Blame
3f2847 | Stanislav Kubrak | 2024-08-23 14:22:46 | 1 | # SF Option Payoff |
2 | ||||
3 | Let's consider vanila call option. | |||
4 | The corresponding payoff looks as following: | |||
5 | ||||
4af538 | Stanislav Kubrak | 2024-08-24 22:16:53 | 6 | $\text{Payoff}_{vanila} = max(S_T-K,0)$ |
3f2847 | Stanislav Kubrak | 2024-08-23 14:22:46 | 7 | |
8 | However Stochastic.Finance options have a bit of non-trivial payoff as a fraction of the supplied collateral: | |||
9 | ||||
4af538 | Stanislav Kubrak | 2024-08-24 22:16:53 | 10 | $\text{Payoff}_{SF} = \frac{\max(S_T - K, 0)}{\max(S_T - K, 0) + K}$ |
3f2847 | Stanislav Kubrak | 2024-08-23 14:22:46 | 11 | |
12 | for every ETH supplied collateral, so that in case the collateral is 10 ETH the total payoff would be $P_{SF}$ * 10 ETH | |||
4af538 | Stanislav Kubrak | 2024-08-24 22:16:53 | 13 | |
14 | This payoff function can be interpreted as: | |||
15 | ||||
16 | $\text{Payoff}_{SF} = \begin{cases}\frac{S_T - K}{S_T} & \text{if } S_T > K \\0 & \text{if } S_T \leq K\end{cases}$ | |||
17 | ||||
18 | The price of the option $V$ is given by the expected value of the discounted payoff under the risk-neutral measure $\mathbb{Q}$: | |||
19 | ||||
20 | $V = e^{-rT} \mathbb{E}^{\mathbb{Q}}\left[\frac{\max(S_T - K, 0)}{\max(S_T - K, 0) + K}\right]$ | |||
21 | ||||
22 | ||||
23 | ##### Substituting the explicit form of the payoff: | |||
24 | ||||
25 | $V = e^{-rT} \mathbb{E}^{\mathbb{Q}}\left[\frac{S_T - K}{S_T} \cdot \mathbb{I}(S_T > K)\right]$ | |||
26 | ||||
27 | where $\mathbb{I}(S_T > K)$ is an indicator function that equals 1 when $S_T > K$ and 0 otherwise. | |||
28 | ||||
29 | Let’s express the expected value in terms of the distribution of $S_T$, the stock price at time $T$ under the risk-neutral measure: | |||
30 | ||||
31 | $V = e^{-rT} \int_{K}^{\infty} \frac{S_T - K}{S_T} f_{S_T}(S_T) dS_T$ | |||
32 | ||||
33 | ||||
34 | ##### Log-Normal Distribution of $S_T$: | |||
35 | ||||
36 | Under the Black-Scholes model, the stock price $S_T$ is log-normally distributed: | |||
37 | ||||
38 | $S_T = S_0 \exp\left(\left(r - \frac{\sigma^2}{2}\right)T + \sigma W_T\right)$ | |||
39 | ||||
40 | where $W_T$ is a standard Brownian motion under the risk-neutral measure. | |||
41 | ||||
42 | The PDF of $S_T$ is: | |||
43 | ||||
44 | $f_{S_T}(S_T) = \frac{1}{S_T \sigma \sqrt{2\pi T}} \exp\left(-\frac{\left(\ln\left(\frac{S_T}{S_0}\right) - \left(r - \frac{\sigma^2}{2}\right)T\right)^2}{2\sigma^2 T}\right)$ | |||
45 | ||||
46 | ||||
47 | ##### Rewriting the Integral: | |||
48 | ||||
49 | We can now rewrite the option price as: | |||
50 | ||||
51 | $V = e^{-rT} \int_{K}^{\infty} \left(1 - \frac{K}{S_T}\right) f_{S_T}(S_T) dS_T$ | |||
52 | ||||
53 | This can be split into two integrals: | |||
54 | ||||
55 | $V = e^{-rT} \left[ \int_{K}^{\infty} f_{S_T}(S_T) dS_T - K \int_{K}^{\infty} \frac{1}{S_T} f_{S_T}(S_T) dS_T \right]$ | |||
56 | ||||
57 | The first integral | |||
58 | ||||
59 | $\int_{K}^{\infty} f_{S_T}(S_T) dS_T$ | |||
60 | ||||
61 | is simply the probability $\mathbb{P}^{\mathbb{Q}}(S_T > K)$, which is given by $\Phi(d_2)$ where: $d_2 = \frac{\ln\left(\frac{S_0}{K}\right) + \left(r - \frac{\sigma^2}{2}\right)T}{\sigma\sqrt{T}}$ | |||
62 | ||||
63 | The second integral can be expressed as: | |||
64 | ||||
65 | $\int_{K}^{\infty} \frac{1}{S_T} \cdot \frac{1}{S_T \sigma \sqrt{2\pi T}} \exp\left(-\frac{\left(\ln\left(\frac{S_T}{S_0}\right) - \left(r - \frac{\sigma^2}{2}\right)T\right)^2}{2\sigma^2 T}\right) dS_T$ | |||
66 | ||||
67 | ||||
68 | $= \frac{1}{\sigma \sqrt{2\pi T}} \int_{K}^{\infty} \frac{1}{S_T^2} \exp\left(-\frac{\left(\ln\left(\frac{S_T}{S_0}\right) - \left(r - \frac{\sigma^2}{2}\right)T\right)^2}{2\sigma^2 T}\right) dS_T$ | |||
69 | ||||
70 | Fortunatly such integral has a closed-form solution. The final formula for option price looks as following: | |||
71 | ||||
72 | $\text{V}_{SF} = \exp(-rT)\left(\Phi(d_2) - \frac{1}{2}\frac{K}{S_0}\text{erfc}(\zeta)\exp\left(-(r -\sigma^2)T\right)\right)$ | |||
73 | ||||
74 | where: | |||
75 | ||||
76 | $\zeta = \frac{3 \sqrt{2} T \sigma^2 - 2^{3/2} T r + 2^{3/2} \ln\left(\frac{K}{S_0}\right)}{4 \sqrt{T} \sigma}$ |