The Test of the Efficiency of the Saudi Financial Capital Markets at Weak Form: An Empirical Study of the TASI Index and Sub-Indices of the Saudi Market
Bibliographic record
Abstract
The aim of this paper is to examine the normality of the destitution of the main Saudi TASI Index and the other sub-indices, as well as to test the random walk hypotheses of the Saudi TASI index and the random walk hypotheses of the main sectors index and the sub-indices in Saudi capital market. It investigates the weak form efficiency of the Saudi capital market. The study highlights the importance of structuring in the Saudi market, with regard to the redistribution of some companies in other sectors, in addition to the increase in the number of companies listed in the Saudi Tadawul market, where the study included larger and longer sectors in terms of the time period. An as extension, it requests the reconsideration of some previous studies, some of which proved the efficiency of the Saudi market and others which proved the inefficiency of the Saudi market at the level of low efficiency. The study test includes daily indices return from December 2002–October 2010. The results show that return series of all Saudi market indices have non-normal distribution. This paper applied four tests to examine the study’s hypotheses. The Shapiro Wilk test of normality of the Skewness/Kurtosis applied and the other tests for RWH Box-Ljung, the other test one is parametric test Augmented Dicky-Fuller test and the other test is non-parametric test Phillips-Perron test and Run test. The result that was found states that the Saudi market’s indices are inefficient in the weak form hypotheses.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".