Effect of Trading Companies Share on Investors Attitude and Financial Behavior

Pakistan is under developing country and it has an unpredictable market nature of shareholder-investors observe the company’s performance. This research could help to companies in understanding financial behavior, attitude and investors’ satisfaction in stock trade. Financial behavior is comparatively new subject in Pakistan therefore; this study has examined the financial behavior and attitude of investors. The behavioral finance that has been attempt to understand the positive experiences influences investors’ financial behavior. This study has find out that investor satisfaction is strongest in influence of positive financial behavior of investor and trader in stock trading; positive experience and investors satisfaction are strengthens the investment decision of investors and increases behavior loyalty to prefer over competitor. The findings of this study has showing that investment gains results in more positive financial behavior and experience which leads investors satisfaction and preference the company over competitor. However negative financial behavior and complain induce by loss and loss also results decrease in behavior and attitudinal loyalty which leads the disappointment and regret. Purpose – The main purpose of this study is to find factors that effects the positive experiences with stock trading on investors’ and trader’s satisfaction, attitudinal loyalty and financial behavior in Pakistan. Design /methods and approach – The research framework links with experiences in stock trade for positive (negative) experiences, attitude and financial behavior is developed. The research framework is measured with data from sample of Karachi; the data is analyzed in smart PLS which is variance based structural equation modeling using partial least square path modeling, non-parametric software. Research Limitation – This study is focused on trading experience with company’s active investors and traders in banking industry in Pakistan. The future research could be research in other sectors with inter-related issue of investors and traders in stock trade. Originality/ Value – This is the first study in this research area; this study is determined the experiences with positive (negative) financial behavior, attitude and investors satisfaction of investors and traders in stock trade. Therefore adding in this area of study, which will help in understanding the investors and traders attitude and financial behavior in financial market. Keywords – Financial Behavior, Investor satisfaction and Attitudes, Traders or Brokers and Investors Behavior, Positive and negative Experience. Paper type – Research Paper DOI: 10.7176/RJFA/11-12-09 Publication date:June 30th 202

Impact of Liquidity Ratio on Profitability of Firm: An Empirical Evidence from Automobile Industry of Pakistan

Pakistan automobile industry was experiencing a boom from the last two decades, but currently it is facing footraces due to financial suffering in the Pakistan market. This study is an attempt to investigate the impact of liquidity on profitability either positively or negatively. Liquidity of a firm can be measured through different ratios e.g. current ratio, cash ratio, and quick ratio, whereas profitability or financial performance of firm can be scaled with the proxies like return on equity and return on assets. Panel data of 5 years of 12 automobile firms listed in PSX is used for the analysis. Fixed effect model and random effect model were used for empirical investigation and Hausman test was employed to choose appropriate model between fixed and random effect. Results of the analysis revealed that the liquidity (quick ratio) positively effect on profitability; return on assets (ROA). However, there is a negative relationship between liquidity (current ratio and cash ratio) with return on asset. Keywords: Profitability, Liquidity, Return on assets, quick ratio, current ratio, cash ratio financial performance. DOI: 10.7176/RJFA/10-22-16 Publication date: November 30th 201

Factors Affecting Car Financing: A Case Study of Conventional & Islamic Banks in Hyderabad Pakistan

In present market scenario where competition forces the firms to introduce new products in order to be competitive and profitable in uncertainties, financial institutions offering car financing are facing tough competition. In order to maintain their market share they offer different options for car financing for different types of customers. This study aimed to find out factors influencing car finance behavior and investigates whether religiosity play any significant role for selecting a religion oriented financial product. Theory of planed behavior was applied to assess whether religious beliefs affect the car financing decision? Primary data of 200 walk-in customers of conventional and Islamic banks (located on different sites of Hyderabad, Pakistan) were collected through non-probability (convenience) sampling. The results showed that the intention to opt for Islamic car finance is heavily influenced by religiosity.  While on the other hand perceived behavioral control strongly influences the intention to finance a car from conventional banks. This research confirmed the hypotheses where Perceived Behavioral Control (PBC) affects the intentions of customers of conventional banks while in the case of Islamic finance the hypothesis the effects of PBC on intentions of customers of Islamic Banks is rejected. Keywords: - Conventional and Islamic Banking, Customer, Religiosity Theory of Planned Behavior, Car Financing, partial least squares (PLS). DOI: 10.7176/RJFA/10-24-12 Publication date: December 31st 201

Prediction of groundwater quality index in the Gaza coastal aquifer using supervised machine learning techniques

This paper investigates the performance of five supervised machine learning algorithms, including support vector machine (SVM), logistic regression (LogR), decision tree (DT), multiple perceptron neural network (MLP-NN), and K-nearest neighbours (KNN) for predicting the water quality index (WQI) and water quality class (WQC) in the coastal aquifer of the Gaza Strip. A total of 2,448 samples of groundwater were collected from the coastal aquifer of the Gaza Strip, and various physical and chemical parameters were measured to calculate the WQI based on weight. The prediction accuracy was evaluated using five error measures. The results showed that MLP-NN outperformed other models in terms of accuracy with an R value of 0.9945–0.9948, compared with 0.9897–0.9880 for SVM, 0.9784–0.9800 for LogR, 0.9464–0.9247 for KNN, and 0.9301–0.9064 for DT. SVM classification showed that 78.32% of the study area fell under poor to unsuitable water categories, while the north part of the region had good to excellent water quality. Total dissolved solids (TDS) was the most important parameter in WQI predictions while and were the least important. MLP-NN and SVM were the most accurate models for the WQI prediction and classification in the Gaza coastal aquifer. HIGHLIGHTS Machine learning (ML) algorithms are used for predicting water quality index.; Prediction performance of LogR, DT, KNN, SVM, and MLP-NN are compared.; MLP-NN and SVM-based prediction and quality classification models performed better than other ML-developed models.; Gaza coastal aquifer is experiencing a severe deterioration in water quality, as it is currently unsafe for drinking purposes without adequate treatment.

Application of Item Response Theory (IRT)-Graded Response Model (GRM) to Entrepreneurial Ecosystem Scale

The scale of entrepreneurial ecosystems (EE) assesses the perceptions about entrepreneurial ecosystem domains, finances, capital finances, support, support professions, policies, markets, human resources, and culture. The scales are always error-prone—these scales must possess properties that enable them it to provide maximum information and validity reliability. Convenient sampling data from (n = 474) founders, co-founders, and entrepreneurs were collected. The IRT-GRM model is used to validate and test the instrument-based on polytomous scales. IRT yields discriminating power—the level of difficulty of the items of the scale. The scale consists of 48 items. The item Pol5 (4.13) was found to have the highest discriminating value (4.13), the item mar5 had the lowest discriminating value (1.57), and all items had discriminating values greater than the threshold value of 0.60. The EE Scale showed good reliability based on McDonald’s omega and Cronbach’s alpha (0.80 and 0.88). The parallel and factor analysis showed good agreement of the one-dimesnionality of the scale. The model goodness of fit statistics based on the comparative fit index (CFI) and the Tucker–Lewis index, (TLI) and the standardized root mean square residual (SRMR) showed a satisfactory level of fit; however, the root mean square error of approximation (RMSE) showed a poor fit. The item characteristic curves showed that the all item responses were properly ordered. The items of the scale showed a satisfactory level of discrimination power and level of difficulty, and it was found to have three levels of agreement about entrepreneurial ecosystem scale. It is concluded that the EE scale possesses good psychometric properties and that it is reliable and valid instrument to measure the entrepreneurial ecosystem of the given region

Application of Item Response Theory (IRT)-Graded Response Model (GRM) to Entrepreneurial Ecosystem Scale

The scale of entrepreneurial ecosystems (EE) assesses the perceptions about entrepreneurial ecosystem domains, finances, capital finances, support, support professions, policies, markets, human resources, and culture. The scales are always error-prone—these scales must possess properties that enable them it to provide maximum information and validity reliability. Convenient sampling data from (n = 474) founders, co-founders, and entrepreneurs were collected. The IRT-GRM model is used to validate and test the instrument-based on polytomous scales. IRT yields discriminating power—the level of difficulty of the items of the scale. The scale consists of 48 items. The item Pol5 (4.13) was found to have the highest discriminating value (4.13), the item mar5 had the lowest discriminating value (1.57), and all items had discriminating values greater than the threshold value of 0.60. The EE Scale showed good reliability based on McDonald’s omega and Cronbach’s alpha (0.80 and 0.88). The parallel and factor analysis showed good agreement of the one-dimesnionality of the scale. The model goodness of fit statistics based on the comparative fit index (CFI) and the Tucker–Lewis index, (TLI) and the standardized root mean square residual (SRMR) showed a satisfactory level of fit; however, the root mean square error of approximation (RMSE) showed a poor fit. The item characteristic curves showed that the all item responses were properly ordered. The items of the scale showed a satisfactory level of discrimination power and level of difficulty, and it was found to have three levels of agreement about entrepreneurial ecosystem scale. It is concluded that the EE scale possesses good psychometric properties and that it is reliable and valid instrument to measure the entrepreneurial ecosystem of the given region