Asian Option Pricing & Averaging Lab
Price arithmetic and geometric average Asian options using Kemna-Vorst (1990) closed forms and Turnbull-Wakeman moment matching. Quantify volatility dampening and hedge corporate cash flows.
Contract & Averaging Inputs
Valuation Summary & Volatility Dampening
| Model / Pricing Method | Option Premium | Effective Volatility (σ_eff) | Savings vs. Vanilla | Analytical Character |
|---|---|---|---|---|
| Arithmetic Asian (Turnbull-Wakeman) | $0.00 | 0.0% | 0.0% | Moment-matching approximation |
| Geometric Asian (Kemna-Vorst 1990) | $0.00 | 0.0% | 0.0% | Exact closed-form solution |
| Monte Carlo with Control Variate (10k paths) | $0.00 | - | 0.0% | Standard Error < $0.005 |
| European Vanilla Benchmark (Black-Scholes) | $0.00 | 0.0% | Baseline (0.0%) | Standard lognormal terminal |
Asian Option Greeks (Finite Difference Engine)
Visual Analytics & Averaging Dynamics
Matrix 1: Spot Price (S) vs. Volatility (σ) on Arithmetic Asian Price
Evaluates Arithmetic Asian option valuation across spot price shifts (±20%) and volatility shocks.
Matrix 2: Observation Points (N) vs. Expiry (T) on Hedging Discount (%)
Analyzes cost savings vs. standard European vanilla options across sampling frequencies and horizons.
Mathematical Foundation: Kemna-Vorst & Turnbull-Wakeman
1. Geometric Closed Form (Kemna & Vorst 1990)
For continuous geometric averaging G = exp((1/T) ∫_0^T ln(S_t) dt), the log of the product of lognormals is strictly normally distributed, yielding an exact analytical closed form:
b_G = (1/2) · (b - (1/6)σ²)
d_1 = [ln(S / K) + (b_G + 0.5σ_G²)T] / [σ_G √T]
d_2 = d_1 - σ_G √T
C_G = S e^{(b_G - r)T} N(d_1) - K e^{-rT} N(d_2)
Because σ_G = σ/√3 ≈ 0.577σ, volatility is dampened by over 42%, making geometric Asian options substantially cheaper than vanilla contracts.
2. Arithmetic Moment Matching (Turnbull & Wakeman 1991)
Arithmetic averages A = (1/T) ∫_0^T S_t dt have no simple closed form because the sum of lognormals is not lognormal. Turnbull-Wakeman matches the first two analytical moments:
M_2 = E[A²] = [2 S² / (b + σ²)] · [(e^{(2b+σ²)T} - 1)/((2b+σ²)T²) - (e^{bT}-1)/(bT²)]
σ_A = √(ln(M_2 / M_1²) / T)
C_A = e^{-rT} · [M_1 N(d_1) - K N(d_2)]
Turnbull-Wakeman provides sub-cent accuracy compared to 100,000-path Monte Carlo simulations, serving as the benchmark standard in commercial commodity trading desks.
Asian Option Mastery Quiz
Frequently Asked Questions
Explore Related Quantitative Finance & Derivatives Labs
Barrier Option Pricing Lab
Model single barrier knock-in & knock-out exotic options, in-out parity, and pin risk.
Black-76 Futures Option Lab
Model options on futures, commodity forwards, interest rate caplets, and swaptions.
Bjerksund-Stensland Lab
Closed-form flat boundary approximation for American commodity and equity options.
SABR Volatility Smile Lab
Model Hagan asymptotic Black-76 implied vol smiles and CEV elasticity backbones.
Garman-Kohlhagen FX Lab
Price currency options under Covered Interest Parity and calculate dual interest rate Greeks.
Black-Scholes Options Lab
Evaluate classic lognormal option pricing, Greeks sensitivity surfaces, and implied volatility root-finding.