Analysis of the Tick Rule and Bulk Volume Classification algorithms in the Brazilian stock market

ABSTRACT This study aimed to compare the performance of Tick Rule (TR) and Bulk Volume Classification (BVC) models in classifying assets traded on the Brazilian stock exchange (B3) and indicate which one performs better as an investment decision tool. The assets were split into three groups based on their volume, and actual data was used to assess the accuracy of both algorithms. Data from 2018 was used to estimate the parameters that best fit BVC, and transactions from 2019 were used to test the algorithm’s efficiency. Afterward, the Volume-Synchronized Probability of Informed Trading (VPIN) was calculated for each asset using TR and BVC, and the values obtained were compared against VPIN calculated using real data. In conclusion, the TR algorithm shows betters performance than BVC for all three groups of assets. Analysis of the properties of both methods reveals that the base upon which the TR is built holds up in the Brazilian market, whereas BVC mechanics does not reflect the observed reality.

摘要 本研究旨在对比报价规则（Tick Rule, TR）与批量成交量分类法（Bulk Volume Classification, BVC）在巴西证券交易所（B3）挂牌交易资产的分类表现，并指明二者中更适合作为投资决策工具的模型。研究将资产按成交量划分为三组，并基于真实交易数据评估两种算法的分类精度。其中，2018年的数据用于拟合适配BVC模型的最优参数，2019年的交易数据则用于测试算法的有效性。随后，分别通过TR与BVC计算每类资产的成交量同步知情交易概率（Volume-Synchronized Probability of Informed Trading, VPIN），并将所得结果与基于真实交易数据计算的VPIN值进行对比。研究结论表明，针对全部三组资产，TR算法的表现均优于BVC模型。对两种方法的特性分析显示，TR所依托的理论基础在巴西市场中成立，而BVC的运行机制则无法反映当地实际交易情况。