# Deep Prediction of Investor Interest: a Supervised Clustering Approach

arXiv: https://arxiv.org/abs/1909.05289 · HTML: https://mlsanity.com/paper/1909.05289/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Sep 2019.

## Built on by (most cited first, 1 of 1)

- [Temporal distribution of clusters of investors and their application in prediction with expert advice](https://mlsanity.com/paper/2406.19403/) (2024)

## Abstract (arXiv)

We propose a novel deep learning architecture suitable for the prediction of investor interest for a given asset in a given time frame. This architecture performs both investor clustering and modelling at the same time. We first verify its superior performance on a synthetic scenario inspired by real data and then apply it to two real-world databases, a publicly available dataset about the position of investors in Spanish stock market and proprietary data from BNP Paribas Corporate and Institutional Banking.