An Analytical Study of the Effect of Inflation on Stock Market Returns
Bibliographic record
Abstract
<span lang="EN-IN">Inflation means a persistent change in the price level of goods and services in an economy. It is generally measured in the consumer price index (CPI) or retail price index (RPI). Inflation reduces the purchasing power of a country's currency, as we need more units of currency over time to buy the same goods and services. The current empirical paper entitled “relationship between inflation and stock market evidence from selected global stock markets” have been undertaken with an intention to investigate the relationship between inflation and stock returns of the chosen economies. In order to realize the stated objectives, the researchers have collected the monthly data 2000 to 2017 for selected indices. In the first phase, log returns were computed and it has been tested for the existence of unit root in the distribution. In the second phase, we ran Pearson correlation coefficient for the collected data to find out the association between the inflation and stock returns. Majority of the chosen indices recorded a negative </span><span lang="EN-IN">coefficient with the dependent variable. </span><span lang="EN-IN">For India, Austria, Belgium, Canada, Chile, China, France, Ireland we found a negative coefficient. However, Brazil </span><span lang="EN-IN">Indonesia, Japanese, Mexico, Spanish and Turkey reported a positive coefficient. </span><span lang="EN-IN">Current study clearly throws light on the effect of inflation on the stock market returns, therefore; it can help the market participants such as traders, fund managers, and investors to make good portfolio decisions based on the information about expected inflation and unexpected inflation. The study confirms that there exists a significant relationship between the stock returns and inflation for Australian, Belgium, Canadian, Chilean, Chinese, French and Irish stock benchmark indices. Firms can take this one has a clue to adjust their reported profits by raising the prices. The policymakers can employ contractionary policy to reduce the supply of money by offering a low interest rate on t bills, increasing the interest rates (bank rate policy) and increasing the cash reserve ratios which in turn reduces the lending capacity of the banks.</span>
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How this classification was reachedexpand
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 | 0.004 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".