Application of Market Timing Theory: Evidence from Canadian Firms
Bibliographic record
Abstract
Internal and external finance are the two primary forms of funding for businesses. Internal financing is derived from retained profits, while external financing may come through borrowing money or the issuance of stocks. Businesses utilize it constantly to grow and stay alive, so the choices they make about finance are crucial. Market timing is vital for determining the appropriate financial structure for a company's success because volatility in market valuation greatly affects the capital structure. Capital structure requires a decision-making tactic that is an art to tackle complex situations. Modigliani and Miller started this ground-breaking study on capital structure in the field of corporate finance in 1958. After that, several theories were developed, but one of those theories was the market timing theory of capital structure, which explains that firms issue new stock when their share price is overvalued and repurchase shares when their share price is undervalued. These price fluctuations of equity will affect corporate financing decisions and ultimately corporate capital structures. The goal of this study is to test the applicability of market timing theory in the context of Canadian firms; thus, the data have been collected from the FINVIZ Stock Screener for the period (2022) and analyzed by a generalized linear model technique through the EViews 13. The research concludes that the market-to-book ratio has a statistically significant negative effect on market leverage as well as book leverage.
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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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.014 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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".