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雷达卡
金融理论与机器学习方法在金融系统工程建模与控制
（英文课程材料，可编辑的pdf电子文档）
Textbook:State-Space Approaches for Modelling and Control in Financial Engineering: Systems theory and machine learning methods
Author(s): Gerasimos G. Rigatos
Course Description:
This course conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary differential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial differential 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 financial engineers in decision making.
The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance 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 financial systems to be established.
Covering the following key areas of financial engineering: (i) control and stabilization of financial 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 financial engineering. It is also a useful resource for the engineering and computer science community
Modelling and Control in Financial Engineering_ Systems theory and machine learn.pdf
(12.82 MB, 需要: RMB 19 元)
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