I'm writing my master thesis right now and I want to quantifying systematic risk factors influencing the pricing of credit derivatives.
My pricing model is the Gausssian single-factor model within i'm using asymptotic analytical approximation procedures to calculate expected tranche losses (Vasicek 1987). Calculating the correlation parameter a base correlation approach is used, calculated with a dynamic panel regression approach.
Φ^(−1)(ρ^(i)_(t)) = β +α_(i) +β ·Φ^(−1)(ρ^(i)_(t-1) + v_(t)+u^(i)_(t)
v_(t) describes an unobservable random effect accounting for any time-specific effect that is not included in the regression.
Now, I like to substitute the random time-effect by some systematic risk factors. Though the model, formerly a mixed one, changes to a fixed regression model.
I'm now thinking about which systematic proxies should be used. Maybe the business climate (S&P500), the volatility (VIX Index), the treasury rate level...
Have you some ideas what kind of systematic risk could influences the pricing?
My pricing model is the Gausssian single-factor model within i'm using asymptotic analytical approximation procedures to calculate expected tranche losses (Vasicek 1987). Calculating the correlation parameter a base correlation approach is used, calculated with a dynamic panel regression approach.
Φ^(−1)(ρ^(i)_(t)) = β +α_(i) +β ·Φ^(−1)(ρ^(i)_(t-1) + v_(t)+u^(i)_(t)
v_(t) describes an unobservable random effect accounting for any time-specific effect that is not included in the regression.
Now, I like to substitute the random time-effect by some systematic risk factors. Though the model, formerly a mixed one, changes to a fixed regression model.
I'm now thinking about which systematic proxies should be used. Maybe the business climate (S&P500), the volatility (VIX Index), the treasury rate level...
Have you some ideas what kind of systematic risk could influences the pricing?