Level 2: Data Interpretation

Pierce & Pierce Academy

⏱️ Total time: ~3-4 hours across 8 modules
🔒 Access: Analyst subscription required ($29/month)
📊 Format: Text-based with data examples, charts, and practical exercises

What You'll Learn in Level 2

Now that you have institutional mental models (Level 1), learn to read the signals professionals monitor.

Level 2 teaches you what data to track and how to interpret it.

You'll learn to read:

  • ETF flows (composition, velocity, context—not just headline numbers)
  • Exchange reserves (distinguishing custodial shifts from accumulation)
  • Corporate treasuries (why MicroStrategy buys barely move price)
  • Government actions (sovereign flows are the most impactful forced flows)
  • On-chain metrics (which ones predict anything vs which are noise)
  • Funding rates + Open Interest (mapping leverage and liquidation risk)
  • Liquidation cascades (why $500M creates -3% or -15% depending on liquidity)
  • Sentiment vs Positioning (Fear & Greed is useless; positioning reveals truth)

By the end of Level 2:

  • ✅ You'll read Farside ETF flow data and know if it's bullish/bearish/neutral
  • ✅ You'll use Coinglass liquidation heatmaps to predict cascade zones
  • ✅ You'll interpret exchange reserve changes correctly (not just "outflow = bullish")
  • ✅ You'll track funding rates and Open Interest like a derivatives desk
  • ✅ You'll know which on-chain metrics matter vs which are astrology

Prerequisites

You must complete Level 1 before starting Level 2.

Level 2 builds directly on the mental models from Level 1:

  • Module 5 (ETF Flows) requires understanding forced vs willing flows
  • Module 10 (Funding + OI) requires understanding spot-derivatives arbitrage
  • Module 11 (Liquidation Cascades) requires understanding liquidity depth

If you haven't completed Level 1 yet: Go to Level 1 →

Access Level 2

Level 2 requires an Analyst subscription ($29/month).

Analyst subscription includes:

  • Level 1 (free, 4 modules)
  • Level 2 (8 modules, data interpretation)
  • Level 3 (6 modules, analytical frameworks)
  • Market briefs (Mon/Wed/Fri)
  • Token research reports

Total: 18 modules, ~6-7 hours of institutional training

Upgrade to Analyst ($29/month) →

Already an Analyst subscriber? Continue below ↓

The 8 Data Frameworks

Module 5: ETF Flow Analysis

⏱️ 25 minutes

What you'll learn:
$2B in ETF inflows isn't automatically bullish. Learn to read flow composition (which funds?), velocity (over how many days?), and context (forced rebalancing or discretionary allocation?).

Key questions you'll be able to answer:

  • Why did $1B in ETF inflows in January 2024 create different price action than $1B in March 2024?
  • Which funds signal institutional conviction vs which are just passive rebalancing?
  • How do you normalize flows to fund AUM (size matters)?

What you'll be able to do:

  • Read Farside Investors data correctly (not just headline flow numbers)
  • Distinguish discretionary allocation from forced rebalancing
  • Track flow streaks and composition shifts
  • Predict when ETF flows will impact spot price vs when they won't

Data sources you'll use:

  • Farside Investors (daily ETF flows)
  • Fund prospectuses (understanding fund mandates)
  • Price-flow correlation analysis

Start Module 5: ETF Flow Analysis →

Module 6: Exchange Reserve Dynamics

⏱️ 20 minutes

What you'll learn:
When 50,000 BTC leaves exchanges in one week, what does that actually mean? Custodial shifts? Miner distribution? Institutional accumulation? Learn to distinguish signal from noise.

Key questions you'll be able to answer:

  • Why did 100k BTC leaving exchanges in 2020 signal bullish accumulation, but similar outflows in 2022 were just custodial shifts?
  • How do you identify genuine accumulation vs exchange operational moves?
  • Why do reserve changes lag price by 1-2 days (and what that means)?

What you'll be able to do:

  • Read CoinGlass exchange reserve data correctly
  • Distinguish accumulation from custodial shifts
  • Identify when reserve changes predict future moves vs lag current moves
  • Cross-reference reserves with price action for confirmation

Data sources you'll use:

  • CoinGlass (exchange reserves by exchange)
  • Glassnode (exchange netflows)
  • Proof-of-reserves data

Start Module 6: Exchange Reserve Dynamics →

Module 7: Corporate Treasury Analysis

⏱️ 20 minutes

What you'll learn:
When MicroStrategy buys $500M Bitcoin, why does spot barely move 2%? When a smaller treasury sells $50M, why does spot drop 8%? Execution matters more than headlines.

Key questions you'll be able to answer:

  • Why do MicroStrategy buys have minimal price impact despite large size?
  • How do corporate treasuries execute (OTC vs exchange, TWAP vs market orders)?
  • When does a corporate buy/sell signal institutional sentiment vs just balance sheet management?

What you'll be able to do:

  • Track corporate treasury holdings via BitcoinTreasuries.net
  • Predict which corporate actions will move price vs which won't
  • Distinguish accumulation execution from distribution execution
  • Use corporate treasury flows as contrarian indicators

Data sources you'll use:

  • BitcoinTreasuries.net (corporate holdings tracker)
  • SEC filings (8-K announcements)
  • OTC desk flow data (when available)

Start Module 7: Corporate Treasury Analysis →

Module 8: Government Bitcoin Actions

⏱️ 25 minutes

What you'll learn:
Germany selling 50,000 BTC crashed markets. US strategic reserve rumors pumped markets. Learn the framework for analyzing sovereign flows—the most impactful forced flows that exist.

Key questions you'll be able to answer:

  • Why did Germany's 50k BTC sale crash price -15%, but US Marshals selling similar amounts in 2014 had minimal impact?
  • How do you predict government sale execution (forced market orders vs patient TWAP)?
  • When are government rumors priced in vs when do they create new moves?

What you'll be able to do:

  • Track government Bitcoin holdings (US, China, Germany, El Salvador)
  • Predict execution style based on government type and context
  • Distinguish forced liquidations from strategic sales
  • Use government actions as supply shock analysis

Data sources you'll use:

  • BitcoinTreasuries.net (government holdings)
  • On-chain analysis (tracking known government addresses)
  • News verification (separating rumors from confirmed actions)

Start Module 8: Government Bitcoin Actions →

Module 9: On-Chain Fundamentals

⏱️ 25 minutes

What you'll learn:
UTXO age, active addresses, exchange flows—which metrics actually predict anything vs which are noise? Learn to use Glassnode and CryptoQuant data like institutions do.

Key questions you'll be able to answer:

  • Why did long-term holder supply increasing in 2020 signal accumulation, but same metric in 2021 signaled distribution?
  • Which on-chain metrics are predictive vs which are lagging indicators?
  • How do you avoid the "on-chain astrology" trap?

What you'll be able to do:

  • Read UTXO age bands correctly (accumulation vs distribution phases)
  • Use MVRV ratio as valuation context (not timing signal)
  • Track active addresses as network activity (not price predictor)
  • Distinguish signal from noise in on-chain data

Data sources you'll use:

  • Glassnode (on-chain metrics)
  • CryptoQuant (exchange flows, miner data)
  • Blockchain.com (basic metrics)

Start Module 9: On-Chain Fundamentals →

Module 10: Funding Rates + Open Interest

⏱️ 30 minutes

Complete derivatives positioning framework. Learn to map liquidation clusters, read funding as cost pressure, and predict cascade zones before they trigger.

Key questions you'll be able to answer:

  • Why does 0.1% funding rate signal extreme leverage in one regime but be normal in another?
  • How do you map liquidation clusters to predict cascade zones?
  • When does high Open Interest predict volatility vs when is it stable?

What you'll be able to do:

  • Read CoinGlass funding rate data correctly (cost pressure, not sentiment)
  • Use Open Interest to identify leverage buildup
  • Map liquidation heatmaps to predict cascade zones
  • Combine funding + OI + liquidations into complete derivatives view

Data sources you'll use:

  • CoinGlass (funding rates, OI, liquidation heatmaps)
  • Exchange APIs (for real-time data)
  • Historical funding analysis

Start Module 10: Funding Rates + Open Interest →

Module 11: Liquidation Cascades

⏱️ 25 minutes

What you'll learn:
Why $500M in liquidations creates -3% or -15% moves (depends on liquidity regime when cascade hits). Learn exhaustion signals and when forced selling creates buying opportunities.

Key questions you'll be able to answer:

  • Why did May 2021 liquidations create -30% cascade while similar liquidations in 2023 created -8% moves?
  • How do you identify cascade exhaustion (when forced selling is complete)?
  • When is a liquidation cascade a buying opportunity vs start of larger move?

What you'll be able to do:

  • Predict cascade magnitude based on liquidity depth + leverage positioning
  • Identify exhaustion signals (volume spikes, funding resets, OI drops)
  • Use liquidation cascades as forced flow opportunities
  • Distinguish local liquidations from systemic deleveraging

Data sources you'll use:

  • CoinGlass (liquidation data by exchange and timeframe)
  • Order book depth analysis
  • Historical cascade patterns

Start Module 11: Liquidation Cascades →

Module 12: Market Sentiment vs Positioning

⏱️ 20 minutes

What you'll learn:
Fear & Greed Index is useless. Retail sentiment is a contrary indicator. Learn what positioning data actually reveals (and what it doesn't).

Key questions you'll be able to answer:

  • Why is Fear & Greed Index at "Extreme Greed" often a sell signal?
  • How do you use retail sentiment as contrarian indicator?
  • What's the difference between sentiment (what people say) and positioning (what people do)?

What you'll be able to do:

  • Read sentiment indicators as contrary signals
  • Use positioning data (funding, OI, exchange flows) as actual conviction measure
  • Identify when sentiment diverges from positioning (highest-edge setups)
  • Avoid the "everyone's bullish so I should be too" trap

Data sources you'll use:

  • Fear & Greed Index (as contrarian tool)
  • Funding rates (revealed preference)
  • Social sentiment analysis (Twitter, Reddit metrics)

Start Module 12: Market Sentiment vs Positioning →

After Level 2: What's Next?

You now know what data to track and how to read it.

You can interpret ETF flows, exchange reserves, derivatives positioning, on-chain metrics, and sentiment correctly.

But you're still reading signals in isolation. Now you need synthesis.

Ready for Level 3?

Level 3 teaches you how to combine signals into complete market view:

  • Multi-signal synthesis (building composite scores)
  • Regime detection (identifying market phases before they're obvious)
  • Risk-on/risk-off framework (when macro overrides crypto)
  • Correlation analysis (BTC-altcoin, crypto-equity relationships)
  • Bitcoin dominance & altseason (complete rotation framework)
  • Building your institutional dashboard (10-minute daily routine)

Level 3 is included in your Analyst subscription.

Go to Level 3: Analytical Frameworks →

Or if you need more practice with Level 2:

Return to Academy Overview →

Questions About Level 2?

How long does Level 2 take?
~3-4 hours if you read all 8 modules straight through. Better approach: One module per day over 1-2 weeks.

Do I need to complete modules in order?
Mostly yes. Module 10 (Funding + OI) and Module 11 (Liquidation Cascades) build on each other. But you can do Module 5 (ETF Flows) before Module 9 (On-Chain) if you want.

What if I don't have access to all data sources?
Everything we teach uses free data (Farside, CoinGlass, BitcoinTreasuries.net, etc.). No paid subscriptions required.

Can I use this for trading?
These are analytical frameworks, not trading signals. We teach you HOW to analyze. What you do with that analysis is up to you.

Not an Analyst subscriber yet?

Upgrade to Analyst ($29/month) →

Includes Level 2 (data interpretation) + Level 3 (frameworks) + market briefs + token research reports.

Pierce & Pierce Academy
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