Invesco QQQ Trust Series 1 (QQQ)
Deep learning enables accurate time series forecasting by capturing complex time dependencies through neural networks' innate understanding of time relationships between data points and interpolation in high-dimensional spaces using continuous activation functions.
| Dataset | Input Feat. | AI | Output | Short Forms |
|---|---|---|---|---|
| Daily QQQ historical data from July 13, 2007 to July 14, 2023. | 'date', 'open', 'high', 'low', 'close', 'volume' | PyTorch Forecasting with NHiTS for multi-scale interpolation and synchronized frequencies. Evaluated with MAE, SMAPE, MQF2DistributionLoss, and QuantileLoss. GPU accelerated. | Predictive time series data for QQQ from July 17, 2023 to August 11, 2023. | Actual Closing Price (ACP), Predicted Closing Price (PCP), Percent Difference (% diff) = [|ACP-PCP|/(ACP+PCP)]*100 |
Comparative Table
17 July to 11 August 2023
| Date | ACP | PCP | % diff |
|---|