Insegnamento a.a. 2018-2019

20247 - APPLIED NUMERICAL FINANCE

Department of Finance

Course taught in English
Go to class group/s: 31
CLELI (6 credits - I sem. - OP  |  SECS-S/06)
Course Director:
ANNA BATTAUZ

Classes: 31 (I sem.)
Instructors:
Class 31: ANNA BATTAUZ


Prerequisites

Intermediate skills of calculus, probability and algebra and basic skills of derivatives valuation.

Mission & Content Summary

MISSION

The course provides the essential tools to understand and solve core computational issues in financial engineering. In particular, we deal with the valuation of American and exotic derivatives that do not admit closed form prices, and that are widely traded in the markets. We analyze derivatives on discontinuous underlying assets, focusing on the jump-diffusion model, to gain insights on the main features of asset prices with jumps. Monte Carlo methods are then applied to price and hedge derivatives. We provide techniques to improve the efficiency and the accuracy of the Monte Carlo estimate of derivatives prices and sensitivities. Students are introduced to VBA (Visual Basic for Applications) and are tutored in the VBA implementation of the algorithms in the lab sessions. However VBA is not mandatory: students proficient with MatLab, R or Python (or other programming languages) are allowed to use their preferred language instead of VBA for the assignment.

CONTENT SUMMARY

  • Valuation and replication of American and path-dependent options via lattice methods.
  • Valuation and replication of basket options in a multidimensional diffusive framework. Currency markets and quanto options.
  • Valuation of European options in the jump-diffusion model.
  • Monte Carlo methods in financial engeneering: efficiency and bias. Simulation of asset prices. Derivatives valuation. Variance reduction techniques. Valuation of the Greeks.
  • Introduction to VBA: routines, functions, plots, arrays, user forms.

Intended Learning Outcomes (ILO)

KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...
  • Select the proper techniques to address path-dependency and American exercise features of financial derivatives.
  • Implement multivariate diffusive models to account for the covariance structure among financial assets;  price and hedge basket derivative securities.
  • Use jump diffusive models for financial assets and price by no-arbitrage European derivatives on these underlyings.
  • Master Monte Carlo methods to simulate asset prices, evaluate derivatives and their greeks, enhance the accuracy of the estimate.

APPLYING KNOWLEDGE AND UNDERSTANDING

At the end of the course student will be able to...

Solve core computational issues in financial engeneering as:

  • Price and replicate path-dependent and American options with trees.
  • Evaluate multiasset derivatives via Monte Carlo methods.
  • Enhance the accuracy of their Monte Carlo estimate via suitable variance reduction techniques.
  • Compute Greeks with various Monte Carlo methods.
  • Deal with algorithms in VBA.
  • Prepare an executive report on one of the aformentioned topics.

Teaching methods

  • Face-to-face lectures
  • Exercises (exercises, database, software etc.)

DETAILS

Theory topics are explained in face-to-face lectures. Students are introduced to VBA (Visual Basic for Applications) and tutored in the implementation of the alghorithms in the lab session. However VBA is not mandatory: students proficient with Python, R or MatLab are allowed to use their preferred language instead of VBA for the assignment.


Assessment methods

  Continuous assessment Partial exams General exam
  • Written individual exam (traditional/online)
    x
  • Individual assignment (report, exercise, presentation, project work etc.)
    x
  • Group assignment (report, exercise, presentation, project work etc.)
    x

ATTENDING AND NOT ATTENDING STUDENTS

The assessment consists of a brief written individual exam and an assignment.

The brief written individual exam counts 70% and consists of open questions on the main arguments of the classes.

  • The written exam verifies students have acquired the necessary knowledge of the theory topics.

The assignment counts 30% and consists in writing a code to solve a selected problem as, for example, the evaluation of a particular path-dependent option, and a brief report on the related numerical/financial issues. Students can choose to code with VBA or any other preferred language (e.g. Python, R, MatLab). The list of assignment titles and instructions are provided during the course. The assignment can be done in groups or individually, and is due the same day of the written exam. The assignment grade is valid until the end of the academic year.

  • The assignment allows students to deepen their knowledge on the specific selected topic, by writing a code, analyzing the numerical and financial critical issues, and by preparing a report.

Teaching materials


ATTENDING AND NOT ATTENDING STUDENTS

Lecture notes and slides distributed by the instructors via Bboard.

Last change 05/07/2018 16:09