I am currently working on a paper that empirically examines the asymmetric relationship between oil price fluctuations and stock returns, and I want to estimate the non-linear error correction model.
I would like to recommend you to perform a statistical test for outliers (anomalies) in empirical data before building the model. Given that the data distribution are non-Gaussian, then normalizing transformations can be recommended for anomaly detection and building the non-linear model. See, for example, the link