Simulation of Canadian S&P/TSX Composite Index for the First 20 Years in the 21st Century with Random Walk Model
Bibliographic record
Abstract
The Canadian S&P/TSX Composite Index is a capitalization-weighted equity index that records the stock performance in Toronto Stock Exchange (TSX), which is the primary stock exchange in Canada.The S&P/TSX is closely monitored by investors and becomes a barometer for the health of the Canadian economy.The random walk model is an important tool to prove or disprove the efficient market hypothesis (EMH).Generally, the use of random walk model to test this hypothesis is conducted using statistical tests.Recently, we conducted a series of studies to use the random walk model to directly simulate/fit the major stock indices around the world.As a part of such an effort, we use the random walk model to simulate the S&P/TSX for the first 20 years in the 21 st century in this study.The results show that the random walk model can satisfyingly simulate the S&P/TSX trend for the long period, but fails for short periods.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".