Investigation of Co-Integration between Standard and Poor Index and Dow Jones Index in the New York Financial Market
Bibliographic record
Abstract
The study investigates the co-integration between (the S&P 500 index)and (Dow Jones index) the DJIA by busing the method Engle-granger co-integration Test. The study use annual data from 1990 to 2016.The study examines the stability of the index of S&P 500 and DJIA using the E-views program through a unit root test. The study found that the indicators are unstable, but they become stable when taking the first difference. This condition integrates (the S&P 500 index) and (the DJIA index) during the long-term co-integration test. The analysis shows that there is a negative co-integration between the two variables. It should be emphasized that the short-term dynamic analysis showed a positive co-integration between both indexes. The study concluded that there is an urgent need to take into account the long-term negative co-integration between (the S&P 500 index) and (the DJIA index) by investors in the New York market. Also, the study considers short-term positive integration between (the S&P 500 index) and (DJIA index), which turns into a negative relationship in the long term when taking into account the markets linked with the New York market as a major global market and other international financial markets when making any financial investment. The result of this study could help users of major international financial markets in investment diversification to reduce risk.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".