This paper shows a novel machine learning model for realized volatility (RV) prediction using a normalizing flow, an invertible neural network. Since RV is known to be skewed and have a…
deep learning
7 Articles
7
We apply an information-theoretic perspective to reconsider generative document retrieval (GDR), in which a document x∈X is indexed by t∈T, and a neural autoregressive model is trained to map queries Q to T. GDR…
The bitcoin price crash at the beginning of 2018 was caused by various social factors. The influence of news wire stories and social media was especially crucial because of the…
The theory of econophysics reveals the scaling properties of price, which explains why market crashes much more frequently than expected. A challenge of financial market modeling is to characterize the…
A generative model is a mathematical formulation that generates a sample similar to real data. Many such models have been proposed using machine learning methods, including deep learning. Study of…
For mathematical models of language, their potential, limitations, and ways of improvement are investigated in terms of whether they reproduce the complex properties of language. The nature of linguistic structure…
State-of-the-art word embedding methods represent a word with a single vector and presume a linear vector space, which does not easily incorporate nonlinearity that is necessary to, for example, represent…