STAT471 INTRODUCTION TO FINANCIAL ENGINEERING
| Course Code: | 2460471 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Statistics |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Prof.Dr. ÖZLEM İLK DAĞ |
| Offered Semester: | Fall Semesters. |
Course Objectives
This course gives insight and a comprehensive introduction to some of the most important quantitative methods and commonly used financial tools required for a thorough understanding of financial markets. Measuring the risk associated with an investment requires being aware of the properties of related statistical estimates. This course will provide these estimates and use of them in financial data along with the study of the models used for financial instruments. It intends to enable students to have access to statistical models and methods to analyze data from financial markets and arbitrage theory for pricing financial instruments and the related mathematical machinery. As a consequence, it aims the students to gain solid background information in the area of finance both for job market and research or personal use.
Course Content
This course gives insight and a comprehensive introduction to some of the most important quantitative methods and commonly used financial tools required for a thorough understanding of financial markets. Measuring the risk associated with an investment requires being aware of the properties of related statistical estimates. This course will provide these estimates and use of them in financial data along with the study of the models used for financial instruments. It intends to enable students to have access to statistical models and methods to analyze data from financial markets and arbitrage theory for pricing financial instruments and the related mathematical machinery. As a consequence, it aims the students to gain solid background information in the area of finance both for job market and research or personal use.
Course Learning Outcomes
1. Provide basic introduction to important notions: financial instruments such as options and
derivatives and related elementary methods. Cash flows, discounting and the term structure of interest rates are studied at an elementary level.
2. Learn statistical techniques and application areas in returns and there on in stock prices. Learn Statistical measures for their location, dispersion and skewness which all have
important economic interpretations, and the relevant statistical approaches to estimate them
will be carefully introduced.
3. Measuring the risk associated with for example,
Volatility and it is primarily related to the standard deviation and value-at-risk, by definition, which requires the study of quantiles and their statistical estimation.
4. Learn principle of no-arbitrage, the principle of risk-neutral pricing and the relation of
these notions to probability, calculus, particularly to an equivalent martingale. Studying them in the most elementary form or simply by examples.
5. Learn Discrete Time Processes: Binomial Trees
6. Learn Continuous Time Processes: Brownian motion, Ito Calculus, Black–Scholes pricing formula for a European call option and its statistical aspects and analysis.
Program Outcomes Matrix
| Level of Contribution | |||||
| # | Program Outcomes | 0 | 1 | 2 | 3 |
| 1 | Applying the knowledge of statistics, mathematics and computer to statistical problems and developing analytical solutions. | ✔ | |||
| 2 | Defining, modeling and solving real life problems that involve uncertainty, and interpreting results. | ✔ | |||
| 3 | To decide on the data collection technique, and apply it through experiment, observation, questionnaire or simulation. | ✔ | |||
| 4 | Analysing small and big volumes of data and interpreting results. | ✔ | |||
| 5 | Utilizing up-to-date techniques, computer hardware and software required for statistical applications; developing software programs and numerical solutions for specific problems when necessary. | ✔ | |||
| 6 | Taking part in intradisciplinary and interdisciplinary teamwork, using time efficiently, taking leadership responsibilities and being entrepreneurial. | ✔ | |||
| 7 | Taking responsibility in individual work and offering authentic solutions. | ✔ | |||
| 8 | Following contemporary developments and publications in statistical science, conducting research, being open to novelty and thinking critically. | ✔ | |||
| 9 | Efficiently communicating in Turkish and English to define and analyze statistical problems and to interpret the results. | ✔ | |||
| 10 | Having a professional and ethical sense of responsibility. | ✔ | |||
| 11 | Developing computational solutions to statistical problems that cannot be solved analytically. | ✔ | |||
| 12 | Having theoretical background and developing new theories in statistics, building relations between theoretical and practical knowledge. | ✔ | |||
| 13 | Serving the society with the expertise in the field. | ✔ | |||
0: No Contribution 1: Little Contribution 2: Partial Contribution 3: Full Contribution