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You said:"I understand that the generated ticks will be generated using interpolation (so they won't be exacts)". You are very optimistic, they will not only be far away from being exact, they (the tick data) will be completely removed from reality, the only parameters known for the tick data will be boundary conditions, such as open high low close. You ...

I reproduced Ledoit and Wolf's experiment outlined in their paper "Honey I Shrunk the Covariance Matrix" in Python which includes an implementation of their method to shrink the covariance matrix (can be found here see the get_shrunk_covariance_matrix() method on line 417). All the code for the entire thing is on Github here. I make use of the cvxopt module ...

I know this is an old question, but Wes McKinney, the developer of pandas (mentioned in another answer) is releasing a new Python package called RapidQuant that I think might meet the OP's stated needs. It appears to include both non-standard risk definitions and portfolio optimization. However, it is not open source. While the OP didn't specifically mention ...