假設已有dataset:
| company | date | stock return |
| a1 | DATE#1 | RET(a1,1) |
| a1 | DATE#2 | RET(a1,2) |
| ... | ... | ... |
| a1 | DATE#T | RET(a1,T) |
| a2 | DATE#1 | RET(a2,1) |
| ... | .... | .... |
| a2 | DATE#T | RET(a2,T) |
| ... | ... | ... |
| a5000 | DATE#1 | RET(a5000,1) |
| ... | ... | ... |
| a5000 | DATE#T | RET(a5000,T) |
請問該如何利用PROC TIMESERIES,估算這5000家公司股票報酬率的cross-covariance matrix呢?
cross-covariance:
GAMMA(K)=E[(Xi,t - E(Xi))(Xj,t+K - E(Xj))],
i=1,2,...,N;
j=1,2,...,N;
N: total number of companies
K: lag period
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我嘗試透過PROC IML建立新的dataset(如下),但遇到memory相關問題
| company i | company j | date | return i | return j |
| ... | ... | ... | ... | ... |



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