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Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (8): 94-104    DOI: 10.11925/infotech.2096-3467.2018.1137
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Ontology Reasoning for Financial Affairs with RBR and CBR
Shaohua Qiang1(),Yunlu Luo2,Yupeng Li1,Peng Wu3
1School of Economics and Management, Nanjing Tech University, Nanjing 211800, China
2School of Economic Information Engineering, Southwestern University of Finance and Economics, Chengdu 611130, China
3School of Economics and Management, Nanjing University of Science &Technology, Nanjing 210094, China;
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Abstract  

[Objective] This paper tries to predict the impacts of financial events/news on stock price with financial, non-financial and public opinion factors. [Methods] We designed a financial affairs ontology based on the Rule-Based Reasoning (RBR) and Case-Based Reasoning (CBR). Then, we created a SWRL rule-based reasoning model, which pursued the rule-based reasoning using the Dloors engine. Thirdly, we designed a topic case database to describe the structure of the financial cases. Finally, we used the model to describe, retrieve, reuse, correct and preserve the data. [Results] We conducted an empirical study to examine the reliability of rule-based reasoning and case-based reasoning with enterprise data. [Limitations] We did not compare our model with the existing methods. [Conclusions] The proposed method could predict the stock price in big data environment.

Key wordsFinancial Affairs      Ontology      Rule-Based Reasoning      Case-Based Reasoning      Stock Price Forecast     
Received: 16 October 2018      Published: 29 September 2019
ZTFLH:  TP393 G35  
Corresponding Authors: Shaohua Qiang     E-mail: shaohua3900@163.com

Cite this article:

Shaohua Qiang,Yunlu Luo,Yupeng Li,Peng Wu. Ontology Reasoning for Financial Affairs with RBR and CBR. Data Analysis and Knowledge Discovery, 2019, 3(8): 94-104.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2018.1137     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2019/V3/I8/94

评测指标 备注
所处行业
舆情 股市情绪 网民情感
财务指标 发展能力 净利润增长率
现金流水平 全部现金回收率
盈利能力 净资产收益率、成本费用利润率、营业利润率、资产报酬率
经营能力 固定资产周转率、应收账款周转率、总资产周转率、流动资产周转率
风险能力 经营杠杆、综合杠杆、财务杠杆
非财务指标 专利数量
信息披露
社会责任
子公司数
媒体和机构关注度
金融事件 政府政策
自身危机
行业创新
股价 事件发生前5天涨跌
事件发生前10天涨跌
事件发生后股价涨跌
规则 说明
规则1 发展能力=0.074×净利润增长率
规则2 现金流水平=0.074×全部现金回收率
规则3 盈利能力=0.083×净资产收益率+0.074×成本费用利润率+0.083×营业利润率+0.078×资产报酬率
规则4 经营能力=0.088×固定资产周转率+0.078×应收账款周转率+0.088×总资产周转率+0.088×流动资产周转率
规则5 风险水平=0.069×经营杠杆+0.0698×综合杠杆+0.064×财务杠杆
规则6 财务指标=发展能力+现金流水平+盈利能力+经营能力+风险水平
规则7 非财务指标=0.17×专利数量+0.392×社会责任+0.545×媒体和分析机构关注度+0.352×信息披露+0.441×子公司数
规则8 舆情=1×正面评论数+0×中性评论数+(-1)×负面评论数
规则9 股价后续发展得分=0.65×财务指标+0.17×非财务指标+0.18×舆情
规则10 股价得分≥90 →股价极有可能上涨, 61<股价得分<89→股价可能上涨, 31<股价得分<60→股价持平, 股价得分<30→股价下跌
概念类 相似度
Sim (产品危机, 人事危机) 4/5
Sim (公共政策, 产品创新) 3/5
属性名称 乐视案例 贵州茅台案例 相似度 属性权重 加权相似度
所处行业 传播文化 食品饮料 0 0.05 0
金融舆情 -0.285 -0.263 0.978 0.20 0.196
财务状况 65.62 150.34 0.511 0.36 0.184
非财务状况 153.44 44.13 0.221 0.09 0.020
金融事件 经营危机、前5天股价下跌、前10天股价下跌、后5天股价下跌 产品危机、前5天股价上涨、前10天股价下跌、后5天股价下跌 0.690 0.30 0.207
相似度总和 0.607
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