Quant research
Study price dynamics, market structure, and repeatable patterns across prediction venues.
Prediction-market quant research and information systems
Quant research and information systems for prediction markets.
Laplaxton focuses on quantitative research, trading support, and information discovery for prediction markets.
Focus
Research, trading support, and information discovery.
Trading support
Build data, signal, and monitoring systems that support research and execution.
Information discovery
Extract structure from noisy external information flows relevant to market prediction.
Signal View
Information asymmetry detection in a stylized oil prediction market.
Information asymmetry detection
Sequential residuals diverge from baseline by +2.7σ.
Anomaly window
Local jump intensity rises to 1.9x normal regime.
Probability shift
Posterior probability shifts by +11.8 pts.
Approach
Inspired by Laplace's Demon. Built with practical tools.
Laplaxton takes its name from Laplace's Demon, the thought experiment that a mind with perfect information could infer the future from the present. The name also reflects our aim to compress noisy market worldlines and information flows into quantized information particles.
In practice, we use machine learning, modern AI, and data engineering to extract structured signals for research, trading support, and information discovery.
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