Analyzing the relationship between stock market investments and inflation in the United States and Canada from 1980 to 2023
Bibliographic record
Abstract
This thesis explores the intricate relationship between stock market investments and inflation within the United States and Canada, spanning an extensive period from 1980 to 2023. Employing robust linear regression models, this study scrutinizes the interplay between the Consumer Price Index (CPI) and three prominent stock market indices: NASDAQ, S&P (Standard & Poor's 500), and Dow Jones. The primary objective is to uncover the underlying dynamics that connect economic indicators with stock market performance.The findings reveal a profound and nuanced correlation between stock market dynamics and inflation, resonating across both the United States and Canada. The research not only identifies shared patterns but also distinct variations in how specific stock market indices influence inflation dynamics. While the fundamental concept of a positive relationship between stock market indices and inflation remains a consistent thread, the extent and specific impact of each index exhibit diversity.Moreover, the study provides substantial evidence through consistently high R-squared values, indicating that fluctuations in the selected stock market indices significantly contribute to the variability in CPI. Noteworthy is the positive association between NASDAQ and CPI, emphasizing the notable influence of technology-driven and growth-oriented stocks on inflation. Similarly, the comprehensive representation of the S&P index corresponds with heightened consumer prices, while Dow Jones, with a more modest effect, contributes to shaping inflation dynamics.The robust statistical foundation of the models is underscored by their substantial F-statistics and reasonably low Mean Squared Error (MSE) values, reaffirming the accuracy and reliability of the employed linear regression models.In summary, this thesis enriches the comprehension of the intricate interplay between stock market investments and inflation across American and Canadian markets. The insights derived from this research carry practical implications for investors, policymakers, and researchers, offering valuable perspectives on the interconnectedness of financial markets and economic indicators. Furthermore, this study emphasizes the necessity for sophisticated analytical approaches when assessing the influence of specific stock market indices on consumer prices across various decades. Future research avenues may delve into sector-specific influences within these indices and consider the potential involvement of additional economic variables, further enhancing our understanding of this multifaceted relationship.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".