英文标题：
《Trading via Image Classification》
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作者：
Naftali Cohen, Tucker Balch, and Manuela Veloso
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最新提交年份：
2020
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英文摘要：
  The art of systematic financial trading evolved with an array of approaches, ranging from simple strategies to complex algorithms all relying, primary, on aspects of time-series analysis. Recently, after visiting the trading floor of a leading financial institution, we noticed that traders always execute their trade orders while observing images of financial time-series on their screens. In this work, we built upon the success in image recognition and examine the value in transforming the traditional time-series analysis to that of image classification. We create a large sample of financial time-series images encoded as candlestick (Box and Whisker) charts and label the samples following three algebraically-defined binary trade strategies. Using the images, we train over a dozen machine-learning classification models and find that the algorithms are very efficient in recovering the complicated, multiscale label-generating rules when the data is represented visually. We suggest that the transformation of continuous numeric time-series classification problem to a vision problem is useful for recovering signals typical of technical analysis.
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中文摘要：
系统金融交易的艺术随着一系列方法的发展而演变，从简单的策略到复杂的算法，所有这些都主要依赖于时间序列分析的各个方面。最近，在参观了一家领先金融机构的交易大厅后，我们注意到，交易员总是在屏幕上观察金融时间序列图像的同时执行交易订单。在这项工作中，我们以图像识别的成功为基础，研究了将传统的时间序列分析转换为图像分类的价值。我们创建了一个大样本的金融时间序列图像，这些图像编码为烛台（盒子和胡须）图，并按照三种代数定义的二进制交易策略标记样本。利用这些图像，我们训练了十几个机器学习分类模型，发现当数据以视觉方式表示时，这些算法在恢复复杂的多尺度标签生成规则方面非常有效。我们认为，将连续数字时间序列分类问题转化为视觉问题有助于恢复技术分析的典型信号。
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Computer Vision and Pattern Recognition        计算机视觉与模式识别
分类描述：Covers image processing, computer vision, pattern recognition, and scene understanding. Roughly includes material in ACM Subject Classes I.2.10, I.4, and I.5.
涵盖图像处理、计算机视觉、模式识别和场景理解。大致包括ACM课程I.2.10、I.4和I.5中的材料。
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一级分类：Quantitative Finance        数量金融学
二级分类：Computational Finance        计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
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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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