The purpose of this paper is to predict the banking sector index using financial ratios, and compare the capability of financial ratios for Islamic banks and financial ratios for non-Islamic Banks to predict the banking sector index in Amman Stock Exchange. The study used yearly data of three Islamic banks and thirteen non-Islamic banks during the period between 2005 and 2017. Ordinary least square method (OLS) has been utilized using seven financial ratios to predict the banking sector index. The findings revealed that the financial ratios can predict the banking sector index in Amman Stock Exchange. Mainly, the equity ratio (ER), debt (DR), and stock turnover (STR) of Islamic banks can predict of the banking sector index in Amman Stock Exchange. The quick ratio (QR), return on equity (ROE), return on assets (ROA), and market book value (MBR) of Islamic banks does not predict the banking sector index. In contrast, debt ratio (DR), stock turnover (STR), return on equity (ROE), return on assets (ROA), and price to book value (MBR) of non-Islamic banks can predict of the banking sector index. The equity ratio (ER) and a quick ratio (QR) of non-Islamic banks do not predict the banking sector index. Nevertheless, the findings also revealed that stock turnover ratio can predict of the banking sector index in Amman Stock Exchange for both Islamic and non-Islamic banks.

The purpose of this paper is to identify the dimensions affecting the performance of companies. The systematic literature Review was conducted in four databases; Scopus, ProQuest Central, Ebscohost and Google Scholar, from 2008 to 2018. The study has identified 10 dimensions toward company's performance. The main dimensions found are management, human resources, company’s characteristics, supply chain, intellectual capital, and technology, corporate’ governance, board of directors, financial analysis, and Z-score (MDA).

Analysts in business companies face challenges to determine factors affecting company's performance. Accounting and market indicators are one of the significant factors that necessary to verify its impact on the company's performance continuously. In addition, the scaling rate of volatility indicates larger moves and changes in the asset’s value. An asset with higher volatility is likely to make a large move up as it does down. This condition would also create a noticeable impact on performance. Therefore, the study proposes a conceptual framework to test the accounting and market indicators towards company’s performance and the mediating effects of stock volatility on its relationships, by a review of existing studies and theories. The panel data of companies using regression models, multiple discriminant analysis, and structural equation modelling had supposed as a suitable analysis to accomplish the study objectives. The model fit will be confirmed after the collection of the research data and analysis. This study is important as it offers potential investors a better understanding of the factors affecting the company's performance. Further, investors will be able to appropriately decisions their investments and identify relevant factors that affect performance. The study is expected that profitability analysis, credit risk analysis, valuation analysis and market capitalization are a significant factor could directly affect the company’s performance, could discriminate between companies’ performance, and the stock volatility has a mediating impact on its relationships with the company’s performance.

The efficient market hypothesis theorizes that current stock prices and returns reflect all relevant information. Stock prices and returns only change upon the emergence of new information. Firms must provide information to help investors make investment decisions. The concerns of owners, investors, business partners, stakeholders, and creditors about the financial position of a company calls for appropriate performance measurement tools (i.e., discriminate between investment opportunities and effect of stock volatility). Most often, they rely on publicly available accounting and market indicators. There is also a lack of financial analysis techniques on financial indicators that can discriminate between performing and underperforming companies. The extant literature is inconclusive about the impacts of accounting and market indicators on stock price and return, likely due to its implicit assumption that they are direct. An alternative perspective, one that has met with little investigation, is that the impact may be influenced by a mediator, such as stock volatility. Against these issues, this study built on past research to: 1) investigate the impact of accounting and market indicators on stock price and return; 2) evaluate company performance and distinguish companies into performing and underperforming; and 3) investigate the mediating effect of stock volatility on relationships between accounting and market indicators and stock price and return. Therefore, investors and stakeholders can predict stock validity using indicators that reflect the performance of firms’ operating activities. Additionally, they enable policymakers and market regulators to make rational decisions to enhance investment policies. The study analyzed a panel data of 63 companies constituting the Amman Stock Exchange General Index from 2008 to 2018 using ordinary and generalized least squares regression models, multiple discriminant analysis, and structural equation modelling. The findings showed that: 1) earnings per share (EPS), return on asset (ROA), market capitalization (MC), stock turnover ratio (STR), and book value per share (BPS) significantly and positively affected stock price; 2) total asset turnover (TOA), ROA, EPS, STR, and price-to-book value (PBV) significantly and positively affected stock return; 3) STR, EPS, and TOA significantly discriminated between performing and underperforming companies; 4) stock price volatility fully and positively mediated the relationship between STR and stock price; and 5) stock return volatility fully and positively mediated the relationship between MC and STR and stock return. The results were robust, and they evinced that accounting and market indicators, which are the main references of financial information, are reflected on company performance. The results are expected to provide an informative guideline to researchers to design appropriate performance evaluation models (e.g., Z-score models and mediation models); investors to choose the best investment opportunities in ASE; and financial policymakers to improve investment policies in Jordan. Investors, especially, may refer to the findings to help them make short-term investment decisions. Academics could also adopt the novel research models to evaluate company performance while accounting for stock volatility, allowing them to identify high performing firms and rank companies by performance. Future studies may consider replicating the analysis in developed and other emerging markets.

The main purpose of this paper is to predict the banking sector index using financial ratios. The study used yearly data of fourteen banks listed in ASE, during the period between 2005 and 2017. Using ordinary least square method (OLS), seven financial ratios have been tested to predict the banking sector index. The findings revealed that the financial ratios can predict the banking sector index in ASE, and significant relationships were found between debt ratio, stock turnover, return on assets, price to book value and return on equity with the banking sector index in ASE. In contrast, the relationships between the equity ratio and quick ratio with banking sector index in ASE were not significant.