Original Research
Every paper starts from an internal hypothesis and formal model design before implementation begins.
Research
Whitepapers &
Quantitative Analysis.
Merkava Labs research documents the full pipeline behind the systems: original model design, implementation discipline, out-of-sample validation, Monte Carlo stress work, robustness review and data-driven refinement before release.
Original research
Production-linked engineering
Whitepapers and methodology notes
Validated in Practice
Research is followed by out-of-sample validation, robustness testing and Monte Carlo-style stress work before release.
Refined from Data
Quantitative framing matters, but the final systems are also refined from cross-asset results and real implementation behavior.
Library
Research library.
Released papers are available now. Forthcoming papers stay visible until publication.
Synthetic Timeframe Architectures
A cross-disciplinary synthesis of timeframe ratio research across EMD, MSM cascades, wavelet analysis, Hurst scaling and signal theory, translated into a practical synthetic timeframe architecture for MT5 implementation.
Download PDFQuantum ZigZag: Beyond Retail
Advanced ZigZag research built around TDR volume analysis, Outside Bar logic and Smart L1 adaptation for higher-quality structure mapping.
Download PDFVector Consensus Divergence
A slope-based divergence framework designed to warn when price and multi-model consensus separate without relying on slower pivot-style confirmation.
Download PDFRegime Transition Mechanics
A research paper on how directional structure weakens, confirmation decays and transition states emerge before a full regime shift becomes obvious on chart.
Coming SoonCross-Asset Invariance
An exploration of what must remain stable for a trading model to transfer across FX, metals, indices and crypto without collapsing into market-specific overfit behavior.
Coming SoonResearch Access
Read the research behind the systems.
Research is where synthetic timeframe logic, consensus engineering and structure methodology are documented, then tied back to implementation, out-of-sample validation, Monte Carlo stress work and release discipline.