Spot-Futures Parity
Spot-futures parity is a theoretical relationship that describes the fair price of a futures contract relative to the spot price of an asset, adjusted for the cost of carry. In an efficient market, the futures price should equal the spot price plus the interest costs and storage costs, minus any dividends or yield earned on the asset.
If the futures price deviates from this parity, an arbitrage opportunity exists. In the crypto market, spot-futures parity is complicated by the lack of traditional storage costs and the presence of staking yields.
Deviations from this parity provide insight into market efficiency and the availability of leverage. It serves as a benchmark for determining whether a contract is overvalued or undervalued.
Glossary
Mean Reversion
Theory ⎊ Mean reversion is a core concept in quantitative finance positing that asset prices and volatility levels tend to revert to their long-term average over time.
Liquidity Provision
Mechanism ⎊ Liquidity provision functions as the foundational process where market participants, often termed liquidity providers, commit capital to decentralized pools or order books to facilitate seamless trade execution.
Asset Liability Management
Balance ⎊ Asset liability management (ALM) in crypto finance focuses on balancing a firm's assets, such as collateral holdings and investment positions, against its liabilities, which include outstanding loans, derivative obligations, and funding costs.
Prisoner's Dilemma
Action ⎊ The Prisoner's Dilemma, when applied to cryptocurrency derivatives or options trading, highlights the strategic tension between individual actors and collective outcomes.
GARCH Models
Application ⎊ GARCH models, within cryptocurrency markets, provide a dynamic volatility framework crucial for pricing derivatives and managing risk, differing from simpler models by allowing volatility to cluster and respond to past shocks.
Bid-Ask Spread
Liquidity ⎊ The bid-ask spread represents the difference between the highest price a buyer is willing to pay (bid) and the lowest price a seller is willing to accept (ask) for an asset.
Machine Learning
Algorithm ⎊ Machine learning, within cryptocurrency and derivatives, centers on algorithmic identification of patterns in high-frequency market data, enabling automated strategy execution.
Supply Side Economics
Economics ⎊ Supply Side Economics, within cryptocurrency and derivatives markets, centers on influencing asset availability to modulate price discovery, differing from demand-focused approaches.
Cost of Carry
Calculation ⎊ The cost of carry represents the net cost incurred for holding a financial asset or derivative position over a specific period.
Social Media Sentiment
Analysis ⎊ Social Media Sentiment, within cryptocurrency, options, and derivatives, represents the aggregation and interpretation of publicly available textual data to gauge market participant attitudes.