Impact of energy prices on equity markets: the analysis of different market conditions
Bibliographic record
Abstract
Energy prices have been considered to be an essential component in the development of any country both economically and financially. After the global financial crisis, the upsurge in prices for different kind of commodities has gained the attention of policymakers to the part of investors ' action in financial markets. These rises and fall in the prices significantly influence the relationship between energy prices and equity market prices around the globe. In connection with this, the present research aims to examine the effect of different energy prices (such as oil, heating oil, natural gas and gasoline) on the prices dynamics of the equity market in top energy-consuming countries. To attain this objective, the current research collects time-series data of the top five energy-consuming countries including the United States of America, China, India, Japan and Canada. The study used the daily time-series data from 1st January 1996 to 30th November 2020. The study applied different linear and nonlinear estimation to confirm the association between different energy prices and equity market prices. The findings of nonlinear estimation (i.e. quantile cointegration) confirmed a significant nonlinear connection between different energy prices and equity market in top energy-consuming countries. Furthermore, the findings of quantile-on-quantile regression confirmed that the effect of all energy prices are mostly positive on equity returns except the oil prices returns which affect negatively equity returns during normal market conditions. Moreover, on the extreme tails, the effect is strong and weak positive for all energy prices returns in the USA and Canada. On the other hand, China and Japan have a similar case, the energy prices show a positive and significant impact on equity returns mostly in the normal market conditions and also in bearish and bullish market conditions. In the case of India, the effect of oil, natural gas and heating oil (gasoline and energy portfolio) are negative (positive) on equity returns during normal market conditions. However, the effect of all energy prices returns are strong positive on equity returns during bearish and bullish market conditions. On the other hand, the outcomes endorse that the influence of different energy prices returns on equity price volatility are different across the quantiles and the maximum fluctuation in the relationship can be seen on extreme tails of the conditional distribution which is bearish and bullish market conditions. In the case of the USA, India and Canada, the effect of all energy prices are mostly positive on equity volatility except the energy portfolio returns which affect negatively equity volatility during normal market conditions. Moreover, on the extreme tails, the effect is strongly positive and negative for all energy prices returns. On the other hand, China and Japan have a similar case, the energy prices show a positive and significant impact on equity volatility mostly in the normal market conditions and also in bearish and bullish market conditions. The study recommends several policy implications to the investor and all for the top energy-consuming countries considering the relationship between energy prices and equity market prices.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".