The paper "Current trends in Matrix Analysis and its Application to Financial Planning" is a worthy example of a math assignment. Matrix analysis refers to the use of different algebraic, mathematical, statistical and mechanical techniques in order to make fundamental analyses such as future forecasting, business planning, etc. It is extensively used in business operations and different financial institutions (J. P. Bouchaud). A restricted dimensional vector space is the fundamental requirement of matrix analysis (Roger A. Horn). Vector space basically indicates that a complete set of vectors is enclosed in a binary field which subsequently helps in binary operations (Matrix Algebra and Applications).
Currently, financial planning, implementation, and forecasting are done on the basis of different statistical tools and techniques including matrix analysis (Alice C.. Lee). Different trends and approaches of matrix analysis are widely available however, their perfect application and implementation are associated with the experience and intellect of financial managers. Managers use matrix analysis to make wealth creation policies, health, and care benefits, strategic management, implementation of marketing strategies, debt calculation, and reduction, etc (Matrix Planning Solutions). This paper aims to discuss contemporary approaches of matrix analysis and its application to financial planning.
The primary focus is over the Random Matrix Theory, econometric models, risk estimation, portfolio optimization, interactive multiple goal programming and scalar multiplication (J. P. Bouchaud). All of these financial operations use the basic components of matrix analysis, for instance, consider the interactive multiple goals programming which is extensively required in order to make realistic financial plans and forecasting of future revenues and expenses (Steven D.. Eppinger).