Book a Demo
Antoine Bouvet
Gray shield icon
Is this you?
Claim your profile.

Antoine Bouvet

Senior Rates Strategist

AS SEEN ON
insep.hal.science

Preston's Summary

Antoine Bouvet is a Senior Rates Strategist at ING. He specializes in rates, inflation, and strategies pertaining to the US and UK markets, often providing insights into the dynamic landscape of financial trends. Antoine's expertise is featured in notable publications such as HAL Inria.

Preston is the artificial intelligence that powers the Intelligent Relations PR platform. Meet Preston

Geo Focus

Coverage Attributes:

Beta
Data Driven: 50 %
Informative: 50 %

Themes Covered:

Not enough data icon

Not enough data

Most Recent Topics:

  • Rates
  • Spark
  • Inflation
  • US/UK Strategies

Pitching Insights

Antoine Bouvet's coverage primarily focuses on finance and economy, with an emphasis on rates, inflation, and investment analysis. The high percentage of cited data indicates a preference for fact-based reporting.

To effectively pitch to Antoine, consider providing data-driven insights into interest rates trends or in-depth analysis of economic indicators such as ISM reports and payrolls. Additionally, expertise in US and UK monetary policy strategies to combat inflation may be valuable for his coverage.

Given the nature of his articles' titles, it appears that Antoine delves deeply into financial market dynamics and is interested in detailed analyses rather than general overviews.

This information evolves through artificial intelligence and human feedback. Improve this profile .

Articles

HAL Inria

Distinctive Regulation Profiles of Stroke Mechanics Underlie Pacing and Discriminate 400 m Front-Crawl Performance

By: Antoine Bouvet, Nicolas Bideau

This study aims to identify the stroke mechanics regulations that underlie pacing optimization and differentiate final performance in the 400 m front-crawl across different performance levels. 157 all-out 400 m trials from trained to elite swimmers equipped with a sacrum worn IMU were analyzed. Hierarchical generalized additive models were fitted to describe (1) the technical predictors of final performance, through the interrelationships between averaged kinematics (i.e., stroke rate (SR), stroke length (SL), jerk cost (JC)) and mean speed, and (2), the profiles of pacing and associated stroke mechanics regulations leading to performance. These models depict both the common patterns shared by all swimmers and the specific group deviations by performance level (G1 -slowest- to G4 -fastest-) from population trends. All swimmers shared a reverse-J-shaped pacing (p < 0.001). The fastest swimmers reduce pacing variability with a relatively slower start, a minimized drop in speed in the middle of the race, and a greater end-spurt than the population trend (p < 0.05). Their stroke mechanics are effectively adapted to the requirements of such specific race sections, both through a U-shaped JC with higher magnitude (p < 0.001) and a continuous adaptation of the SR (p < 0.01) and SL (p < 0.01) combination. A high average SL (i.e., at least 1.50 m.stroke(-1)), coupled with an SR close to 70 strokes.min(-1) and maximizing stroke smoothness at race pace, are critical technical abilities for optimizing final performance. Technical training should prioritize the reduction of intra-cyclic acceleration variations at race pace as a key driver of 400 m performance development. The best performers lower pacing variability by amplifying the magnitude of kinematic regulations, particularly in terms of stroke smoothness management. Such underlying adaptations in stroke mechanics play a pivotal role in continuous speed control throughout the race. The findings of this study enhance the technical understanding of discriminative 400 m pacing skills for coaches and swimmers.

© 2026 Intelligent Relations