摘要
金融市场高频数据包括时间序列数据和其他宏观经济指标,通常具有高维特征.其处理需要更复杂的算法,易产生较高的模型过拟合风险.基于此,提出基于局部线性映射(Local Linear Mapping,LLM)的金融市场波动率高频数据异常检测方法,对各个高频数据目标的日平均序列数据进行标准化处理,在数据筛选时,使用标准化处理设定相关阈值,将不同维度的数据转化为相同的尺度,并利用连通图算法,将具有边连接的金融市场波动率高频数据划分至一个群组内,计算待检测高频数据阈值,采用局部线性映射,完成金融市场波动率高频数据异常检测.实验结果表明:所提方法在TPR为0.98时,ROC曲线稳定运行,贡献因子为1.287,重构误差为1.6%,能够以最快速度使训练集异常检测的损失值达到稳定.
High-frequency data in financial markets usually has high-dimensional characteristics,including time-series data and other macroeconomic indicators.The processing of high-dimensional data requires more sophisticated algorithms,leading to increased computational complexity and the risk of model over-fitting.In view of this,the anomaly detection method of financial market volatility high-frequency data based on LLM is proposed.Specifically,the method sets to standardization of the daily average sequence of each high-frequency data.While screening data,the method uses standardized processing to set the relevant threshold,transforms the data of different dimensions into the same scale,�and applies the connected algorithm to put edge-connected financial market volatility high-frequency data into a same group.When calculating high-frequency data threshold to be detected,the method uses local linear mapping so as to bring the financial market volatility high-frequency data anomaly detection to an end.The experimental results show that when the proposed method is 0.98,the ROC curve displays a stable run and,with the contribution factor being 1.287,and the reconstruction error being 1.6%,the loss value of anomaly detection in the training set reaches a steady state at the fastest speed.
作者
何远景
李光龙
HE Yuanjing;LI Guangong(Anhui Institute of Industrial Economics and Vocational Technology,College of Finance and Economics,Hefei 230000;Economics School of Anhui University,Hefei 230000,China)
出处
《常熟理工学院学报》
2024年第2期89-94,共6页
Journal of Changshu Institute of Technology
基金
2021年安徽省省级质量工程项目“《保险理论与实务》精品课程”(2021jpk028)
教育部职业教育提质培优行动计划(2020—2023年)“《大数据视域下,高校思政教育协同育人建构路径研究——基于金融类专业分析》”(皖教秘高[2021]35号)
安徽省职业与成人教育学会2022年度教育教学研究规划课题“大思政”背景下,高职金融学课程群协同育人建构路径研究(Azj2022091)
2020年院级质量工程项目“《保险理论与实务》线下课程”(2020yxxkc01)。
关键词
局部线性映射
金融市场
波动率
高频数据
异常检测
local linear mapping
financial markets
volatility
high-frequency data
anomaly detection
