Help on basics from the book option pricing models and volatility

[NWoodham]

Hello all,

I have read from cover to cover a few times now the book, Option pricing model and volatility using excel-VBA by Wiley Finance

This is my first look at these models and am very interested in GARCH models, Binomial models and Stochastic modeling.

If you have read the book I would like some help in understanding the basic input parameters, I will try and put my assumptions below, I hope someone will respond to me to clear up the questions I have.

Question 1)

In Chapter 2 there is a symbol for Lambda this describes a tilt parameter for the flexible Binomial Tree

Tilt Parameter (Lambda (greek symbol))

Lambda > 0 for Positive Tilt
Lambda < 0 for Negative Tilt
Lambda = 999 for Automatic

lambda=log(Strike/Spot)-(2jo-n)volatility sqrt of dt
---------------
(n volatility squared) dt

where

jo=log(Strike/Spot)-n log(d0)
---------
log(uo/do)

How to code this into excel? ( I need to attach a picture of this formula is on Page 81



Question 2)

When looking at the Kurtosis of a data set, do you need to sort it from lowest to highest before you apply the kurt function in Excel?


Question 3)

What is the formula for Initial Stock Volatility and the formula for Volatility Skew, in basic excel please


Question 4)

Heston (1993) Stochastic Model for options

There are input parameters for the Heston model
Rho
Kappa ( is this Vega)?
Theta
Volatility of variance
Current variance
Lambda
Gamma

I would like clear instruction on how to obtain these input parameters, this is a bit confusing to me, are these estimates? And if so where from, how am I meant to deduce this?

Question 5)

The Heston and Nandi 2000 Garch Model

Again deducing the inputs, Where are they from? I understand Alpha, Beta, Gamma what the correct way to obtain them in a professional sense.

Alpha
Beta
Gamma
Omega
Lambda


These are meant to be estimates for inputting, then analyzing after for parameters?

Chapter 9 is all about parameter estimation, In the chapter are the following formula

GarchMLE (Maximum likelihood for garch models)
Garchparams which invokes the nelder mead algorithm
Root mean squared error loss function
Relative root mean squared option
Implied volatility root mean squared error loss function.

How are these formulas fitted into the Heston and Nandi 2000 Garch Model


The book is great but I am weak in this area, and dont have anyone to call on for help, if someone can help me this will be a real boost to my understanding

Thanks for reading

Neil