{"id":15632727,"url":"https://github.com/jm199504/financial-time-series","last_synced_at":"2025-04-07T07:12:30.633Z","repository":{"id":41159511,"uuid":"194996513","full_name":"jm199504/Financial-Time-Series","owner":"jm199504","description":"金融时间序列（预测分析 / 相似度 / 数据处理）","archived":false,"fork":false,"pushed_at":"2024-07-10T13:46:52.000Z","size":5058,"stargazers_count":226,"open_issues_count":1,"forks_count":63,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-31T06:04:36.952Z","etag":null,"topics":["financial-prediction","financial-time-series","python","similarity-measures"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jm199504.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-07-03T06:52:02.000Z","updated_at":"2025-03-22T09:55:17.000Z","dependencies_parsed_at":"2024-10-23T02:03:16.236Z","dependency_job_id":null,"html_url":"https://github.com/jm199504/Financial-Time-Series","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jm199504%2FFinancial-Time-Series","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jm199504%2FFinancial-Time-Series/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jm199504%2FFinancial-Time-Series/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jm199504%2FFinancial-Time-Series/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jm199504","download_url":"https://codeload.github.com/jm199504/Financial-Time-Series/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247608153,"owners_count":20965952,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["financial-prediction","financial-time-series","python","similarity-measures"],"created_at":"2024-10-03T10:45:07.970Z","updated_at":"2025-04-07T07:12:30.602Z","avatar_url":"https://github.com/jm199504.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"### 金融时间序列（数据预测 / 相似度 / 数据处理）\n\n![author](https://img.shields.io/static/v1?label=Author\u0026message=junmingguo\u0026color=green)\n![language](https://img.shields.io/static/v1?label=Language\u0026message=python3\u0026color=orange) ![topics](https://img.shields.io/static/v1?label=Topics\u0026message=financial-time-series\u0026color=blue)\n\n\n#### 1. Financial-Prediction-Methods（金融时间序列预测方法）\n\n- 1.1 Financial-Prediction-CNN（卷积神经网络）\n\n- 1.2 Financial-Prediction-LSTM（长短期记忆神经网络）\n\n- 1.3 Financial-Prediction-Random-Forest（随机森林）\n\n- 1.4 Financial-Prediction-ARMA（自回归滑动平均模型）\n\n- 1.5 Financial-Prediction-ARIMA（自回归积分移动平均模型）\n\n- 1.6 Financial-Prediction-Muiti-Input-Conv1D（多输入Conv1D模型）\n\n- 1.7 Financial-Prediction-2DCNN（2D卷积神经网络）\n\n- 1.8 Financial-Prediction-3DCNN（3D卷积神经网络）\n\n---\n\n#### 2. Financial-Time-Similarity（金融时间序列相似度计算）\n\n- 2.1 pearson_correlation_coefficient（皮尔逊相关系数）\n\n- 2.2 dynamic_time_wrapping（动态时间规整）\n\n- 2.3 cosine similarity（余弦相似度）\n\n- 2.4 similarity_time_series.py（相似金融时间序列绘制）\n\n---\n\n#### 3. Finance-Time-Others（金融时间序列其他处理）\n\n- 3.1 calc_variance.py（计算特征方差）\n- 3.2 confuse_matrix.py（绘制混淆矩阵）\n\n![](https://github.com/jm199504/Financial-Time-Series/blob/master/3%20Financial-Time-Others/images/matrix.png?raw=true)\n\n- 3.3 corr.py（特征间相关性）\n\n![](https://github.com/jm199504/Financial-Time-Series/blob/master/3%20Financial-Time-Others/images/corr.png?raw=true)\n\n- 3.4 result_bar.py（绘制预测模型性能——柱状图）\n\n![](https://github.com/jm199504/Financial-Time-Series/blob/master/3%20Financial-Time-Others/images/bar.png?raw=true)\n\n- 3.5 result_plot.py（绘制预测模型性能——折线图）\n\n![](https://github.com/jm199504/Financial-Time-Series/blob/master/3%20Financial-Time-Others/images/plot.png?raw=true)\n\n- 3.6 evaluation.py（计算分类的评价指标）\n\n  - 准确率Accuracy\n\n  - 精确率Precision\n  - 召回率Recall\n  - 特异度Specificity\n  - 综合评价指标F-measure\n  - 马修斯相关系数MCC(Matthews Correlation Coefficient)\n- 3.7 normalization.py（窗口数据归一化）\n  - z-score标准化（std）\n  - 最大最小归一化（maxmin）\n- 3.8 roc.py（roc曲线绘制）\n\n![](https://github.com/jm199504/Financial-Time-Series/blob/master/3%20Financial-Time-Others/images/roc.png?raw=true)\n\n- 3.9 confusion_matrix.py（混淆矩阵绘制）\n\n![](https://github.com/jm199504/Financial-Prediction/blob/master/3%20Financial-Time-Others/images/cm.png?raw=true)\n\n- 3.10 kalmanfilter.py（卡尔曼滤波）\n\n![](https://github.com/jm199504/Financial-Prediction/blob/master/3%20Financial-Time-Others/images/kf.png?raw=true)\n\n- 3.11 calc_technical_indicators_formula.py（基于公式计算技术指标）\n- 3.12 calc_technical_indicators_TA_LIB.py（基于TA_LIB库计算技术指标）\n\n****\n\n#### 4. Financial-Candle-Picture（金融蜡烛图）\n\n基于`mpl_finance`和`matplotlib`库实现将股价转为蜡烛图，效果预览：\n\n![](https://github.com/jm199504/Financial-Prediction/blob/master/3%20Financial-Time-Others/images/002253_0_01.png?raw=true)\n\n---\n\n#### 5.Financial-Data-Download（金融数据下载）\n\n提供了三种金融数据源：JQdata、akshare、tushare\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjm199504%2Ffinancial-time-series","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjm199504%2Ffinancial-time-series","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjm199504%2Ffinancial-time-series/lists"}