Pulse
Regime-Aware Research Architecture
PULSE is a regime-aware quantitative research framework developed to analyse the structural behaviour of liquid equity index markets through probabilistic modelling, factor decomposition, and adaptive regime classification.
Understanding market behaviour through probabilistic regime analysis.
Developed alongside ongoing doctoral research at the University of York, the framework examines how market behaviour changes across distinct volatility, momentum, and participation environments. Rather than treating markets as a single continuous process, PULSE seeks to identify the prevailing regime and evaluate how underlying characteristics evolve as conditions change.
Modelling
The framework produces analytical observations describing market structure and behavioural conditions. It does not generate recommendations, investment advice, trading instructions, or personalised financial guidance.
Framework Characteristics:
• Regime-aware analytical architecture
• Probabilistic modelling framework
• Multi-factor decomposition engine
• Adaptive market-state classification
• Structured research outputs
• Institutional analytical orientation
• Developed through active doctoral research
Outputs
The framework combines market-state classification, probabilistic inference, signal decomposition, and performance attribution within a structured research architecture designed for institutional analytical environments.
Research outputs may include:
• Market regime classification
• Momentum condition assessment
• Probabilistic state-transition analysis
• Signal persistence evaluation
• Structural asymmetry identification
• Multi-factor decomposition outputs
• Regime-conditioned performance attribution
Context
PULSE forms part of Bridgholds' broader research programme examining regime-aware momentum frameworks, volatility-state identification, and adaptive systematic methodologies for liquid equity index markets.
All outputs are produced for research, informational, and methodological purposes only.
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The Pulse pipeline is a structured research architecture that transforms raw market data into layered analytical outputs through sequential modelling stages.
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The process comprises data ingestion, regime classification, model generation, structural validation, and performance attribution under controlled research conditions.
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Each stage evaluates methodological consistency and structural robustness across market environments, producing analytical outputs that describe behaviour rather than prescribe action.
optimised at VIKING
VIKING is the University of York’s national high-performance computing infrastructure, supporting large-scale quantitative modelling, statistical simulation, and machine learning workloads across academic research programmes.
The platform provides the computational foundation for Bridgholds framework development and testing.
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134 compute nodes powered by AMD EPYC™ processors
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96 CPU cores and 512GB memory per standard node
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Dedicated high-memory nodes with up to 4TB RAM
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60 NVIDIA GPUs, including A40 and H100 architectures
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Over 1.7PB high-performance storage capacity
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100Gb/s low-latency interconnect infrastructure
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134 compute nodes: each with 96 CPU cores per node (two processors each with 48 cores), 512GB memory, and AMD EPYC3 7643 processor generation
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Three high memory nodes: one with 4TB and two with 2TB memory
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60 graphics processing units (GPU): 48× NVIDIA A40 and 12× NVIDIA H100
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Over 1.7PB storage: 1.5PB scratch space and 215TB usable NVMe
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100 Gb/s interconnect: with Intel omni-path architecture (OPA)
Time for Action
Pulse is offered on a subscription basis, which can be canceled anytime. Check our FAQ section if you still have any doubt, or feel free to contact us.
