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I introduce an agent-based model of a Perpetual Futures market with heterogeneous agents trading via a central limit order book. Perpetual Futures (henceforth Perps) are financial derivatives introduced by the economist Robert Shiller, designed to peg their price to that of the underlying Spot market. This paper extends the limit order book model of Chiarella et al. (2002) by taking their agent and orderbook paramete…
The label event-linked perpetual often conflates mathematically different contracts. We replace a flat product list with a four-axis taxonomy: underlying geometry, temporal structure, settlement structure, and venue-oracle composition. The taxonomy covers a single binary probability, conditional ratios, event spreads, baskets, path functionals, liquidity indices, rolling sequences, and flow-only swaps. We derive a co…
Leverage does not create manipulation or informed trading in event markets, but it changes their economics. We separate four conduct channels: market-price manipulation, real-world outcome manipulation, resolution-process manipulation, and informed trading that exploits non-public information without changing the event or resolution rule. A capital-constrained amplification model shows that gross directional gains sc…
We study reinforcement learning (RL) on volatility surfaces through the lens of Scientific AI. We ask whether axiomatic no-arbitrage laws, imposed as soft penalties on a learned world model, can reliably align high-capacity RL agents, or mainly create Goodhart-style incentives to exploit model errors. From classical static no-arbitrage conditions we build a finite-dimensional convex volatility law manifold of admissi…
Examples of stochastic processes whose state space representations involve functions of an integral type structure $$I_{t}^{(a,b)}:=\int_{0}^{t}b(Y_{s})e^{-\int_{s}^{t}a(Y_{r})dr}ds, \quad t\ge 0$$ are studied under an ergodic semi-Markovian environment described by an $S$ valued jump type process $Y:=(Y_{s}:s\in\mathbb{R}^{+})$ that is ergodic with a limiting distribution $π\in\mathcal{P}(S)$. Under different assump…