Work2019

Cryptocurrency Price Analysis with Artificial Intelligence

74 citations0/0 files storedInternational Conference on Information Management

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Blockchain Technology Applications and Security

Abstract

Cryptocurrency is playing an increasingly important role in reshaping the financial system due to its growing popular appeal and mechant acceptance. While many people are making investments in Cryptocurrency, the dynamical features, uncertainty, the predictability of Cryptocurrency are still mostly unknown, which dramatically risk the investments. It is a matter to try to understand the factors that infiuence the value formation. In this study, we use advanced artificial intelligence frameworks of fully connected Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM) Recurrent Neural Network to analyse the price dynamics of Bitcoin, Etherum, and Ripple. We find that ANN tends to rely more on long-term history while LSTM tends to rely more on short-term dynamics, which indicate the efficiency of LSTM to utilise useful information hidden in historical memory is stronger than ANN. However, given enough historical information ANN can achieve a similar accuracy, compared with LSTM. This study provides a unique demonstration that Cryptocurrency market price is predictable. However, the explanation of the predictability could vary depending on the nature of the involved machine-learning model.

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References

2014Stock Price Prediction Using the ARIMA Model 1996Designing a neural network for forecasting financial and economic time series 2005Empirical exchange rate models of the nineties: Are any fit to survive?1988Economic prediction using neural networks: the case of IBM daily stock returns 2014Bayesian regression and Bitcoin 2012Stock Price Prediction using Neural Network with Hybridized Market Indicators 2018Non-linear Autoregressive with Exogeneous input (narx) bitcoin price prediction model using PSO-optimized parameters and moving average technical indicators

Cited by

2020Cryptocurrencies and Artificial Intelligence: Challenges and Opportunities 2021Time-Series Prediction of Cryptocurrency Market using Machine Learning Techniques 2022Fusion in Cryptocurrency Price Prediction: A Decade Survey on Recent Advancements, Architecture, and Potential Future Directions 2021Comparing Bitcoin's Prediction Model Using GRU, RNN, and LSTM by Hyperparameter Optimization Grid Search and Random Search 2024Cryptocurrency Price Prediction Algorithms: A Survey and Future Directions

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