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Enron Mail |
Ken and Greg,
What we have been doing is absoutely fine under the assumption that the market conditions move relatively small ( where Taylor series has fast convergence). However, we could run into troubles when the market has a big move. In order to have a error proof bucketing, we can use the following method(finite-difference), let me know what you guys think how to implement it to the transport book. Sensitivity to risk parameters, or P/L attribution by risk bucket: Today's premium = Premium based on today's curves Last day's premium = Premium based on last day's curves Change due to DeliveryCurveShift = [Premium based on today's delivery price and last day's receipt price, volatilities, interest rate, last's time to expiration etc] - Last day's premium - today's change due to Gamma1 ReceiptCurveShift = [Premium based on today's receipt price and last day's everything else] - Last day's premium -today's change due to Gamma2 Vega1 = [Premium based on today's delivery volatility and last day's everything else] - Last day's premium Vega2 = as above for gas volatility Rho = as above for interest rate Eta = as above for correlation Theta = {[Premium based on today's days to expiration and last day's everything else] - Drift - Last day's premium } / 365.25 [This is a daily Theta.The sprdopt function returns an annualised theta.] Gamma1 = 0.5 Last day's Gamma1' * PriceShift1 2??Gamma2 = 0.5 Last day's Gamma2' * PriceShift2 2 Drift = [(exp (Last day's interest rate*(Today - Last days) /365.25)) - 1 ]* Last day's premium Priceshift1 = Today's delivery price - Last day's delivery price Priceshift2 = Today's receipt price - Last day's receipt price Gamma1' = theoretical Gamma1, i.e. gamma from spread option Gamma2' = theoretical Gamma2, i.e. gamma from spread option calculation Liquidation= Premium of option which expired the day before, i.e. intrinsic value.
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