Statistical Arbitrage and Securities Prices
Statistical Arbitrage and Securities Prices
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统计套利和证券价格
DOI：
10.2139/ssrn.320943
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发表时间：
2002
期刊：
影响因子：
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通讯作者：
Oleg Bondarenko
中科院分区：
文献类型：
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作者：
Oleg Bondarenko
本文介绍了统计套利机会（SAO）的概念。在有限视界经济中，SAO是一种零成本的交易策略，其(i)预期收益为正，（ii）经济中每个最终状态的条件预期收益是非负的。与纯粹的套利机会不同，如果每个最终状态的平均收益是非负的，那么SAO可以具有负收益。如果经济中的定价核心是路径无关的，那么不可能存在sao。此外，排除sao对证券价格的动态施加了一种新的鞅式限制。该限制的重要性质是：(1)它是无模型的，也就是说它不需要对真正的均衡模型进行参数假设；(2)可以在受选择偏差影响的样本中进行测试，比如比索问题；(3)当投资者的信念出错时，它仍然成立。本文认为，利用这一新的约束可以从经验上解决传统有效市场假设检验中存在的联合假设问题。牛津大学出版社版权所有。
This article introduces the concept of a statistical arbitrage opportunity (SAO). In a finite-horizon economy, a SAO is a zero-cost trading strategy for which (i) the expected payoff is positive, and (ii) the conditional expected payoff in each final state of the economy is nonnegative. Unlike a pure arbitrage opportunity, a SAO can have negative payoffs provided that the average payoff in each final state is nonnegative. If the pricing kernel in the economy is path independent, then no SAOs can exist. Furthermore, ruling out SAOs imposes a novel martingale-type restriction on the dynamics of securities prices. The important properties of the restriction are that it (1) is model-free, in the sense that it requires no parametric assumptions about the true equilibrium model, (2) can be tested in samples affected by selection biases, such as the peso problem, and (3) continues to hold when investors' beliefs are mistaken. The article argues that one can use the new restriction to empirically resolve the joint hypothesis problem present in the traditional tests of the efficient market hypothesis. Copyright 2003, Oxford University Press.