Impact of energy prices on equity markets: the analysis of different market conditions
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».