Monte Carlo Methode in Finance Kurs für Forex TraderZuletzt aktualisiert & geprüft: 28.03.2019
Interessanter Kurs – sehr sehenswert!
Non-bankers can learn to understand the mathematical models that have made the headlines so many times in recent years. A course for students of economics, business studies, mathematics, physics and computer science.
Über den Kurs
Learn how to measure the risk of an investment portfolio!
In this course you will simulate the time evolution of prices of financial assets, use the Black-Scholes model to price European or Asian options and compute the Value-at-Risk of a portfolio. The approach is hands-on with a strong emphasis on practical simulations that you will program, run and explore in your own computer.
„Monte Carlo Methods in Finance“ will be offered on iversity, starting 20 January 2014.
The course is structured in 9 one or two-week chapters
Chapter 1: Introduction
Chapter 2: Understanding random numbers
Chapter 3: Generating random numbers
Chapter 4: Brownian motion
Chapter 5: Ordinary differential equations
Chapter 6: Stochastic differential equations
Chapter 7: Pricing of simple derivative products
Chapter 8: Pricing of more complex derivative products
Chapter 9: Modeling and quantifying financial risk
Chapters are divided into units. Each unit consists of a video followed by a multiple choice question. At the end of each chapter, you will solve and turn in some homework exercises. These exercises will be evaluated by peer grading.
Some of the explanations in the videos and the exercises make reference to short programs that you can download and execute in your own computer. You are encouraged to experiment with these programs (modify the values of parameters, complete or rewrite the code to alter the model or to implement related functionality) and run your own simulations. The code provided can be executed in either GNU Octave or MATLAB.
At the end of this course you will know how to answer the following questions:
- Why are random numbers needed in quantitative finance? And, if they are random, how can they be used to give precise, accurate answers to quantitative financial problems?
- What is the Black-Scholes model and how can it be used to simulate the evolution of asset prices in financial markets?
- How are Monte Carlo methods used to determine the right price of a derivative product, such as a European call option?
- What is the theory of copulas and how can it be used to model general dependencies among financial assets?
- How is financial risk modeled, characterized and quantified?
You will need between 5 and 8 hours of work per week during a total of 12 weeks to complete all the learning activities, including the homework.
The course is geared to students not only in economics and finance, but also in mathematics, computer science, engineering, physics and the natural sciences.
No knowledge of finance is required.
Basic knowledge of Calculus (integration and differentiation, Taylor series), Linear Algebra (matrices, determinants, eigenvalues and eigenvectors) and Probability (random variables, probability density and cumulative distribution functions) at an introductory undergraduate level is strongly recommended.
Programming knowledge is recommended. We will be designing simulations that can be executed in either GNU Octave or in Matlab. The programs will be short, intuitive, fully documented and easy to follow. Yet they will be powerful tools under your control, and will allow you to explore, experiment and learn at your own initiative.
The course is scheduled to start on 20 January 2014. There will be a short break for Easter.
The course will be taught in English.
Eine stetige Weiterbildung ist einer der wichtigsten Punkte beim Trading und sollte daher nie aus den Augen verloren werden. Nur so können Trader auf dem aktuellen Stand bleiben und ihre Strategien dauerhaft verbessern.