A Model for Recognizing Key Factors and Applications Thereof to Engineering

This paper presents an approach to recognize key factors in data classification. Using collinearity diagnostics to delete the factors of repeated information and Logistic regression significant discriminant to select the factors which can effectively distinguish the two kinds of samples, this paper creates a model for recognizing key factors. The proposed model is demonstrated by using the 2044 observations in finical engineering. The experimental results demonstrate that the 13 indicators such as “marital status,” “net income of borrower,” and “Engel's coefficient” are the key factors to distinguish the good customers from the bad customers. By analyzing the experimental results, the performance of the proposed model is verified. Moreover, the proposed method is simple and easy to be implemented

Loan systems, financial ranking and fiscal positioning: Evidence from India

This paper examines the financial ranking and performance of banks by taking one bank as a sample case. We evaluate performance of bank through fiscal reserves it posses, its monetary arrangement, its liquidity and its competence to get used to transformation in the market in which it operates. The study provides some important insights about banks liquidity and its ability to change cash flows in future circumstance Keywords – Bank liquidity, financial ranking, fiscal positioning, Indi

Effects of the budgetary process on SME’s performance: An Exploratory study based on Selected SME’s in India

This research study is intended to find out the impact of budgeting on the performance of small and medium enterprises of India. Three major areas of the study are budgeting in SMEs, performance measurement in SMES and Small and Medium Enterprises. The budgeting process is explained and analyzed from the point of view of budgetary planning, budgetary sophistication and control. A sample of two hundred and sixty eight firms is selected from SME sector of India. The sample was selected from three districts of Mumbai, Pune and Solapur. Impact of budgeting on firm performance in these firms was tested through detailed analysis. Questionnaires and other statistical tools were used for analysis of the problem statement. A positive relationship between firm performance and budgeting process is found in this research study. The performance of Small and Medium Enterprises of India is further affected by the characteristics of the budget goals. The results add to the fact that higher performance can be achieved through more clear goals. Astonishingly budget goals that are difficult but achievable motivate employees to achieve budget goals. Moreover tight but achievable goals also increase employee’s motivation in achievement of budget objectives and it improved the performance of Small and Medium Enterprises of India. Another important result is that formal and tight control mechanism of control for budgetary process also tends to increase firm performance in the SME sector of India. It was very interesting to find out that budgetary process have greater impact on the performance of the firm in SME sector as compared to the budgetary control process. Furthermore budgeting planning affects the sales growth of firms in Small and Medium Enterprises more than the budgetary control phenomena. But the impact of budgetary planning on sales becomes very weak and in turn budgetary control strongly affects the profit in small and medium enterprises. Sales and budgetary sophistication have a statistically insignificant relationship and budget sophistication relationship with profit is even negative. The sophistication of budgetary tools includes acquiring and installation of costly financial modeling software, training and expensive training and follow up mechanism. This needs a huge investment which is difficult for Small and Medium Enterprises to acquire that much huge investment. If firm goes for these huge investments this increase in their expenses will decrease their net profit value. Budgetary goal clarity has a statistically insignificant relationship with the employee’s motivation level and further the budget goal difficulty and employee’s job involvement also shows a statistically insignificant relationship. As far as the firm size is concerned it affects sales insignificantly, however it impacts profit of the firm in SMEs sector. Medium sized firms showed a greater growth in their sales as compared to the smaller sized firms. Key Words: Small and Medium Enterprises, Budgeting, Firm Performance, Budget Contro

Short- And Long-Term Value-At-Risk, Skewness, Kurtosis and Coherent Risk Measure

Standard risk management focuses on short-run risks rather than longer periods. We introduce an improved risk measure which can be used to estimate both short-and long-term structure of value at risk and the corresponding expected shortfall. The short- and long-term coherent measure of risk is specified and computed for both S&P 500, HSI and SHSZ 300. We also test long-term skewness and kurtosis from empirical analysis for S&P 500, HSI and SHSZ 300. We also show that our improved risk measure gives a better estimate of the value at risk for short horizons and never decreases to negative values like VaR for long-run horizons. Both long-term skewness and kurtosis for HSI and SHSZ 300 are analyzed empirically

Feature selection in credit risk modeling: an international evidence

This paper aims to discover a suitable combination of contemporary feature selection techniques and robust prediction classifiers. As such, to examine the impact of the feature selection method on classifier performance, we use two Chinese and three other real-world credit scoring datasets. The utilized feature selection methods are the least absolute shrinkage and selection operator (LASSO), multivariate adaptive regression splines (MARS). In contrast, the examined classifiers are the classification and regression trees (CART), logistic regression (LR), artificial neural network (ANN), and support vector machines (SVM). Empirical findings confirm that LASSO’s feature selection method, followed by robust classifier SVM, demonstrates remarkable improvement and outperforms other competitive classifiers. Moreover, ANN also offers improved accuracy with feature selection methods; LR only can improve classification efficiency through performing feature selection via LASSO. Nonetheless, CART does not provide any indication of improvement in any combination. The proposed credit scoring modeling strategy may use to develop policy, progressive ideas, operational guidelines for effective credit risk management of lending, and other financial institutions. The finding of this study has practical value, as to date, there is no consensus about the combination of feature selection method and prediction classifiers

Impact of early COVID-19 pandemic on the US and European stock markets and volatility forecasting

This study examines the impact of early COVID-19 pandemic on U.S. and European stock indices, implied volatility (IV) indices, and forecasting accuracy of IV indices from daily data of January 2012 to December 2020, using an out-of-sample assessment of COVID19. Our results show that COVID-19 death and recovery cases have had a significant positive impact on S&P 500, DJIA and NASDAQ 100. On the other hand, VIX, VXD and VXN show a negative association. Again, we also observe the significant impact of COVID-19 on stock trading prices and volatility expectations. Furthermore, the evidence of the point forecasts is more reliable for European IV indices than for U.S. IV indices. Finally, this study validates the informational efficiency of IV indices on the financial markets and has implications for investors regarding portfolio management and investment risk minimisation in similar future pandemic situations