agency and pecking order theory, behavior, and rational explanations. Finally, this study contributes practical implications for managers and individual investors to prevent adverse impacts of asset growth anomalies.

Order backlog is an important non-GAAP metric that is a leading indicator of future earnings. We explore how various fundamental analysis metrics interacted with order backlog impacts future earnings. This study examines whether future earnings predicted by order backlog is contingent on other fundamental analysis metrics, such as a sales decrease, the cash conversion cycle, asset growth, and the ratio of order backlog to sales. We find that order backlog is an even more informative leading indicator of future earnings when sales decrease, the cash conversion cycle is longer, and asset growth is higher. In contrast, we find that order backlog in the presence of a higher order backlog to sales ratio predicts lower future earnings. We also find that market participants incorporate the moderating effect of order backlog on sales decreases and the cash conversion cycle, while we do not find the same evidence with asset growth and the backlog to sales ratio. These empirical findings are important for managers who want to effectively communicate the prospects of a firm’s future profitability, and for investors who want to understand the financial fundamentals of firms with an order backlog. Overall, our findings show that the informativeness of order backlog can be conditional on fundamental analysis metrics in certain instances.

We evaluate and compare the performance of four popular factor pricing models: the capital asset pricing model, the Fama and French three-factor model, Carhart's four-factor model, and the five-factor model of Fama and French. We aim to establish which of these models is most applicable in the Polish stock market. To do so, we employ a battery of tests-cross-sectional regressions, examination of one-way and two-way sorted portfolios, tests of monotonic relationships, and factor redundancy tests-and apply them to a sample of more than 1100 stocks for the years 2000-2018. The results indicate that the four-factor model outperforms the other models; it has the greatest explanatory ability for cross-sectional returns and is therefore well-suited for asset pricing in Poland.