The impact of ownership structure on corporate debt policy : two stage least square simultaneous model approach for post crisis period : evidence from Kuala Lumpur Stock Exchange

Ownership concentration as a governance mechanism has received considerable attention among academician, practitioners as well as policy makers because large-block shareholders are increasingly active in their demands that corporations adopt effective governance mechanisms to control managerial decisions, which include corporate debt policy. Earlier study on the agency model of the firm widely recognizes that the managerial ownership and external debt play an important role in mitigating agency conflicts and enhancing firm value. They also found that increase in the external monitors, for example the institutional investors, can actually play a useful role in limiting agency problems in the firm. This paper, using 100 Composite Index companies from Brusa Malaysia between 1998 to 2002 explores the impact of institutional holdings on managerial ownership and debt policy in an integrated framework by using a simultaneous equations estimation procedure (2SLS). The findings show that there is a significant impact of institutional ownership which serves effective control mechanism on managerial ownership and corporate debt policy as hypothesized. Findings of such evidence suggest that institutional holding thus have played an important role in managers' strategic management decision and reduce agency conflict. In addition, corporate debt policy too is governed by managerial ownership and exhibited a negative relation.

Simultaneous volatility transmission and spillover effects

Simultaneous volatility models are developed and shown to be separate from multivariate GARCH estimators. An example is provided that allows for simultaneous and unidirectional volatility and volume of trade effects. These effects are tested using intraday data from the Australian cash index and index futures markets. Overnight volatility spillover effects from the United States S&P500 index futures markets are tested using alternative estimates of this US market volatility. The simultaneous volatility model proves to be robust to alternative specifications of returns equations and to misspecification of the direction of volatility causality.

Convergence of object focused simultaneous estimation of optical flow and state dynamics

The purpose of this study is to prove the convergence of the simultaneous estimation of the optical flow and object state (SEOS) method. The SEOS method utilizes dynamic object parameter information when calculating optical flow in tracking a moving object within a video stream. Optical flow estimation for the SEOS method requires the minimization of an error function containing the object's physical parameter data. When this function is discretized, the Euler-Lagrange equations form a system of linear equations. The system is arranged such that its property matrix is positive definite symmetric, proving the convergence of the Gauss-Seidel iterative methods. The system of linear equations produced by SEOS can alternatively be resolved by Jacobi iterative schemes. The positive definite symmetric property is not sufficient for Jacobi convergence. The convergence of SEOS for a block diagonal Jacobi is proved by analysing the Euclidean norm of the Jacobi matrix. In this paper, we also investigate the use of SEOS for tracking individual objects within a video sequence. The illustrations provided show the effectiveness of SEOS for localizing objects within a video sequence and generating optical flow results.