jpcolino / ipython_notebooks Goto Github PK

Using your implementation of LSM MC for derivatives pricing from https://github.com/jpcolino/IPython_notebooks/blob/master/Least%20Square%20Monte%20Carlo%20Implementation%20in%20a%20Python%20Class.ipynb - thanks! Noticed that the class is immutable and you're using @property decorator for all calculated properties. Unfortunately, @property doesn't cache (memoize) the results so all the "expensive" properties (e.g. MCprice_matrix) are recalculated many times over when referenced from other methods.

A quick fix (and a huge speedup) is possible via Boltons package from boltons.cacheutils import cachedproperty and then using @cachedproperty instead of @property everywhere.

I understand that the source code is pretty old, so just letting you know this in case you're still maintaining it (or any derivations of it). I found it useful, so possibly others find it useful too.

Thanks.