The data science doctor continues his exploration of techniques used to reduce the likelihood of model overfitting, caused by training a neural network for too many iterations. Regularization is a ...
As is well known, the centerpiece of model calibration is regularization, which plays an important role in transforming an ill-posed calibration problem into a stable and well-formulated one. This ...
The vector autoregressive model has long been used for portfolio analysis, while a recent extension (VARX) incorporates exogenous factors. Despite its increased forecasting precision, the ...
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