|Course Code and Name: SEEM4730/ ESTR4508 Statistics Modeling and Analysis in Financial Engineering|
This course studies statistical methods and models for financial engineering applications. Emphasis will be put on basic statistical techniques such as sample estimates, univariate distribution fitting, hypotheis tests and bootstrap, as well as regression and time series models. The course also teaches students how to use the statistical software R for data analysis.
After completing the course, you should be able to understand and apply the following statistical models and methods for financial engineering applications:
* some basic statistical techniques, such as sample estimates, univariate distribution fitting, hypothesis tests and bootstrap;
* regression models;
* time series models;
* principal component analysis.
Students should also be able to use the software R to analyze data using the statistical models in this course.
(P1) The ability to apply knowledge of mathematics, science, and engineering appropriate to the degree discipline (K/S)
(P2) The ability to design and conduct experiments, as well as to analyze and interpret data (K/S)
(P3) The ability to design a system, component, or process to meet desired needs within realistic constraints, such as economic, environmental, social, political, ethical, health and safety, manufacturability and sustainability (K/S)
(P4) The ability to function in multi-disciplinary teams (S/V)
(P5) The ability to identify, formulate, and solve engineering problems (K/S)
(P6) The understanding of professional and ethical responsibility (V)
(P7) The ability to communicate effectively (S)
(P8) The ability to understand the impact of engineering solutions in a global and societal context, especially the importance of health, safety and environmental considerations to both workers and the general public (V)
(P9) The ability to recognize the need for, and to engage in life-long learning (V)
(P10) The ability to stay abreast of contemporary issues (S/V)
(P11) The ability to use the techniques, skills, and modern engineering tools necessary for engineering practice appropriate to the degree discipline (K/S)
(P12) The ability to use the computer/IT tools relevant to the discipline along with an understanding of their processes and limitations (K/S/V)
(P13) The ability to apply the skills relevant to the discipline of operations research and information technology and their applications in engineering and managerial decision making, especially in financial services, logistics and supply chain management, business information systems, and service engineering and management (K/S)
K = Knowledge outcomes
S = Skills outcomes
V = Values and attitude outcomes