Long-only cryptocurrency portfolio management by ranking the assets: a neural network approach

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📝 Original Info

  • Title: Long-only cryptocurrency portfolio management by ranking the assets: a neural network approach
  • ArXiv ID: 2512.08124
  • Date: 2025-12-09
  • Authors: Zijiang Yang

📝 Abstract

This paper will propose a novel machine learning based portfolio management method in the context of the cryptocurrency market. Previous researchers mainly focus on the prediction of the movement for specific cryptocurrency such as the bitcoin(BTC) and then trade according to the prediction. In contrast to the previous work that treats the cryptocurrencies independently, this paper manages a group of cryptocurrencies by analyzing the relative relationship. Specifically, in each time step, we utilize the neural network to predict the rank of the future return of the managed cryptocurrencies and place weights accordingly. By incorporating such cross-sectional information, the proposed methods is shown to profitable based on the backtesting ex...

📄 Full Content

Investment in the financial market is crucial to both retail and institutional investors. Investors hold a number of assets and construct the financial portfolio. In the context of portfolio management, how to allocate the weight to each asset becomes the most crucial and challenging problem. Markowitz, who received the 1990 Nobel price in economics, proposed the foundational theoretical model for modern portfolio theory(MPT) [1]. The main idea behind is to maximize the return while controlling the overall risk.

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Reference

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