By vectorizing computations and using Numba JIT, the performance of SRISK calculations has been significantly improved. #7
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Added a crucial state check to the fit method in GJRGARCHModel that was previously omitted. The absence of this check led to redundant estimations during the optimization of parameters 'a' and 'b' in the DCC-GJRGARCH model, resulting in significant performance inefficiencies. This update ensures that all necessary conditions are verified before proceeding with calculations, thus enhancing the model's efficiency and reliability.
Vectorize the grid search method for finding initialization parameters and use the Numba JIT function to wrap the volatility model for improved performance.
Vectorize the grid search method for finding initialization parameters and use the Numba JIT function to wrap the dcc model for improved performance.
Vectorize the S-sample calculations and computation process of LRMES to enhance performance.
lianghx123
changed the title
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Sorry I missed this PR. Let me check into this later this month. I was trying to use C++ extension when possible but maybe replacing all C++ extensions with Numba is also a good idea. |
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Note: The initial installation and compilation of JIT functions take relatively longer.