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市场时钟异步与交易市场不完备性

文章 arXiv papers · 作者: Chris Angstmann et al.

总结

本文质疑所有资产共享一个连续日历时钟这一常见假设。市场实际以异步方式运行:订单流随事件到达,事件之间的时间间隔可能是随机的。文章将事件时间、更新过程、点过程和订单流描述与传统连续时间价格模型进行比较,继而探讨这些选择如何影响无套利推理和风险中性期权定价。

文章的核心观点是,离散事件市场可能存在多个有效的连续时间极限,从而揭示一种更深层的市场不完备性。操作时间可能影响交易决策,而风险管理还必须将敞口换算到日历时间。讨论认为,即使时钟不匹配使高频对冲和执行更复杂,平均意义上的完备性仍可能适用于较低频率的投资组合构建。本文属于概念性讨论,没有实证检验或具体交易规则;其含义取决于所采用的时间尺度和市场表示方式。

核心观点

  • 市场以异步方式运行,事件到达不一定遵循均匀时钟。
  • 事件时间模型和日历时间模型可能对价格和风险得出不同看法。
  • 离散事件过程可能存在多个连续时间极限。
  • 时钟不匹配可能使高频执行和对冲更加复杂。
  • 较低频率的投资组合构建仍可能利用有效的平均完备性。

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# Non-unique time and market incompleteness


# Non-unique time and market incompleteness









Financial markets are often modelled as if time were unique and continuous across assets and markets. Financial markets are however asynchronous, order flow is event-driven, and waiting times between events are often random. Many of the most influential formulations of financial market models presuppose a unique global calendar time and advocate for this or that preferred single latent continuous-time price system. Here we critically contrast these assumptions with event-time, renewal, point-process, and order-flow descriptions. We revisit no-arbitrage, no-dynamic-arbitrage, and risk-neutral option pricing in settings where the market is represented as a discrete event system and where the continuum limit of a discrete-time random walk need not be unique. The central suggestion is then that such non-uniqueness points to a more foundational form of market incompleteness than is usually emphasized. This highlights the importance of operational time at the level of decision making but reminds market practitioners that managing risk itself often requires reconciling operational time with a global calendar time. At these longer time scales forms of effective or average completeness may still emerge at lower frequencies and remain useful for portfolio construction and risk management, even if high-frequency hedging and execution expose a clock mismatch between trading, pricing, and longer-horizon allocation.

在遵守原作品许可的前提下,附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写,并非原文副本。