Can LSTM deep neural network predict bitcoin price based on historical data?
Is it feasible to use a Long Short-Term Memory (LSTM) deep neural network to accurately predict the future price of Bitcoin based solely on its historical data? While historical trends can provide valuable insights, can this complex algorithm capture the intricate nuances and sudden fluctuations that characterize the cryptocurrency market? Additionally, how robust is the model's ability to adapt to unforeseen events, such as regulatory changes or significant market manipulations, that could drastically alter Bitcoin's price trajectory?
Can LSTM predict bitcoin price?
Could you elaborate on the feasibility of using Long Short-Term Memory (LSTM) networks to predict the price of Bitcoin? Are there any studies or examples that demonstrate the success of LSTM in accurately forecasting Bitcoin's volatile market movements? What are the potential challenges and limitations in applying LSTM for Bitcoin price prediction, and how might these be addressed or mitigated? Furthermore, how do LSTM's capabilities compare to other machine learning or statistical methods for predicting Bitcoin prices?