The purpose of this study is to analyse the relationship between financial constraint factors that can affect the chosen of leasing for the firm in Malaysia. The sample of data consist of 1150 firms including listed firm, unlisted firm and SMEs with the total number of firm-years observation are 8339. This study cover 7 years period from year 2007 until 2014. The dependent variable are lease ratio and debt ratio while the independent variable are the financial constraint determinant such as internal funds, growth, collateral, and size. This study also include control variables such as uniqueness (R&D expenses), tax loss and macroeconomics factor such as based lending rates (BLR). The results indicate that not all financial constraint firm tend to used lease financing compare to debt financing. It depends on what types of financial constraint that the firm face. For this analysis, the firm that have financial constraint in internal funds, collateral and size tend to used lease compare to debt financing. However, for the firms have less growth opportunities, it is difficult for them to choose either lease or debt financing because of their future survival.

Ridge regression (RR)estimator has been introduced as an alternative to the ordinary least squares estimator (OLS) in the presence of multicollinearity. In the ridge regression analysis, the estimation of ridge parameter k is an important problem. Several algorithms for the ridge parameter have been proposed in the literature. In this paper, a new method for estimating ridge parameter is suggested to solve multicollinearity problem. The investigation of the performance of the proposed estimator has been carried out using Monte Carlo simulations. The results indicate that under certain conditions, the proposed estimator performs better than other well-known estimators.

Small medium-sized enterprises (SMEs) are known to contribute to any countries’ economic growth. To ensure their survival in a competitive market, SMEs need to have the ability to innovate and develop new products. Prompt decisions making therefore needed to innovate and produce new products to reach market first before their competitors. However, due to their size as well as financial and human resources constraints, SMEs face obstacles and huge challenges. Therefore, one of the major aspects of developing a successful new product is managing risks. Risk can have either a positive or negative impact on new product performance. It is crucial for companies to manage risks in order to achieve the desired new product development (NPD) performance without compromising quality. Therefore, this study aims to identify the influence of risk on NPD performance in SMEs. Four main types of risk may affect NPD performance: technology, market, operational and financial risks are discuss pertaining to NPD performance.

This paper attempts to introduce an appropriate model for modeling and forecasting the total value of traded securities on the Arab Republic of Egypt ,the long memory of series was investigated and fitted a fractionally integrated autoregressive moving-average (ARFIMA) model using 2649 daily data (from March 01, 2004 to June 29,2015). The paper shows the efficiency of the different methods used to estimate fractional parameter in the ARFIMA model, estimates were obtained by semi-parametric and parametric methods. The results indicate that the semi-parametric methods, specially Local Whittle method, outperformed the parametric method when elements of AR or MA components are involved. The forecasting ability of the method was compared to the traditional ARIMA model, with ARFIMA proving to be the better of the two.