Multivariate Causality between Stock price index and Macro variables: evidence from Canadian stock market
Bibliographic record
Abstract
Currently, the investor considers monetary indicators a vital factor when making any investment in equity prices. This research aim to find the long-run relationship between stock returns (DLSP) of Canada and monetary indicators as the exchange rate (LEXC), the interest rate (LINT), and inflation rate (INF). We consider T=232 observations for each variable from January 1999 to April 2018. From the Johansen cointegration approaches, there is no long-run association between stock prices and monetary indicators. Results of the Granger causality tests have demonstrated the unidirectional causation from the stock return to Inflation rate and to Exchange rate growth. While Results of Toda and Yamamoto Wald tests have demonstrated a bidirectional causal relation between stock price and consumer price index and a unidirectional causation from stock price to the interest rate and to the exchange rate growth. Based on IRFs, Inflation rate is shown to be inversely related to stock returns. Thus, it is concluded that the predictability of Canadian stock return relies only on the variations of inflation rate.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".