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(Re-)Imag(in)ing Price Trends
We reconsider trend-based predictability by employing flexible learning methods to identify price patterns that are highly predictive of returns, as opposed to testing predefined patterns like momentum or reversal. Our predictor data are stock-level price charts, allowing us to extract the most predictive price patterns using machine learning image analysis techniques. These patterns differ significantly from commonly analyzed trend signals, yield more accurate return predictions, enable more profitable investment strategies, and demonstrate robustness across specifications. Remarkably, they exhibit context independence, as short-term patterns perform well on longer time scales, and patterns learned from U.S. stocks prove effective in international markets.
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| PSB lt.dasar - Pascasarjana (Koleksi Majalah) | 1 |
| Penerbit | USA: The American Finance Association 2023 |
|---|---|
| Edisi | Volume78, Issue 6 December 2023 Pages 3193-3249 |
| Subjek | Investments Stock markets |
| ISBN/ISSN | 1540-6261 |
| Klasifikasi | NONE |
| Deskripsi Fisik | - |
| Info Detail Spesifik | The Journal of Finance |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas |