Advisory · Consulting
Consulting
Project-based engagements in securities finance, alternative data, and capital markets engineering. For institutions where deep domain knowledge — not generalist advisory — is what the problem requires.
About These Engagements
Domain expertise applied to problems that require it.
Tidal Markets takes on a select number of project-based consulting engagements each year. These are not generalist strategy assignments. They are narrow, technical problems in securities finance, alternative data, and capital markets infrastructure — the same problems our research program is built on.
The value is specificity. Building a lending signal from transaction data, evaluating a competitor’s backtest, migrating off a legacy securities finance platform, architecting a capital markets ML pipeline — these require someone who has done the exact work, not a consultant who has read about it.
Engagements are project-based. Scope, deliverables, and timeline are defined upfront. Contact us to describe the problem.
Practice Areas
Five areas of deep technical focus.
Each practice area reflects work that has been done in production — not proposed in theory.
Securities Lending Signal Development
Bespoke design and validation of proprietary signals derived from securities lending transaction data. Covers signal specification, statistical methodology, cross-sectional testing, sub-period decomposition, and production-grade documentation. For institutions seeking a proprietary edge rather than a licensed feed.
AWS ML Pipeline Architecture
Architecture and build of cloud-native machine learning pipelines for capital markets applications. Specializing in time-series rate forecasting, transformer-based deep learning models, and distributed processing workflows at institutional scale. Delivered on AWS using Step Functions, Glue, Lambda, and SageMaker.
Securities Finance System Integration
Integration, migration, and build of securities finance and collateral processing infrastructure. Covering legacy platform decommissioning, triparty agent connectivity, and end-to-end collateral eligibility processing. Platform experience spans the major institutional systems in the securities finance ecosystem.
Alternative Data Evaluation
Independent due diligence on alternative data vendors and their research claims. Covers methodology review, evidence quality assessment, backtest scrutiny, and signal orthogonality analysis. Designed for buy-side quant and risk teams evaluating new data sources — an independent second opinion before commercial commitment.
Data Engineering
Design and build of data pipelines, production database infrastructure, and automated reporting workflows for capital markets environments. From schema design and ingestion architecture to scheduled delivery and monitoring. Built for 24/7 institutional workloads with minimal operational overhead.
Sample Engagements
Recent work, anonymized by client.
Each engagement below reflects a completed project. Client names are not disclosed.
Architected and delivered an AWS ML pipeline for daily lending rate prediction across 5,000+ securities. Trained transformer deep learning models with attention mechanisms for time-series forecasting, achieving 70–90% directional accuracy. Engineered a model routing framework that assigns securities to optimal algorithms based on z-score classification.
Designed and implemented a non-cash collateral intraday and end-of-day ingestion system via external triparty agents. Programmed collateral eligibility and loan release processing logic, resulting in an $8 billion loan outstanding position at launch.
Led decommissioning of a legacy securities finance platform and transition to a new memo segregation workflow. Delivered business requirements, impact assessment, and master test plan in collaboration with Settlements, Fixed Income, and Stock Loan senior management.
Discuss an engagement.
Describe the problem. We will respond directly — no sales process, no intermediaries.
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