Learning objectives
By the end you can:
- Classify a digital asset by primary-source mechanics, not marketing (payment/store-of-value token, smart-contract platform token, utility token, security token, or stablecoin (fiat-collateralized, crypto-collateralized, or algorithmic)) and state which legal test actually governs the security-or-not question in the US, and why India currently answers that question through tax and anti-money-laundering law rather than a dedicated securities framework.
- Explain, from the Bitcoin whitepaper and protocol rules, how mining, proof-of-work, the halving schedule, and the 21-million cap work, and compute the current supply, the stock-to-flow ratio, and the share of eventual supply already issued at any given halving.
- Explain how a smart-contract platform (Ethereum) differs mechanically from Bitcoin (the account model, gas, and the shift from proof-of-work to proof-of-stake) and compute how a validator's staking reward moves as total network stake changes.
- Distinguish the three stablecoin designs by their actual backing mechanism, and explain (using the real collapse of an algorithmic stablecoin and a real DeFi liquidation event) what "backed" does and does not guarantee.
- Explain custody (self-custody vs custodial) and what a real, large custodial failure teaches about counterparty risk that a marketing page never will.
- Compute how a constant-product automated market maker prices a trade and how slippage grows with trade size relative to pool depth, and compute a perpetual future's funding-rate payment and its cash-and-carry arbitrage implication.
- Build and interpret a real correlation matrix and a real portfolio-allocation stress test across a range of crypto weights, and state (with the numbers in front of you) what a small crypto sleeve actually does to one-month tail risk.
- State, citing the primary documents themselves, the current shape of US (SEC, the GENIUS Act) and India (Sections 115BBH/194S, the PMLA notification, and the honest absence of a dedicated securities framework) regulatory treatment, and the standard-setting work of IOSCO and BIS/CPMI.
- (Productivity objective: R10 duality.) Apply the Primary-Source Guardrail (AI0.01) specifically to AI-generated claims about a token, protocol, or yield product, arguably the single highest AI-over-trust surface in this entire corpus, so that no unsourced number or unverified "audit" claim survives into your own analysis.
The duality, stated once (R10). Objectives 1–8 are what the mastery gate rewards, the by-hand mechanism, the citation discipline, the arithmetic. Objective 9 is the productivity payoff you keep: knowing exactly which claims in this asset class an AI tool is most likely to fabricate convincingly, and running the Guardrail on them by reflex. No tool buys you a pass on the gate, and here more than almost anywhere else in the corpus that matters, because, by the standard-setters' own published assessments, cited throughout this module, this is the corner of finance with the highest concentration of confident, unverifiable claims per page.
Prerequisites & connections
Builds on. AL1.01 (hedge-fund fee decomposition, bring the identical 2/20-and-lock-up skepticism to a "crypto fund" wrapper; a fund charging performance fees on a beta you could hold directly is the same math with a different noun). AL1.02 (the commodity/real-asset asset-class case built on decomposing return into spot, roll, and collateral yield, this module asks whether Bitcoin has an equivalent return source and gives you the honest, unflattering answer in §"The asset-class case" below, rather than re-deriving AL1.02's framework). M7.06 §4.10 (commodities as macro signals, gold's long-documented low correlation with equities is the diversifier baseline this module tests a crypto allocation against, using real IMF-documented correlation findings, not slogans). E11.01 (credit analysis, the toolkit for pricing credit and platform risk into an above-market yield; apply it here to a crypto-lending or "earn" product exactly as you would to a corporate bond spread, not differently because the coupon is denominated in a token). DV1.01 (cost-of-carry pricing for forwards, futures, and swaps, a perpetual future's funding-rate mechanism is this module's crypto-native cousin of that framework, and is contrasted against it directly, not re-taught).