2021 5th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) · 2021 · 11 citations · 14 references
ComputingComputer ScienceEconomicsForecastingMachine LearningPredictive AnalyticsDeep LearningFinancial ForecastingFinancial Time Series AnalysisShort-term ForecastingTime Series ForecastingTime Series PredictionConvolutional Neural NetworksDeep Learning For ForecastingDeep Learning For Time Series ForecastingDeep Learning-based ForecastingDeep Learning-based Price ForecastingFinancial Time Series ForecastingLong Short-term Memory NetworksRelative Strength
Bitcoin as a digital cryptocurrency interests the scientists substantially in the areas of computer science, cryptography and economics. In this work, we propose to forecast the last price of Bitcoin Dollar rate in short-term or frequent trading transactions known as day-trading. In addition to statistical indicators such as maximum, minimum, and average prices, technical indicators such as Bollinger band (BB), hour-based moving average (MA), Relative Strength Index (RSI) are also evaluated as a feature set. In order to estimate the price of Bitcoin, different deep and hybrid deep learning methodologies are employed, namely convolutional neural networks (CNNs), long short-term memory networks (LSTMs), convolutional long short-term memory networks (ConvLSTM), CNN Long Short-Term Memory Network (CNN-LSTM). Extensive experiment results exhibit that the usage of ConvLSTM hybrid deep learning model is capable to estimate the price of Bitcoin with 2.4076 of MAPE result.
14
Klaus Greff, Rupesh K. Srivastava, Jan Koutník et al. · IEEE Transactions on Neural Networks and Learning Systems · 2016 · 6.8K citations · Full text
An Introduction to Convolutional Neural Networks
Keiron O’Shea, Ryan Nash · arXiv (Cornell University) · 2015 · 952 citations · Full text