[Paper Review] A multi-agent reinforcement learning framework for optimizing financial trading
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] A multi-agent reinforcement learning framework for optimizing financial trading
33:15
[Paper Review]Leveraging multi-time-span sequences and feature correlations for improved stock trend
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review]Leveraging multi-time-span sequences and feature correlations for improved stock trend
26:33
[Paper Review] Deep learning in stock portfolio selection and predictions
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Deep learning in stock portfolio selection and predictions
23:11
[Paper Review] Forecasting financial signal for automated trading: An interpretable approach
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Forecasting financial signal for automated trading: An interpretable approach
24:50
[Paper Review] A new LSTM based reversal point prediction method using upward/downward
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] A new LSTM based reversal point prediction method using upward/downward
28:05
[Paper Review] Automated cryptocurrency trading approach using ensemble deep reinforcement learning
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Automated cryptocurrency trading approach using ensemble deep reinforcement learning
40:14
[Paper Review] A novel Deep Reinforcement Learning based automated stock trading system
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] A novel Deep Reinforcement Learning based automated stock trading system
30:06
[Paper Review] Stock market forecasting using a multi-task approach integrating long short-term
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Stock market forecasting using a multi-task approach integrating long short-term
44:42
[Paper Review] Series decomposition Transformer with period-correlation for stock market index
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Series decomposition Transformer with period-correlation for stock market index
41:50
[Paper Review] A stock time series forecasting approach incorporating candlestick patterns
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] A stock time series forecasting approach incorporating candlestick patterns
56:56
[Paper Review] Stockformer: A price–volume factor stock selection model based on wavelet transform
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Stockformer: A price–volume factor stock selection model based on wavelet transform
49:18
[Paper Review] Stock return prediction with multiple measures using neural network models
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Stock return prediction with multiple measures using neural network models
59:10
[Paper Review] An interpretable intuitionistic fuzzy inference model for stock prediction
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] An interpretable intuitionistic fuzzy inference model for stock prediction
41:39
[Paper Review] Enhanced stock price forecasting through a regularized ensemble framework with GCNs
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Enhanced stock price forecasting through a regularized ensemble framework with GCNs
41:45
[Paper Review] Exploiting experience accumulation in stock price prediction with continual learning
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Exploiting experience accumulation in stock price prediction with continual learning
25:49
[Paper Review] Transformer-based attention network for stock movement prediction
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Transformer-based attention network for stock movement prediction
27:09
[Paper Review] Prediction of index futures movement using TimeGAN and 3D-CNN:Empirical evidence
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Prediction of index futures movement using TimeGAN and 3D-CNN:Empirical evidence
24:34
[Paper Review] MWDINet: A multilevel wavelet decomposition interaction network for stock price
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] MWDINet: A multilevel wavelet decomposition interaction network for stock price
47:35
[Paper Review] Stock price momentum modeling using social media data
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Stock price momentum modeling using social media data
53:02
[Paper Review] The application research of neural network and BP algorithm in stock price pattern
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] The application research of neural network and BP algorithm in stock price pattern
38:11
[Paper Review] Attention-based CNN–LSTM for high-frequency multiple cryptocurrencytrend prediction
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Attention-based CNN–LSTM for high-frequency multiple cryptocurrencytrend prediction
23:29
[Paper Review] DTSMLA: A dynamic task scheduling multi-level attention model for stock ranking
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] DTSMLA: A dynamic task scheduling multi-level attention model for stock ranking
42:12
[Paper Review] Predicting the highest and lowest stock price indices
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Predicting the highest and lowest stock price indices
56:23
[Paper Review] Stock price prediction using deep learning and frequency decomposition
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Stock price prediction using deep learning and frequency decomposition
33:52
[Paper Review] Multi-scale contrast approach for stock index prediction with adaptive stock fusion
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Multi-scale contrast approach for stock index prediction with adaptive stock fusion
20:48
[Paper Review] Quantitative stock portfolio optimization by multi-task learning risk and return
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Quantitative stock portfolio optimization by multi-task learning risk and return
19:57
[Paper Review] Stock market index prediction using deep Transformer model
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Stock market index prediction using deep Transformer model
29:25
[Paper Review]Deep reinforcement learning based on transformer and U-Net framework for stock trading
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review]Deep reinforcement learning based on transformer and U-Net framework for stock trading
34:59
[Paper Review] Deep learning-based feature engineering for stock price movement prediction
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Deep learning-based feature engineering for stock price movement prediction
30:59
[Paper Review] Cross-modal scenario generation for stock price forecasting using WGAN and GCN
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Cross-modal scenario generation for stock price forecasting using WGAN and GCN
37:18
[Paper Review] Shortlisting machine learning-based stock trading recommendations
순천향대학교 AI·빅데이터학과 ADS 연구실
[Paper Review] Shortlisting machine learning-based stock trading recommendations
21:38