maths in book

README.md

@@ -80,9 +80,9 @@ We offer a `SampleCovariance` class as seen above.
 Factor risk models use the projection of the weight vector into a lower
 dimensional subspace, e.g. each asset is the linear combination of $k$ factors.
 
-$$
+```{math}
 r_i = \sum_{j=1}^k f_j \beta_{ji} + \epsilon_i
-$$
+```
 
 The factor time series are $f_1, \ldots, f_k$. The loadings are the coefficients
 $\beta_{ji}$.
@@ -94,15 +94,15 @@ factor space. The variance for a position $w$ is the sum of the variance of the
 systematic returns explained by the factors and the variance of the
 idiosyncratic returns.
 
-$$
+```{math}
 Var(r) = Var(\beta^T w) + Var(\epsilon w)
-$$
+```
 
 We assume the residual returns are uncorrelated and hence
 
-$$
+```{math}
 Var(r) = y^T \Sigma_f y + \sum_i w_i^2 Var(\epsilon_i)
-$$
+```
 
 where $\Sigma_f$ is the covariance matrix of the factors and $Var(\epsilon_i)$
 is the variance of the idiosyncratic returns.

book/_config.yml

@@ -8,6 +8,7 @@ only_build_toc_files: true
 parse:
   myst_enable_extensions:
     # for conversion of the maths
+    - amsmath
     - dollarmath
 
 # needed for plotly