A wavelet-convolution channel-attention LSTM model improves one-step-ahead stock price prediction and long-short portfolio backtests on four large-cap US stocks, with reported Sharpe ratios above 1.8.
In: 2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS), pp
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
baseline 1
citation-polarity summary
fields
q-fin.ST 1years
2025 1verdicts
CONDITIONAL 1roles
baseline 1polarities
baseline 1representative citing papers
citing papers explorer
-
Integration of Wavelet Transform Convolution and Channel Attention with LSTM for Stock Price Prediction based Portfolio Allocation
A wavelet-convolution channel-attention LSTM model improves one-step-ahead stock price prediction and long-short portfolio backtests on four large-cap US stocks, with reported Sharpe ratios above 1.8.