测试大体积分类算法

Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal Pub Date : 2020-12-01 DOI:10.2139/ssrn.3746731

Allen Carrion, Madhuparna Kolay

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引用次数: 1

摘要

我们证明，现有证据表明，大宗交易分类(BVC)措施为交易提供信息，主要是由于错误指定的测试而产生的。模拟表明，这些测试可以检测到仅包含不知情流动性交易的数据中的虚假关系。我们还评估了纳斯达克高频交易数据集中BVC订单失衡的表现，表明BVC订单失衡在检测知情交易方面表现不如传统的订单失衡指标。被BVC指定为被动知情交易的订单流组件无法用正确的符号预测收益。总的来说，我们的证据支持使用传统的订单不平衡措施来识别知情交易。

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Testing the Bulk Volume Classification Algorithm

We document that the existing evidence that bulk volume trade classification (BVC) measures informed trading arises largely due to mis-specified tests. Simulations show that these tests detect spurious relationships in data containing only uninformed liquidity trades. We also assess the performance of BVC order imbalances in the NASDAQ HFT dataset, showing that BVC order imbalances underperform conventional order imbalance measures in detecting informed trading. The component of order flow designated by BVC as passive informed trading fails to predict returns with the correct sign. On balance, our evidence supports the use of conventional order imbalance measures to identify informed trading.

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Microeconomics: General Equilibrium & Disequilibrium Models of Financial Markets eJournal

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