Hi All,
I am attempting a MC simulation using GARCH(1,1) volatility model. I am not trying to estimate parameters as these have been given (Ritchken & Trevor (1999)). I am just trying to achieve the correct result. I have obtained the expected variance using the information in (Hull, 2005) shown below:
From: Options, Futures and Other Derivatives (Hull, 2005) ( Evolution of sigma(t+1) )
GARCH(1,1) Volatility:
\(\sigma^2_{n} = \gamma V_{L} + \alpha u^{2}_{n-1} +\beta \sigma^{2}_{n-1}\)
where:
(\(\gamma = 1 - \alpha - \beta\))
\(\sigma^2_{n} = (1 - \alpha -\beta)V_{L} + \alpha u^{2}_{n-1} +\beta \sigma^{2}_{n-1}\)
Where the long term variance (\(V_{L}\)):
\(V_{L} = \frac{\omega}{1 - \alpha -\beta}\)
and the Return (\(u_{n-1}\)):
\(u_{n-1} = \frac{S_{n-1} - S_{n-2}}{S_{n-2}}\)
The expected variance (\(E[\sigma^2_{n+1}]\)):
\(E[\sigma^2_{n+1}] = V_{L} + (\alpha + \beta)(\sigma^{2}_{n} - V_{L}\))
I am then trying to use the equation given by Duan(1995) for the stock price evolution:
From: Duan (1995) ( Evolution of the stock price S(t+1) )
Using the Locally Risk-Neutral Valuation Relationship (LRNVR), the dynamics in the equivalent martingale measure is given by:
\(ln \frac{S_{t+1}}{S_{t}} = r - \frac{1}{2}\sigma_{n} +\widetilde{\varepsilon}_{t} \)
where:
\(\widetilde{\varepsilon}_{t}\) ~ \(N(0,\sigma_{n})\)
However, this does not produce the correct result. My question is, is the equation above the correct one for the evolution of the stock price under GARCH(1,1) volatility? I cannot seem to find any other equation.
From: Ritchken & Trevor (1999) (The option I am trying to price)
American Put Option Price:
Interest rate (r) is fixed at 10% (annualized using 365 days a year).
Stock price (S) is 100.
Time is (T = 100 days).
ω = 0.06575 (as we are working with returns in percentage terms)
α = 0.04
β = 0.90
γ = 0.00
λ = 0.00
Option Price: 3.143
Many thanks,
Hob
I am attempting a MC simulation using GARCH(1,1) volatility model. I am not trying to estimate parameters as these have been given (Ritchken & Trevor (1999)). I am just trying to achieve the correct result. I have obtained the expected variance using the information in (Hull, 2005) shown below:
From: Options, Futures and Other Derivatives (Hull, 2005) ( Evolution of sigma(t+1) )
GARCH(1,1) Volatility:
\(\sigma^2_{n} = \gamma V_{L} + \alpha u^{2}_{n-1} +\beta \sigma^{2}_{n-1}\)
where:
(\(\gamma = 1 - \alpha - \beta\))
\(\sigma^2_{n} = (1 - \alpha -\beta)V_{L} + \alpha u^{2}_{n-1} +\beta \sigma^{2}_{n-1}\)
Where the long term variance (\(V_{L}\)):
\(V_{L} = \frac{\omega}{1 - \alpha -\beta}\)
and the Return (\(u_{n-1}\)):
\(u_{n-1} = \frac{S_{n-1} - S_{n-2}}{S_{n-2}}\)
The expected variance (\(E[\sigma^2_{n+1}]\)):
\(E[\sigma^2_{n+1}] = V_{L} + (\alpha + \beta)(\sigma^{2}_{n} - V_{L}\))
I am then trying to use the equation given by Duan(1995) for the stock price evolution:
From: Duan (1995) ( Evolution of the stock price S(t+1) )
Using the Locally Risk-Neutral Valuation Relationship (LRNVR), the dynamics in the equivalent martingale measure is given by:
\(ln \frac{S_{t+1}}{S_{t}} = r - \frac{1}{2}\sigma_{n} +\widetilde{\varepsilon}_{t} \)
where:
\(\widetilde{\varepsilon}_{t}\) ~ \(N(0,\sigma_{n})\)
However, this does not produce the correct result. My question is, is the equation above the correct one for the evolution of the stock price under GARCH(1,1) volatility? I cannot seem to find any other equation.
From: Ritchken & Trevor (1999) (The option I am trying to price)
American Put Option Price:
Interest rate (r) is fixed at 10% (annualized using 365 days a year).
Stock price (S) is 100.
Time is (T = 100 days).
ω = 0.06575 (as we are working with returns in percentage terms)
α = 0.04
β = 0.90
γ = 0.00
λ = 0.00
Option Price: 3.143
Many thanks,
Hob
