Deep State-Space Model for Predicting Cryptocurrency Price

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. Preprint submitted to XXX November 28, 2023 1. Introduction Investopedia defines crypto-currency as "a digital or virtual currency that is secured by cryptography, which makes it nearly impossible to counterfeit or double-spend" and is built on "decentralized networks based on block-chain technology--a distributed ledger enforced by a disparate network of computers". A defining feature of crypto-currencies is that they are usually not issued by central banking agencies like the Federal Reserve System in US, Bank of Canada, European Central Bank, or the People's Bank of China; this makes cryptocurrencies (theoretically) immune to government interventions. The introduction of Bitcoin around 2009 and its meteoric rise led to investors infuse their funds in crypto-currencies.