Module 1 - Building Blocks of Quantitative Finance

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This module covers the foundational math essential to success in the CQF program, and as a quant. You will be introduced to the rules of applied Itô calculus as a modelling framework. You will build tools in both stochastic calculus and martingale theory and look at simple stochastic differential equations and their associated Fokker-Planck and Kolmogorov equations.

Sections

The Random Behavior of Assets

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• Different types of financial analysis
• Examining time-series data to model returns
• Random nature of prices
• The need for probabilistic models
• The Wiener process, a mathematical model of randomness
• The lognormal random walk- The most important model for equities, currencies, commodities and indices

PDEs and Transition Density Functions

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• Taylor series
• A trinomial random walk
• Transition density functions
• Our first stochastic differential equation
• Similarity reduction to solve partial differential equations
• Fokker-Planck and Kolmogorov equations

Applied Stochastic Calculus 1

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• Moment Generating Function
• Construction of Brownian Motion/Wiener Process
• Functions of a stochastic variable and Itô’s Lemma
• Applied Itô calculus
• Stochastic Integration
• The Itô Integral
• Examples of popular Stochastic Differential Equations

Applied Stochastic Calculus 2

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• Extensions of Itô’s Lemma
• Important Cases - Equities and Interest rates
• Producing standardised Normal random variables

Binomial Model

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• A simple model for an asset price random walk
• Delta hedging
• No arbitrage
• The basics of the binomial method for valuing options
• Risk neutrality

Martingales

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• Binomial Model extended
• The Probabilistic System: sample space, filtration, measures
• Conditional and unconditional expectation
• Change of measure and Radon-Nikodym derivative
• Martingales and Itô calculus
• A detour to explore some further Ito calculus
• Exponential martingales, Girsanov and change of measure

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Lecture order and content may occasionally change due to circumstances beyond our control. However, this will never affect the quality of the program.

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Quantitative Risk & Return