Web: http://arxiv.org/abs/2205.01639

May 4, 2022, 1:11 a.m. | Nicole Koenigstein

cs.LG updates on arXiv.org arxiv.org

The growth of machine-readable data in finance, such as alternative data,
requires new modeling techniques that can handle non-stationary and
non-parametric data. Due to the underlying causal dependence and the size and
complexity of the data, we propose a new modeling approach for financial time
series data, the $\alpha_{t}$-RIM (recurrent independent mechanism). This
architecture makes use of key-value attention to integrate top-down and
bottom-up information in a context-dependent and dynamic way. To model the data
in such a dynamic manner, …

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