docs: correct typo

factorpricingmodel · Dec 8, 2022 · 46d3202 · 46d3202
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diff --git a/docs/source/statistical.md b/docs/source/statistical.md
@@ -4,11 +4,9 @@ The statistical approaches deduces the factor structures from the sample returns
 covariance matrix of the estimation universe. One of the common approaches is
 principal components analysis (PCA)
 
-
-
 ```{toctree}
 :caption: Approach
 :maxdepth: 2
 
 statistical/pca
-```
+```
diff --git a/docs/source/statistical/pca.md b/docs/source/statistical/pca.md
@@ -2,7 +2,7 @@
 
 Assume the historical instrument returns of the estimation universe is
 represented by a T x N matrix R. With singular value decomposition (SDV),
-the covariance matrix $\hat{Q}$ is decomposited by its eigenvectors and
+the covariance matrix $\hat{Q}$ is decomposed by its eigenvectors and
 eigenvalues.
 
 $$
@@ -28,4 +28,3 @@ $$
 
 where $W$ is the weight matrix in regression, e.g. an identity matrix in ordinary
 weighted least-squares.
-