1 / 86

Who is Afraid of Black Scholes

Who is Afraid of Black Scholes. A Gentle Introduction to Quantitative Finance Day 2. July 12 th 13 th and 15 th 2013 UNIVERSIDAD NACIONAL MAYOR DE SAN MARCOS. Ito Calculus. Suppose the stock price evolved as Problem with this model is that the price can become negative . Ito Calculus.

trory
Télécharger la présentation

Who is Afraid of Black Scholes

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Who is Afraid of Black Scholes A Gentle Introduction to Quantitative Finance Day 2 July 12th 13th and 15th 2013 • UNIVERSIDAD NACIONAL MAYOR DE SAN MARCOS

  2. Ito Calculus Suppose the stock price evolved as Problem with this model is that the price can become negative

  3. Ito Calculus A better model is that the ‘relative price’ NOT the price itself reacts to market fluctuations Q: What does this integral mean?

  4. Constructing the Ito Integral We will try and construct the Ito Stochastic Integral in analogy with the Riemann-Stieltjes integral Note the function evaluation at the left end point!!! Q: In what sense does it converge?

  5. Stochastic Differential Equations Consider the following Ito Integral We use the shorthand notation to write this as This is a simple example of a stochastic differential equation

  6. Convergence of the Integral We have noted the integral converges in the ‘mean square sense’ To see what this means consider This means

  7. Convergence of the Integral So we have (in the mean square sense) OR

  8. How to Integrate? A detour into the world of Ito differential calculus Q: What is the differential of a function of a stochastic variable? e.g. If what is Is it true that in the stochastic world as well? We will see the answer is in the negative We will construct the correct Taylor Rule for functions of stochastic variables This will help us integrating such functions as well

  9. Taylor Series & Ito’s Lemma Consider the Taylor expansion The change in F is given by We note that behaves like a determinist quantity that is it’s expected value as i.e. formally!!

  10. Taylor Series & Ito’s Lemma We consider when So the change involves a deterministic part and a stochastic part

  11. Ito’s Lemma We consider a function of a Weiner Process and consider a change in both W and t Ito’s Lemma

  12. Ito’s Lemma Obtain an SDE for the process We observe that So by Ito’s Lemma

  13. Integration Using Ito we can derive E.g. Show that

  14. Example Evaluate Evaluate

  15. Extension of Ito’s Lemma Consider a function of a process that itself depends on a Weiner process What is the jump in V if ?

  16. Extension of Ito So we have the result

  17. Example If S evolves according to GBM find the SDE for V Given Given

  18. Stochastic Differential Equation We will now ‘solve’ some SDE Most SDE do NOT have a closed form solution We will consider some popular ones that do

  19. Arithmetic Brownian Motion Consider dX=aXdt+bdW To ‘solve’ this we consider the process From extended Ito’s Lemma

  20. Ito Isometry A shorthand rule when taking averages Lets find the conditional mean and variance of ABM

  21. Mean and Variance of ABM We have using Ito Isometry

  22. Geometric Brownian Motion The process is given by To solve this SDE we consider Using extended form of Ito we have

  23. Black Scholes World The value of an option depends on the price of the underlying and time It also depends on the strike price and the time to expiry The option price further depends on the parameters of the asset price such as drift and volatility and the risk free rate of interest To summarize

  24. Assumptions The underlying follows a log normal process (GBM) The risk free rate is known (it could be time dependent) Volatility and drift are known constants There are no dividends Delta hedging is done continuously No transaction costs There are no arbitrage opportunities

  25. A Simple One Step Discrete Case

  26. The Payoff

  27. Short Selling

  28. Hedging with the Right Amount

  29. And the value is…….

  30. Drift and Volatility

  31. Delta Hedging • How did one know the quantity of stock to short sell? • Let’s re do the example: • Start with one option • And short on the stock • The portfolio at the next time is worth • if the stock rises • if the stock falls

  32. Delta Hedging • We want these to give the same value • In general we should go

  33. The Stock Price Model • Is out stock price model correct?

  34. Derivation of Black Scholes Equation We assumed that the asset price follows Construct a portfolio with a long position in the option and a short position in some quantity of the underlying The value of this portfolio is

  35. Derivation Q: How does the value of the portfolio change? Two factors: change in underlying and change in option value We hold delta fixed during this step

  36. Derivation We use Ito’s lemma to find the change in the value of the portfolio The change in the option price is Hence

  37. Derivation Plugging in Collecting like terms

  38. Derivation We see two type of movements, deterministic i.e. those terms with dt and random i.e. those terms with dW Q: Is there a way to do away with the risk? A: Yes, choose in the right way Reducing risk is hedging, this is an example of delta-hedging

  39. Derivation We pick Now the change in portfolio value is riskless and is given by

  40. Derivation If we have a completely risk free change in we must be able to replicate it by investing the same amount in a risk free asset Equating the two we get

  41. Black Scholes Equation We know what should be This gives us the Black Scholes Equation

  42. Black Scholes Equation This is a linear parabolic PDE Note that this does not contain the drift of the underlying This is because we have exploited the perfect correlation between movements in the underlying and those in the option price.

  43. Black Scholes Equation The different kinds of options valued by BS are specified by the Initial (Final) and Boundary Conditions For example for a European Call we have We will discuss BC’s later

  44. Variations: Dividend Paying Stock If the underlying pays dividends the BS can be modified easily We assume that the dividend is paid continuously i.e. we receive in time Going back to the change in the value of the portfolio

  45. Variations: Dividend Paying Stock The last terms represents the amount of dividend Using the same delta hedging and replication argument as before we have

  46. Variations: Currency Options These can be handled as in the previous case Let be the rate of interest received on the foreign currency, then

  47. Variations: Options on Commodities Here the cost of carry must be adjusted To simplify matters we calculate the cost of carrying a commodity in terms of the value of the commodity itself Let q be the fraction that goes toward the cost of carry, then

  48. Solving the Black Scholes Equation We need to solve a BS PDE with Final Conditions We will convert it to a ‘Diffusion Equation IVP’ by suitable change of variables Method of solution depends upon the PDE and BC Considering the BC in this case we will use the Fourier Transform Methods to find a function that satisfies the PDE and the BC Using different IC/FC will give the value for different options

  49. Transforming the BS Equation Consider the Black Scholes Equation given by As a first step towards solving this we will transform it into a IVP for a Diffusion Equation on the real line

  50. Transforming the BS Equation We make the change of variables This transforms the equation into Where

More Related