Financial Mathematics for Cryptocurrencies

Master the quantitative foundations you need to successfully invest in and trade digital assets

Financial Mathematics for Cryptocurrencies by Tom J. Espel combines two of today's most dynamic fields – quantitative finance and cryptocurrencies – in a comprehensive guide that addresses the unique mathematical challenges faced by everyone involved in the crypto markets. Espel draws on his extensive experience in frontier assets to explain the analytical frameworks you’ll need to make informed investment decisions, identify pricing opportunities, and manage risk in this volatile asset class.

The book adapts relevant quantitative finance methodologies specifically for digital assets, bridging the gap between traditional financial mathematics and the distinctive characteristics of blockchain-based instruments. Espel introduces three essential constructs for DeFi pricing theory: network time, the validator account as a new numéraire, and wrapped token frameworks for cross-chain valuation. Its modular structure allows readers to navigate directly to relevant sections, covering everything from blockchain fundamentals to advanced valuation models, staking contract mathematics, and liquidity cost analysis in cryptocurrency markets.

You’ll find:

Mathematical frameworks for staking contracts, liquid staking derivatives, and yield farming strategies with rigorous ex-ante and ex-post valuations
Comprehensive coverage of network valuation methods including Metcalfe's Law, Reed's Law, and the ZBOT framework specifically applied to digital assets
Pricing theory extending arbitrage-free pricing to blockchain assets through the validator account and blockchain measure (B-measure)
Expert insights from an author specializing in quantitative strategies for electronic and illiquid assets, with expertise in market microstructure and volatility modeling
Accessible mathematical solutions designed for practitioners in applied mathematics and quantitative finance, with clear and rigorous explanations