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Numerical Methods (SFI)

Descrizione

Prerequisites
Programming for Finance I, II, Statistics, Financial Econometrics

Objectives
This course develops basic numerical quantitative methods. We put emphasis on understanding the theoretical underpinnings, but in particular also the numerical implementation. Common problems encountered in economics and finance will serve as our exercise basis. After having taken the course, students will be able to identify and implement solutions to many applied problems in R.

Description / Program
The course is structured along the following topics.

  • Basic concepts in mathematics: vector spaces and convexity
  • Interpolation – Extrapolation
  • Finite differences
  • Numeric integration, in particular
  • Monte Carlo Simulation
  • Ordinary differential equations
  • Fourier series and the (inverse) Fourier transform
  • Fast Fourier transform

Learning Method / Style of Lessons
Our classes will be split into a theory part, which explains the concepts, and a practice part, where we will apply the theory to commonly encountered problems.

Exam Style
There will be a final exam, taken at the computer, which accounts for 100% of the final grade.

Requested Material
All material will be provided.

Readings/Textbooks
We will be following closely Numerical Methods in C, which can be consulted voluntarily. All material will be developed and presented during the class and uploaded to icorsi.

Persone

 

Schneider P.

Docente titolare del corso

Zurowski W.

Assistente

Informazioni aggiuntive

Semestre
Primaverile
Anno accademico
2018-2019
ECTS
6
Lingua
Inglese
Offerta formativa
Bachelor of Arts in Scienze economiche, Corso di specializzazione, Metodi quantitativi, 3° anno

Master of Science in Economics in Banking and Finance (until A.Y. 2017), Corso a scelta, Corso a scelta, 2° anno

Master of Science in Economics in Finance, Corso obbligatorio, Minor in Quantitative Finance, 1° anno

Master of Science in Economics in Finance (until A.Y. 2017), Corso a scelta, Corso a scelta, 2° anno