In crypto research, access to data isn’t the problem; quality is. Crypto research is exploding. Universities, PhD candidates, and independent analysts all want to publish groundbreaking insights on how markets work or propose new DeFi innovations.
But there’s one critical challenge few talk about: the data.
It’s messy. Incomplete. Hard to use.
One academic team shared how their study on trend detection collapsed:
- One data source stopped midway.
- Another had big gaps.
- A third? Used a different format.
Eventually, the project got stuck, not because the idea wasn’t great, but because the data couldn’t support it.
For too many researchers, this is the norm.
You can’t analyze markets with confidence if your inputs are broken. You need a unified, research-ready data source.
Whether you're an academic, an independent quant, or a post-PhD researcher without institutional backing, you've likely faced the same issues our customers report:
“I spent more time cleaning the data than running the analysis.”
“The APIs I used didn’t align across exchanges, nothing was consistent.”
“I couldn’t reproduce my results three weeks later.”
At CoinAPI, we’ve listened. And we’ve built for you.
Here’s how.
Why Academics struggle with crypto market data
The crypto space generates massive amounts of data across thousands of assets and hundreds of venues, but most sources are fragmented, noisy, or poorly documented. For academic use, this creates serious challenges:
❌ Missing ticks or corrupted order books
❌ Inconsistent symbol mappings between exchanges
❌ Aggregated data with no transparency
❌ APIs that break mid-research
CoinAPI addresses this by providing normalized, historical, and real-time crypto data across 370+ exchanges delivered via flat files, REST, or WebSocket APIs. When needed, every dataset includes precise timestamps, clean schemas, and full order book depth.
Structured research: Your work deserves a foundation
The first bottleneck most researchers face isn’t computing or math, it’s data chaos.
Crypto markets are fragmented. One exchange calls it BTC-USD, another says XBT-USD. Time intervals aren’t aligned. Depth data comes in one format here, another there. Most APIs? They weren’t built for structured academic workflows.
That’s why we built CoinAPI to serve as a research-grade data platform, not just a dev playground.
What researchers get:
- Normalized asset identifiers and symbol mapping
- Schema consistency across 370+ venues
- Unified timestamp formats for precise time-series alignment
- Full support for CSV/FlatFile bulk downloads and structured JSON responses
“I finally stopped duct-taping multiple APIs together. CoinAPI gave me a stable base to build structured datasets.”
Quantitative Finance PhD candidate, Europe
Whether you're studying price discovery, liquidity fragmentation, or cross-chain correlations, structured data unlocks structured thinking.
Granular data: Go beyond surface-level analysis
Every candlestick hides thousands of micro-decisions: quotes, cancellations, fills, slippage.
If you’re only analyzing OHLCV, you’re studying the output, not the behavior.
CoinAPI gives you granular access to what happens in the market.
Researchers can access:
- Tick-by-tick trade data with full metadata
- L2 and L3 order book snapshots and deltas
- Millisecond-level quote frequency
- Trade and quote sequencing for impact analysis
“I was finally able to model trade execution dynamics across multiple exchanges. That just wasn’t possible with public APIs.”
Postdoctoral researcher, machine learning + market microstructure
One research team used CoinAPI data to simulate execution slippage across 5 exchanges over 6 months, modeling different liquidity tiers and detecting how certain altcoins behave under wash trading pressure.
That’s not data you can scrape from CoinGecko.
The importance of reproducibility in crypto research
Publishing results is one thing. Publishing reproducible methods is another.
Too many crypto research papers, even peer-reviewed ones, rely on opaque sources or privately collected datasets. That makes it nearly impossible to validate findings or expand on them.
We believe that transparency in data access is the foundation of credible research.
Here’s how CoinAPI helps:
- Clear, versioned documentation of all endpoints
- Transparent normalization logic
- Public schemas for every dataset
- Static dataset exports for long-term archival access
“When we submitted our paper, reviewers didn’t question the data source once. The CoinAPI dataset and documentation spoke for themselves.”
Blockchain research lab, North America
Your methodology deserves to be trusted. Clean, documented data makes that possible.
Academic use cases
Let’s look at 3 ways academic researchers are using CoinAPI today.
Use Case 1: Order book analysis for liquidity modeling
Use Case: A research group at a European university is analyzing the price impact of large trades on BTC/USDT order books across multiple exchanges.
How CoinAPI Helps:
- Tick-by-tick trade data with millisecond timestamps
- Full L2 order book snapshots for depth reconstruction
- Consistent symbol mapping across Binance, Kraken, Coinbase, and others
Research Output:
A peer-reviewed paper quantifying slippage, spread decay, and liquidity fragmentation across the top 10 centralized exchanges.
Use Case 2: Backtesting arbitrage strategies with historical data
Use Case: A PhD candidate is evaluating the performance of a momentum-based crypto arbitrage strategy over the past 3 years.
How CoinAPI Helps:
- Access to flat file datasets with historical tick data
- Clean, gap-free OHLCV and quote streams
- Reproducible tests thanks to schema stability and versioned datasets
Research Output:
A thesis chapter demonstrating risk-adjusted returns of inter-exchange arbitrage strategies using real market conditions and execution simulation.
Use Case 3: Monitoring stablecoin flows across chains
Use Case: A policy-focused researcher is tracking the growth of stablecoin usage across different blockchain ecosystems to evaluate systemic risk.
How CoinAPI Helps:
- Normalized volume data across multiple assets and chains (e.g., USDT on Tron vs Ethereum)
- Cross-chain analytics via standardized schemas
- Real-time anomaly detection for flow surges
Research Output:
A policy report mapping stablecoin volume spikes to geopolitical events and exchange listings, used by a central bank research team.
Why CoinAPI is academic-ready (vs public APIs)
Academic institutions aren't the only ones pushing crypto research forward. Independent analysts, data scientists, and early-career researchers often face similar roadblocks, and many of them choose CoinAPI to break through.
Here are three common challenges we hear from users in the research space:
1. “Where can I get complete, reliable data for my research?”
Many users come to us after struggling with fragmented or incomplete data from public APIs.
What they need is:
- Historical and real-time depth
- Consistent formats across exchanges
- Documentation that makes data usable
CoinAPI delivers this with normalized schemas, extensive historical archives, and access to real-time and tick-level data from over 370 venues.
2. “How do I make my research reproducible and shareable?”
For academic publishing or even posting a public methodology on GitHub, reproducibility is everything.
CoinAPI’s versioned datasets, consistent endpoints, and timestamped records allow researchers to:
- Build transparent workflows
- Share code that doesn’t break
- Validate results across teams or over time
3. “Can I apply ML, anomaly detection, or network models on this data?”
Advanced analytics require more than just price and volume. Researchers ask for:
- Depth of the book
- Trade sequencing
- Cross-asset relationships
Our customers are building models for alpha detection, volatility clustering, stablecoin flow, and more — all powered by clean, structured data that supports complex pipelines.
What Makes a Crypto Research Source Trustworthy?”
When it comes to crypto research, one of the most common questions we hear from users is: “What data can I trust?”
Here’s what most serious researchers look for:
- Consistent data across time and venues
- Precise timestamps for sequencing and latency modeling
- Clear documentation and versioning for reproducibility
- Transparency in how the data is generated or normalized
CoinAPI users tell us that these are non-negotiable when conducting credible research, whether for peer-reviewed publication or internal analysis.
Experienced researchers know that whitepapers can promise anything, but market behavior tells the truth.
Our users often ask:
- “Is this project being traded organically across exchanges?”
- “Are volumes real or inflated?”
- “Does the token have sustained liquidity, or just a pump-and-dump profile?”
Using CoinAPI’s normalized market data, researchers can:
- Compare real-time price and volume movements across multiple exchanges
- Evaluate trade frequency and book depth
- Detect unusual quote activity or coordinated volume spikes
These insights go far beyond social sentiment. They help filter hype from substance, a crucial step for anyone analyzing crypto projects.
Our research community consistently looks for tools that offer:
- Deep, structured market data (beyond just price)
- Easy export options for backtesting and modeling
- Strong documentation and consistent API behavior
- Transparent methodology and clean schemas
One of the most common pain points we hear?
“Other tools are fine for charts, but we need research-grade data we can trust.”
CoinAPI addresses these needs by providing programmatic access to:
- Tick-by-tick trade data
- Full L2 and L3 order book snapshots
- Timestamped OHLCV and quote feeds
- A normalized schema across 370+ venues
Get started: Access academic datasets from CoinAPI
CoinAPI isn’t just built for traders, it’s designed for anyone who needs high-integrity, granular crypto data. Academic institutions choose CoinAPI because it offers:
âś… Transparent, well-documented schema
âś… Historical datasets for long-term analysis
âś… Tick-level granularity across trades, quotes, and order books
âś… One API for 370+ exchanges (no patchwork integrations)
âś… Support for CSV, REST, and WebSocket access
Whether you’re publishing papers, running simulations, or building academic dashboards, CoinAPI helps researchers focus on insights, not data cleanup.
Final thought: We see you, researchers
You’re trying to build something rigorous in a fast-moving, noisy, often hype-driven ecosystem.
And too often, the infrastructure makes it harder, not easier.
We built CoinAPI because we felt that pain too.
We saw the gap between academic needs and crypto tooling.
So, whether you're publishing to a journal, testing a model, or building an open research repo, these are the pillars that support you:
âś… Structured research because consistency matters
âś… Granular data because the signal lives in the details
âś… Transparent methodology because truth demands clarity
You bring the insight.
We’ll bring the infrastructure.
Want to Try It?
Because in research, your results are only as good as your data. And that data? It should be your strongest foundation, not your biggest risk.
Want to explore our flat files or access datasets for academic use?
👉 Get started with CoinAPI or request sample data today.
