Top Companies Ranking Based on Financial Ratio with AHP-TOPSIS Combined Approach and Indices of Tehran Stock Exchange - A Comparative Study
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
This paper aims to explore the relationship between ranking of the top-50 listed companies on Tehran Stock Exchange (TSE) for the years 2009- 2011 in terms of their liquidity, operation, leverage and profitability ratios using combined AHP-TOPSIS approach and the ranking made by the stock exchange. Ranking of the companies on the stock exchange is done based on their state in terms of the above ratios and it serves as a criterion for decision making on investment. Using a questionnaire, views of experts, scholars and the capital market authorities on the effect of financial ratios were gathered and then using AHP- TOPSIS technique the companies were ranked based on these ratios. The obtained results from the Spearman Test show a weak correlation between the rankings based on AHP-TOPSIS approach and the ranking of the stock exchange. Finally, our results indicate that financial ratios of the top stock exchange selected companies are crucial factors in investment and ranking. This paper contributes to a signaled need for investigation on how and why financial statements of top listed companies cannot be regarded as a critical factor in ranking and decision making on investment.
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 | 0.002 | 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