Notice bibliographique
Résumé
Recent technological advancements have challenged financial markets. Academic researchers, regulators and market participants voice concerns that modern markets bear the negative externalities of such advancements. Specifically, they are concerned that today’s markets are becoming more fragile and unfair to less sophisticated traders. This work employs empirical methodology to test whether these concerns are justified. This thesis contains three essays:\nThe first essay studies whether modern markets become less liquid during intraday extreme price movements (EPMs). When a price moves in a certain direction, liquidity providers face two opposing incentives. The first incentive is to stay in the market to accumulate more inventory in anticipation of a price reversal. The second incentive is to withdraw due to capital constraints, inventory and adverse selection risks. Using data from Canadian and U.S. markets, I find that the former incentive is stronger during intraday EPMs. This finding alleviates concerns that prices are subject to periods of extreme volatility due to systematic liquidity withdrawals. Contrary to these concerns, liquidity providers appear sufficiently incentivized to dampen intraday volatility.\nThe second essay examines the activity of a specific type of modern liquidity providers – high frequency traders (HFTs) – around EPMs. I find that, on average, HFTs provide liquidity during EPMs by absorbing imbalances created by non-high frequency traders (nHFTs). Yet HFT liquidity provision is limited to EPMs in single stocks. When several stocks experience simultaneous EPMs, HFT liquidity demand dominates their supply. There is little evidence of HFTs causing EPMs.\nThe third essay studies whether recent technological advancements result in higher costs for less sophisticated traders. In modern markets, trading firms spend generously to gain a speed advantage over their rivals. The marketplace that results from this rivalry is characterized by speed differentials whereby some traders are faster than others. Is such a marketplace optimal? To answer this question, I study a series of exogenous weather-related episodes that temporarily remove the speed advantages of the fastest traders by disrupting their microwave networks. During these episodes, adverse selection declines accompanied by improved liquidity and reduced volatility. Liquidity improvement is larger than the decline in adverse selection consistent with the emergence of latent liquidity and enhanced competition among liquidity suppliers. The results are confirmed in an event-study setting, whereby a new business model adopted by one of the technology providers reduces speed differentials among traders, which results in liquidity improvements.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».