Forecasting VIX using Bayesian Deep Learning. (arXiv:2401.17042v1 [cs.LG])

Recently, deep learning techniques are gradually replacing traditional
statistical and machine learning models as the first choice for price
forecasting tasks. In this paper, we leverage probabilistic deep learning for
inferring the volatility index VIX. We employ the probabilistic counterpart of
WaveNet, Temporal Convolutional Network (TCN), and Transformers. We show that
TCN outperforms all models with an RMSE around 0.189. In addition, it has been
well known that modern neural networks provide inaccurate uncertainty
estimates. For solving this problem, we …

arxiv bayesian bayesian deep learning cs.lg deep learning deep learning techniques forecasting index machine machine learning machine learning models network paper price probabilistic deep learning show statistical tasks temporal transformers wavenet