The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in ï¬nancial systems when these are described in the form of nonlinear ordinary diï¬erential equations. It then addresses problems associated with the control and estimation of ï¬nancial systems governed by partial diï¬erential equations (e.g. the Black-Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support ï¬nancial engineers in decision making.The application of state-space models in ï¬nancial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for ï¬nance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of ï¬nancial systems to be established.Coveringthe following key areas of ï¬nancial engineering: (i) control and stabilization of ï¬nancial systems dynamics, (ii) state estimation and forecasting, and (iii) statistical validation of decision-making tools, the book can be used for teaching undergraduate or postgraduate courses in ï¬nancial engineering. It is also a useful resource for the engineering and computer science community
