Deep State-Space Model for Predicting Cryptocurrency Price

ArXiv ID: 2311.14731 “View on arXiv”

Authors: Unknown

Abstract

Our work presents two fundamental contributions. On the application side, we tackle the challenging problem of predicting day-ahead crypto-currency prices. On the methodological side, a new dynamical modeling approach is proposed. Our approach keeps the probabilistic formulation of the state-space model, which provides uncertainty quantification on the estimates, and the function approximation ability of deep neural networks. We call the proposed approach the deep state-space model. The experiments are carried out on established cryptocurrencies (obtained from Yahoo Finance). The goal of the work has been to predict the price for the next day. Benchmarking has been done with both state-of-the-art and classical dynamical modeling techniques. Results show that the proposed approach yields the best overall results in terms of accuracy.

Keywords: Deep state-space model, Cryptocurrency price prediction, State-space model, Uncertainty quantification, Deep neural networks, Cryptocurrency

Complexity vs Empirical Score

  • Math Complexity: 8.5/10
  • Empirical Rigor: 6.5/10
  • Quadrant: Holy Grail
  • Why: The paper proposes a novel deep state-space model, integrating non-negative matrix factorization with Gaussian SSMs and requiring an alternating majorization-minimization algorithm for inference, demonstrating high mathematical density. Empirically, it includes benchmarks on real cryptocurrency data from Yahoo Finance and accuracy metrics, suggesting a backtest-ready implementation, though lacking publicly available code or exhaustive statistical validation.
  flowchart TD
    A["Research Goal<br>Predict Day-Ahead<br>Cryptocurrency Prices"] --> B["Data Collection<br>Yahoo Finance<br>Eth & Btc Data"]
    B --> C["Methodology<br>Deep State-Space Model<br>SSM + DNN"]
    C --> D["Computational Process<br>Probabilistic Formulation<br>+ Uncertainty Quantification"]
    D --> E["Comparison<br>vs SOTA & Classical Models"]
    E --> F["Outcome<br>Best Overall<br>Accuracy Achieved"]