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Cryptocurrencies, such as Bitcoin, Binance, Ethereum, FTX, and XRP, are decentralized digital assets known for their volatile nature and potential as investment instruments. Accurate price prediction is crucial for informed investment decisions. This study explores the feasibility of various modeling techniques on diverse data structures and features for predicting the prices of these ...
1 lis 2022 · We employ and analyze various machine learning models for daily cryptocurrency market prediction and trading. We train the models to predict binary relative daily market movements of the 100 largest cryptocurrencies.
27 sie 2023 · This paper discusses the use of six types of machine-learning models (Linear Regression, LSTM, Bi-LSTM, GRU, TARCH, and VAR) to predict the Bitcoin and DogeCoin prices; General Least-Squares Regression and Neural Networks algorithms to predict the volatility of a given cryptocurrency and its prices from 2014 to 2023 with daily cryptocurrency ...
1 lut 2020 · Integrating gold spot price with regular features such as property, network, trading and market in the machine learning algorithm, we develop higher-dimensional features and avoid the problem of simplifying Bitcoin price prediction.
6 sty 2021 · This study examines the predictability of three major cryptocurrencies—bitcoin, ethereum, and litecoin—and the profitability of trading strategies devised upon machine learning techniques (e.g., linear models, random forests, and support vector machines).
This paper compares deep learning (DL), machine learning (ML), and statistical models for forecasting the daily prices of cryptocurrencies. Our one-step-ahead evaluation framework is incremental and works on a monthly retraining schedule.
20 kwi 2023 · Different machine learning approaches including linear regression, support vector machine, random forest, and deep learning networks will be used to construct the prediction model.
