I’m Sophia Lopez, lead researcher at Cryptophia Research.
I focus on liquidity, ETF flows, market structure, on-chain signals, institutional behaviour, self-custody, and the tools investors use to make better decisions.
Crypto markets are noisy by design. Price moves first, narratives arrive later, and most commentary confuses activity with demand. My work separates what matters from what is merely loud.
Why Cryptophia exists
Crypto information is abundant; dependable interpretation is not. Price moves are routinely explained after the fact, weak correlations are presented as causes, product features are confused with security guarantees, and promotional incentives can hide inside apparently objective reviews.
Cryptophia exists to slow that process down. I distinguish observation from inference, key control from asset control, activity from adoption, a low advertised fee from the full route cost, and a plausible scenario from a forecast.
Selected publishing
Research beyond Cryptophia
Selected essays by Sophia Lopez have also appeared in Coinmonks and The Capital on Medium. The links below point to live published work rather than contributor badges or submission permissions.
The Cryptophia Method
How I reach a judgment
Evidence first. Mechanism first. Judgment with clear conditions.
Primary sources
Start with filings, protocol documentation, official statements and direct datasets.
Observation
Separate what happened, where it is visible and what changed from the explanation.
Mechanism
Ask why the evidence should produce the claimed outcome: incentives, structure and constraints.
Counterargument
Test the strongest opposing view, alternative explanations and missing evidence.
Invalidation
Define the thresholds, evidence or conditions that would change the view.
Judgment
State the base case, confidence, implications and what the reader should watch next.
What I research
I work across three connected areas:
- Self-Custody & Security: hardware signers, backups, recovery, permissions and transaction security—evaluated by the failure modes they reduce and the dependencies they add.
- Markets, On-Chain & Risk: liquidity, leverage, stablecoins, market structure and blockchain analytics—separating observable events from labels, transformations and causal stories.
- Platforms & Research Tools: exchanges, analytics platforms, portfolio tools and tax software—reviewed around legal entity, data quality, methodology, exit routes and total operating cost.
Original research should be reusable
I prioritize decision tools that another reader or researcher can apply independently. Current frameworks include the On-Chain Metric Definition Framework, Hardware Wallet Threat Model Matrix, Crypto Exchange Total Cost Checklist, Crypto Tax Record Audit Template and Crypto Risk Assessment Worksheet.
Evidence in practice
Sample research objects
The point is not to decorate an argument with data. It is to use the research object that can actually test the claim.
ETF flows
Flow reconciliation
Price move ≠ ETF net flow
A flow claim needs fund creations and redemptions, source coverage, definition and an as-of date—not a proxy such as price or AUM.
Self-custody
Hardware wallet threat model
Mitigated ≠ eliminated
A useful comparison maps which failure modes a design reduces, which dependencies it adds and what residual risk remains.
Execution cost
Exchange total-cost checklist
Lowest fee ≠ lowest total cost
The cheapest route depends on the full execution path, not one advertised fee in isolation.
Framework examples only. Published quantitative research should state the source, definition and as-of date.
The research standard
- Use primary or direct sources wherever they are available.
- State the instrument, venue, period, definition and cut-off behind material market or on-chain data.
- Show the assumptions behind calculations, classifications and derived charts.
- Separate verified facts, interpretation and scenario analysis.
- Identify failure modes, residual risk and recovery paths before assigning a ranking.
- Disclose material conflicts, holdings and affiliate relationships.
- Correct material mistakes openly and change conclusions when the evidence changes.
What readers should not expect
Cryptophia does not sell guaranteed returns, publish paid conclusions, or describe a token, wallet or platform as safe merely because it is popular or its price has risen. Documentation-led research is never presented as hands-on testing. Research is educational—not personal financial, legal, tax or security advice—and every reader remains responsible for independent verification and decisions.
Independence and affiliate revenue
The publication may earn commissions when readers use clearly marked affiliate links. That revenue supports research and operating costs. A commercial relationship cannot buy a positive rating, suppress a material risk, determine inclusion or change the evidence standard.
Read How We Research, browse Research Notes, use Press & Research Resources for citation-ready materials, and review the Affiliate Disclosure and Legal Disclaimer.