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Free lesson · Crypto derivatives

Linear contract payoff and the multiplier

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Start with the idea

A linear derivative pays in the quote currency in proportion to the underlying price change and signed exposure.

Symbols, units & horizon
  • n: signed contract count
  • m: base-token units per contract
  • P_0,P_1: entry/exit quote-currency prices per base token
  • Π_gross: quote-currency profit before fees/funding over this holding interval

When and why to use this

Translate orders into correct exposure and separate the derivative result from margin deposits.

A linear derivative pays in the quote currency in proportion to the underlying price change and signed exposure.

Positive quantity means long and negative means short. Multiply contract count by base units per contract before applying the price change. Record whether settlement uses an index, mark or final trade price.

Initial margin is collateral, not the notional traded and not necessarily the maximum possible loss. Fees may apply to notional on entry and exit rather than to posted margin.

Πgross=nm(P1−P0)
Model assumptions, derivation and arithmetic

Linear contract payoff and the multiplier

  1. Convert contracts into signed base exposure nm.
  2. Subtract entry price from exit price.
  3. Multiply exposure by price change, then reconcile separate fees and funding.
Work it by hand

Short n=−10 contracts of .01 BTC each at $50,000; exit $48,000. Exposure=−.1 BTC; P&L=−.1×(−2000)=$200.

Apply it in a strategy

  • Translate orders into correct exposure and separate the derivative result from margin deposits.
  • Record the input timestamp, executable quantity, currency and horizon. Reconcile the result with a cash-flow or state table.
  • Stress this failure condition: Wrong multipliers or a different settlement currency can change P&L by orders of magnitude.

Research deliverable

Build and explain a linear contract payoff and the multiplier worksheet. Translate orders into correct exposure and separate the derivative result from margin deposits.

Evidence boundary: Synthetic arithmetic and scenarios illustrate mechanics. They are not historical returns, a paper replication, or evidence of an executable edge. Research sources and their access limitations are recorded at the end of this module.

Research sources, review dates and limitations

Python implementation

Self-contained teaching example. Python 3.10+; dependencies and input conventions are shown in the code and notation. Run in your own Python environment.

# Python 3.10+; standard library unless NumPy is imported below.
# Inputs and outputs use the units defined in this lesson. Synthetic teaching example.
def linear_pnl(contracts,base_multiplier,entry,exit_price):
    if base_multiplier<=0 or min(entry,exit_price)<=0: raise ValueError("Positive multiplier and prices required")
    return contracts*base_multiplier*(exit_price-entry)

print(linear_pnl(-10,.01,50000,48000))

Continue learning

Crypto Derivatives: Carry, Funding and Liquidation — all lessons
  1. Linear contract payoff and the multiplier
  2. Inverse contracts pay in the base asset
  3. Basis annualization and its limits
  4. Perpetual funding as actual cash flows
  5. Equity versus maintenance along a price path
  6. Solve a simplified liquidation boundary
  7. Collateral depegs and wrong-way exposure
  8. Reconcile the funded spot–perpetual hedge

Quantitative finance and development glossary · Python resources and libraries · Research sources and limitations