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Introduction to Implied, Local and Stochastic Volatility

Introduction

Implied Volatility - Ito's Lemma

Taylor Series Expansion

Applying Ito to the Hedging Portfolio

Risk-Neutralization and No-Arbitrage

Implied Volatility (Smiles and Skews)

Local Volatility

Stochastic Volatility

Coupled SDEs for Stochastic Volatility

Risk-Neutralization and No-Arbitrage

The Heston Model

Exact Solution for Heston Volatility

Ornstein-Uhlenbeck Process

Formulae derivation for Heston Volatility

The fundamental solution

References

Books Related

Introduction to Implied, Local and Stochastic Volatility

Applying Ito to the Hedging Portfolio

Now we derive the Black-Scholes equation for a European option V with arbitrary payoff V (S, T) = Ψ(S). Let us construct a portfolio Π consisting of one option and a number "−φ" of an underlying asset. The value of the portfolio is:

Π = V − φS

where φ is constant and makes Π instantaneously risk-free. The jump in the value of this portfolio in one time step is:

dΠ = dV − φdS

Let us consider that the dividend yield is defined as the proportion of the asset price paid out per unit time, so then, at time dt, the underlying asset pays out a dividend D * S * dt. Since we receive D * S * dt for every asset held and since we hold "−φ" of the underlying, our portfolio changes to:

dΠ = dV − φdS − φDSdt

We suppose that the stock price S satisfies the following SDE:

dS = S(r − D)dt + SσdW

where "r" is the risk free bank rate, "D" is the dividend, and "σ” is the volatility for the stock price "S". Applying Ito’s lemma to V , we find:

and so:

(7)

Prof. Klaus Schmitz

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