統計

鑑於回報之間的相關性,股票價格之間的相關性

  • May 8, 2020

假設我有兩隻已知波動率和已知回報相關係數的股票 - 有誰知道如何確定價格與回報之間的相關

當兩隻股票遵循幾何布朗運動時,我們可以獲得給定(對數)收益相關性的價格相關性的封閉式表達式:

$$ S_1(t) = S_1(0)e^{(\mu_1- \frac{1}{2} \sigma_1^2)t}e^{\sigma_1Z_1(t)},\ S_2(t) = S_2(0)e^{(\mu_2- \frac{1}{2} \sigma_2^2)t}e^{\sigma_2Z_2(t)}, $$

在哪裡 $ \text{corr}(Z_1(t),Z_2(t)) = E[Z_1(t)Z_2(t)]=\rho t $ . 日誌返回的相關性在一個長度間隔內 $ \delta t $ 是

$$ \text{corr}\left(\log \frac{S_1(t+\delta t)}{S_1(t)} , \log \frac{S_2(t + \delta t)}{S_2(t)} \right) = \rho \delta t $$

價格相關性為

$$ \tag{*}\rho_{S_1S_2}=\frac{E[(S_1(t) - E(S_1(t))(S_2(t) - E(S_2(t))]}{\sqrt{\text{var}(S_1(t))}\sqrt{\text{var}(S_2(t))}} $$

回想起來 $ E(e^{\sigma_1 Z_1(t)}) = e^{\frac{1}{2} \sigma_1^2 t} $ , 我們獲得 $$ E(S_1(t)) = S_1(0)e^{\mu_1t}, \quad E(S_2(t)) = S_2(0)e^{\mu_2t} \\text{var}(S_1(t)) = S_1(0)^2e^{2 \mu_1 t}( e^{\sigma_1^2t}-1), \quad \text{var}(S_2(t)) = S_2(0)^2e^{2 \mu_2 t}( e^{\sigma_2^2t}-1) $$

注意

$$ E[(S_1(t) - E(S_1(t))(S_2(t) - E(S_2(t))] = E[S_1(t)S_2(t)] - E(S_1(t)) E(S_2(t)) \ = S_1(0)S_2(0)e^{\mu_1t}e^{\mu_2t}\left(e^{-\frac{1}{2}\sigma_1^2t}e^{-\frac{1}{2}\sigma_2^2t}E[e^{\sigma_1Z_1(t) + \sigma_2Z_2(t)}] - 1\right) $$

代入 (*) 我們得到

$$ \tag{**}\rho_{S_1S_2} = \frac{e^{-\frac{1}{2}\sigma_1^2t}e^{-\frac{1}{2}\sigma_2^2t}E[e^{\sigma_1Z_1(t) + \sigma_2Z_2(t)}] - 1}{\sqrt{ e^{\sigma_1^2t}-1}\sqrt{ e^{\sigma_2^2t}-1}} $$

自從 $ Z_1(t) $ 和 $ Z_2(t) $ 均正態分佈,均值 $ 0 $ 和變異數 $ t $ , 它遵循 $ \sigma_1Z_1(t) + \sigma_2 Z_2(t) $ 正態分佈,均值 $ 0 $ 和變異數

$$ \text{var}(\sigma_1Z_1(t)+\sigma_2Z_2(t)) = E[(\sigma_1Z_1(t)+\sigma_2Z_2(t))^2 \ = (\sigma_1^2 + \sigma_2^2 + 2\rho \sigma_1\sigma_2)t $$

然後我們有

$$ E[e^{\sigma_1Z_1(t) + \sigma_2Z_2(t)}] = e^{\frac{1}{2}\sigma_1^2t}e^{\frac{1}{2}\sigma_2^2t}e^{\rho\sigma_1\sigma_2t}, $$

並代入 (**)

$$ \rho_{S_1S_2} = \frac{e^{\rho\sigma_1\sigma_2t} - 1}{\sqrt{ e^{\sigma_1^2t}-1}\sqrt{ e^{\sigma_2^2t}-1}} $$

引用自:https://quant.stackexchange.com/questions/45857