英文标题：
《Quintet Volume Projection》
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作者：
Vladimir Markov, Olga Vilenskaia and Vlad Rashkovich
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最新提交年份：
2019
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英文摘要：
  We present a set of models relevant for predicting various aspects of intra-day trading volume for equities and showcase them as an ensemble that projects volume in unison. We introduce econometric methods for predicting total and remaining daily volume, intra-day volume profile (u-curve), close auction volume and special day seasonalities and emphasize a need for a unified approach where all sub-models work consistently with one another. Historical and current inputs are combined using Bayesian methods, which have the advantage of providing adaptive and parameterless estimations of volume for a broad range of equities while automatically taking into account uncertainty of the model input components. The shortcomings of traditional statistical error metrics for calibrating volume prediction are also discussed and we introduce Asymmetrical Logarithmic Error (ALE) to overweight an overestimation risk.
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中文摘要：
我们提出了一组与预测股票日内交易量的各个方面相关的模型，并将其作为一个整体展示，以统一预测交易量。我们介绍了用于预测总日交易量和剩余日交易量、日内交易量曲线（u曲线）、闭市拍卖量和特殊日季节性的计量经济学方法，并强调需要一种统一的方法，使所有子模型相互一致。历史和当前输入使用贝叶斯方法进行组合，贝叶斯方法的优点是为广泛的股票提供自适应和无参数的成交量估计，同时自动考虑模型输入组件的不确定性。文中还讨论了传统统计误差指标用于校正体积预测的缺点，并引入非对称对数误差（ALE）来加重高估风险。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Trading and Market Microstructure        交易与市场微观结构
分类描述：Market microstructure, liquidity, exchange and auction design, automated trading, agent-based modeling and market-making
市场微观结构，流动性，交易和拍卖设计，自动化交易，基于代理的建模和做市
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