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Quantitative Finance (Done)

The course provides coverage of important topics in modern Quantitative Finance and Risk Management at the advanced graduate level. It is intended for the second year graduate students of Finance, Particular attention is given to the topics such as the Efficient Market Hypothesis, financial markets micro-structure and types of arbitrage, general principles of modelling the price dynamics of financial assets, market risk and other types of financial risks, Value-at-Risk (VaR) approach and applications, modelling of extreme market events, VaR analysis for financial derivatives using the Kolmogorov equations framework, foundations of the copula methods, modelling of periodic and quasi-periodic trends in time series in connection with technical analysis, and the foundations of high-frequency arbitrage trading. The topics covered in this course will enable the students to develop the theoretical knowledge and practical skills required for successful working with multiple types of risks in modern financial markets.

 

Teaching objectives
The goal of this course is to give students insights in the functioning of financial markets, understanding of measuring and forecasting financial risks. This course is aimed at giving students instruments required in order to analyze issues in asset pricing and market finance. After the course students should be familiar with recent empirical findings based on financial econometric models, have a good command of basic econometric techniques and understand practical issues in the forecasting of key financial market variables.

 

Main Reading:

  1. Patton, A. (2007). Quantitative Finance, UoL Study Guide. (AP)
  2.  Wilmott, P. Paul Wilmott on Quantitative Finance (selected chapters). 2nd ed. Wiley, 2006.
  3.  Enders W. Applied Econometric Time Series. 2nd ed., John Wiley & Sons, Inc., 2004 (WE)
  4.  Hamilton, J. (1994), Time Series Analysis, Princeton University Press, Princeton

 

Course outline:

  • Basic time series concepts
  • Modelling asset return volatility: introduction
  • Modelling asset return volatility: extensions
  • Evaluating forecasts of risks and returns
  • The efficient market hypothesis and market predictability
  • Risk management and Value-at-Risk: models
  • Risk management and Value-at-Risk: backtesting
  • Modelling high frequency financial data

 

 

 

Prerequisites: 

The prerequisites for the course are Elements of Econometrics and Microeconomics. Good command of methods of calculus, general probability theory and mathematical statistics are also required for the course. Ofcourse, a good knowledge of C++ or MATLAB is an asset in this course.

Grading Policy: 

Homeworks and Projects -------------------- %50

Final Exam --------------------------------------- %50

Teacher Assistants: 

N/A

Time: 

Saturday and Monday 10:00  to 12:00

Class 3 in Mathematical Building

Term: 
DONE
Grade: 
Graduate

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