Impact of Capital Structure and Dividend Policy on Firm Value

The study aimed to investigate the impact of capital structure and dividend policy on firm value of KSE non financial listed firms using cross sectional time series regression analysis for the period 2006-2013 in Pakistan. The study uses fixed effect Model to measure the disparities of intercepts for each group considering fixed coefficient for independent variables and fixed variance among groups of the panel data. The results of the study reporting number of variables of capital structure and dividend policy has significant impact on dependent variable (tobin’s Q). Three independent variables (TDTA as leverage ratio, SG as profit sustainability ratio and EQ as shareholders equity) of capital structure, while one independent variable (EPS as profitability ratio) of dividend policy has significant impact on dependent variable (tobin’s Q). The left behind two variables (FATO as performance ratio of capital structure and DPO as cash flow indicator ratio of dividend policy) are not significant with depended variable (tobin’s Q). Elaborately; EPS approve the prophecy of signaling theory while EQ, TDTA and SG statistically confirm assumptions of trade off theory and pecking order theory. Furthermore FATO fail to support the trade off hypothesis while DPO fail to favor the signaling theory postulations. Consequently our research analysis approves the hypothesis of pecking order theory and trade off theory in case of capital structure and signaling theory in case of dividend policy. Keywords: Capital Structure, Dividend Policy, Firm Valu

A Robust Continuous Time Fixed Lag Smoother for Nonlinear Uncertain Systems

This paper presents a robust fixed lag smoother for a class of nonlinear uncertain systems. A unified scheme, which combines a nonlinear robust estimator with a stable fixed lag smoother, is presented to improve the error covariance of the estimation. The robust fixed lag smoother is based on the use of Integral Quadratic Constraints and minimax LQG control. The state estimator uses a copy of the system nonlinearity in the estimator and combines an approximate model of the delayed states to produce a smoothed signal. In order to see the effectiveness of the method, it is applied to a quantum optical phase estimation problem. Results show significant improvement in the error covariance of the estimator using fixed lag smoother in the presence of nonlinear uncertainty.Comment: 8 pages, will be presented in 52nd Conference on Decision and Contro