About Me

The Analyst Behind
the Data

Independent crypto market analyst operating from London’s financial district. I bridge the gap between raw on-chain metrics and coherent market narratives.

Cedric Quillmere — Independent On-Chain Intelligence Analyst

Extended Biography

I operate from London’s financial district, where proximity to institutional capital flows shapes my distinctive approach to digital asset research. With a background in quantitative finance and data engineering, I bridge the gap between raw on-chain metrics and coherent market narratives.

My analytical framework integrates three layers: macro liquidity conditions — central bank policy, dollar strength, yield curve dynamics — derivatives market microstructure including funding rates, open interest topology, and options skew — and on-chain behavioural data such as exchange flows, whale wallet clustering, and miner economics. This multi-dimensional lens allows me to identify inflection points that single-metric analysts routinely miss.

My editorial work is recognised for its precision and absence of hype — a deliberate departure from the noise-heavy crypto media landscape. My long-form analyses dissect market cycles with the rigour of academic research whilst remaining accessible to active traders. I have contributed market intelligence to institutional research desks and am frequently cited by crypto-native media outlets for my derivatives positioning commentary.

When I am not tracking order flow, I explore algorithmic trading systems and contribute to open-source on-chain analytics tooling. I hold an MSc in Financial Engineering from the University of London, with a focus on derivatives pricing and stochastic modelling, and a BSc in Mathematics and Computer Science from the University of Bristol.

How I Work

Analytical Methodology

Multi-Layer Framework

Every analysis I produce integrates at least three data layers. I never rely on a single metric or indicator in isolation.

  • 01Macro liquidity conditions — DXY, M2, central bank policy, yield curve dynamics
  • 02Derivatives microstructure — funding rates, OI topology, options skew, basis trade dynamics
  • 03On-chain behavioural data — exchange flows, wallet clustering, miner economics, HODL Waves

Research Principles

I hold myself to a strict set of editorial principles that differentiate my work from the broader crypto media landscape.

  • Every claim backed by verifiable on-chain or market data
  • Probabilistic language over deterministic predictions
  • Uncertainty acknowledged explicitly — no speculation presented as conviction
  • Data sources attributed in every piece

Professional Background

Career Timeline

2024 – Present

Independent On-Chain Intelligence Analyst

Self-employed, London

2021 – 2024

Senior Crypto Research Analyst

Institutional digital asset research desk

2019 – 2021

Quantitative Data Analyst

Fintech / algorithmic trading firm

2017 – 2019

Junior Market Analyst

Traditional finance brokerage

MSc Financial Engineering

University of London

Focus: derivatives pricing, stochastic modelling

BSc Mathematics & Computer Science

University of Bristol

CFA Level II Candidate

Paused — pivoted to crypto full-time

Certified Blockchain Analytics Professional

CBAP

Python for Financial Analysis

Advanced coursework completed

Technical Stack

Tools & Technologies

Data Analysis

Python (pandas, NumPy, scipy), SQL, R

Visualisation

TradingView Pine Script, Plotly, D3.js, Matplotlib

On-Chain Tools

Dune Analytics, Nansen, Arkham Intelligence, Glassnode API

Derivatives

Deribit, Paradigm, Laevitas, Greeks.live

Automation

Custom Python bots for wallet tracking and alert systems

Publishing

Markdown, Notion, Substack, CMS platforms