93008 - Computational Finance

Course Unit Page

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Quality education

Academic Year 2021/2022

Learning outcomes

The objective of the course is to address frontier topics in computational finance and muster the computational skills needed to tackle them. At the end of the course the student will have a working experience on selecting the most appropriate model and the capability to devise, and implement the numerical tools needed for problem at hand. The student will be able to judge the quality of the results from data analysis, and she will have enough knowledge to set up benchmarks to test for the accuracy of the numerical results. The topics addressed will refer to state-of-the-art issues in pricing, risk management and numerical techniques and programming languages. The student will be exposed, and gain proficiency, in rapid prototyping languages like Python and languages better suited to achieve high computational performance, like C/C++

Course contents

1 Generating Random Variables
  1.1 Introductions
  1.2 The Distribution Function
  1.3 The Normal Distribution
    1.3.1 The meaning of (0, 1)
  1.4 How to approximate an integral
  1.5 The weak law of large numbers
  1.6 The central limit theorem
  1.7 Acceptance Rejection Method

2 The Black and Scholes Model
 2.1 Introducing Interest Rates and Dividend Yields .
 2.2 Vanilla Options. The MC approach . . . . . . . .
  2.2.1 The European Put . . . . . . . . . . . . .
  2.2.2 Analytical Computation . . . . . . . . . .
  2.2.3 The European Call . . . . . . . . . . . .
  2.2.4 The Call-Put Parity . . . . . . . . . . . .
  2.2.5 Cap and Floor Option . . . . . . . . . .
  2.2.6 Asian Option . . . . . . . . . . . . . . . .
  2.2.7 Average Strike Option . . . . . . . . . .
 2.3 Vanilla Options. The Finite Difference Approach

3 Multi Dimensional Log Normal Processes
 3.1 An Example . . . . . . . . . . . . . . . . . . .
  3.2 The evolution . . . . . . . . . . . . . . . . . .
  3.3 Generation of a multivariate Gaussian

4 Numerical Utilities
   4.1 A Crash course on Interest rate
      4.1.1 Modeling the discount curve
  4.2 Building a discount curve
     4.2.1 Starting from the data
     4.2.2 Yearly compounded interest rates
   4.3 The Volatility Surface

5 The CIR model
   5.1 Introduction
   5.2 Numerical CIR for poets
  5.3 A helpful result . . . . . .

6 The Hull+White model
  6.1 The 1-factor Hull-White model
  6.2 The Gaussian HW Model
     6.2.1 Solution of the Gaussian HW Model
     6.2.2 The unbiased evolution algorithm
     6.2.3 The Distribution Parameters
     6.2.4 The Zero Coupon Bond

7 Jumps
  7.1 Basic facts
     7.1.1 The martingale process
  7.2 Building martingales
  7.3 Application
     7.3.1 Jumps
     7.3.2 Jump diffusion processes
     7.3.3 The Merton model
     7.3.4 The binomial model
     7.3.5 Bernoulli model
     7.3.6 Kou double exponential model


8 The Variance Gamma Model
8.1 The Variance Gamma Model
8.1.1 A time changed diffusion process
8.1.2 Vg as time changed Brownian motion
8.1.3 The characteristic function
8.1.4 The martingale process
8.1.5 The Characteristic function

9 The Heston Model
  9.1 The Heston Model
  9.2 The MC method
  9.2.1 Numerical simulation
  9.3 The Finite Difference method

10 Numeraire change: a recipe
  10.1 The standard story
  10.2 Generalized Vanilla Option Pricing Equation
  10.3 One dimensional formulation
  10.4 A simple change of measure
  10.5 The SDE for P (t, T )
  10.6 Evolution in the terminal measure
  10.7 Bond Options in the terminal measure

11 First Passage Time
  11.1 Ito calculus
    11.1.1 Basic definition
    11.1.2 The Ito’s theorem in one dimension
    11.1.3 Stochastic differential equations
  11.2 Feynman-Kac Formula
    11.2.1 Introduction
    11.2.2 Solution
  11.3 The Kolmogorov equations for the transition probabilities
    11.3.1 The backward Kolmogorov equation
    11.3.2 The Forward Kolmogorov equation
  11.4 The diffusion equation
    11.4.1 Solution of the equation
    11.4.2 Boundary conditions
    11.4.3 Finite distance barriers
  11.5 Passage Time
  11.6 Vanilla Options
    11.6.1 Notation
    11.6.2 High Barrier
    11.6.3 Low Barrier

12 American Options
  12.1 A Different View on Pricing
  12.2 The America Put Option
  12.3 Binary Trees
  12.4 Finite Difference methods
  12.5 Going Backward. The Longstaff Schwartz method
    12.5.1 Interpolation. A Quick Look
    12.5.2 The Least Square Problem
  12.6 The Forward MC


Readings/Bibliography

[1] Paul Glasserman, Monte carlo methods in financial engineering, vol. 53, Springer Science & Busi-
ness Media, 2013.
[2] Peter Jäckel, Monte carlo methods in finance, vol. 71, J. Wiley, 2002.
[3] Samuel Karlin and Howard M Taylor, A first course in stochastic processes, vol. 1, Academic Press,
1975.
[4] Donald Ervin Knuth, The art of computer programming, vol. 3, Pearson Education, 1997.

Office hours

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