The profitability of trading US stocks in Quarter 4 - evidence from trading signals emitted by SOI and RSI
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since the yields of trading stocks are affected by numerous elements, this study aims to explore whether the profitability of trading stock with the use of technical trading rules, such as Stochastic Oscillator Indicators (SOI) and Relative Strength Index (RSI), would matter in the fourth quarter of the year. By employing the data of Dow Jones 30 (DJI 30) and NASDAQ 100 (NDX100) from 2011 to 2020 and from 1991 to 2020, this study reports that investors applying SOI and RSI would have higher cumulative abnormal returns (CARs) in Quarter 4 as compared with those in Quarters 1–3, respectively. The revealed findings indicate that the quarterly effect should be taken into account by investors when trading DJI 30 and NDX100, the representative indices for US stock markets. More importantly, this study may contribute to the existing literature due to the rare discussion of this interesting issue in the past research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it