Intelligent Risk Evaluation for Investment Banking IPO Business Based on Text Analysis
Abstract
:1. Introduction
2. Literature Review
3. Methodology
3.1. Construction of Text Quality Analysis System Based on Prospectus
3.1.1. Chinese Characters Level
3.1.2. Vocabulary Level
3.1.3. Sentence Level
3.1.4. Chapter Level
3.2. Construction of Company Quality Analysis System Based on Prospectus
3.2.1. Compliance Status
3.2.2. Industry Status
3.2.3. Technology Status
3.2.4. Management Status
3.2.5. Financial Status
3.3. Construction of Risk Intelligent Evaluation System for Investment Banking IPO Business
3.3.1. Feature Selection Based on a Random Forest Model
3.3.2. Risk Prediction Based on Deep Neural Network
3.3.3. Performance Metrics of Machine Learning
4. Application of Risk Intelligent Evaluation System for Investment Banking IPO Business
4.1. Data
4.2. Statistical Features of Risk Evaluation Indicators for Investment Banking IPO Business
4.3. Feature Selection of Risk Evaluation Indicators for Investment Banking IPO Business
4.4. Risk Prediction for Investment Banking IPO Business Based on Random Forest
4.5. Risk Prediction for Investment Banking IPO Business Based on Deep Neural Network
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Lever | Feature | Indicator |
---|---|---|
Chinese character | validity of Chinese characters | the number of valid characters |
commonality of Chinese characters | the number of common characters | |
the number of sub-common characters | ||
Vocabulary | commonality of vocabulary | the number of common vocabularies |
part of speech complexity | the proportion of adverbs | |
vocabulary semantic difficulty | the proportion of financial vocabulary | |
Sentence | syntactic complexity | the proportion of adverbs |
the proportion of common vocabulary | ||
the proportion of financial vocabulary | ||
the proportion of valid characters | ||
the proportion of common characters | ||
the proportion of sub-common characters | ||
sentence length | the average number of characters in the sentence | |
the average number of vocabularies in the sentence | ||
Chapter | chapter length | the number of characters |
the number of vocabularies | ||
the number of sentences |
Level | Prospectus Section | Indicator |
---|---|---|
Compliance status | corporate governance and independence | the number of secondary titles |
the number of tertiary titles | ||
the number of quaternary titles | ||
the number of characters | ||
Industry status | business and technology: company’s main business, main products, or services; the basic situation of the industry in which the company operates | the number of tertiary titles |
the number of quaternary titles | ||
the number of characters | ||
market share | ||
sunrise industry or not | ||
Technology status | business and technology: company’s core technology and research and development; core technologies of the company’s main products | the number of tertiary titles |
the number of quaternary titles | ||
the number of characters | ||
attributes of science and innovation | ||
Management status | company basic situation: directors, supervisors, senior managers, and core technical personnel | the number of tertiary titles |
the number of quaternary titles | ||
the number of characters | ||
the disclosure of close relatives | ||
the number of directors | ||
the number of supervisors | ||
the number of senior managers | ||
the number of core technical personnel | ||
the average age of directors | ||
the average age of supervisors | ||
the average age of senior managers | ||
the average age of core technical personnel | ||
Financial status | financial and accounting information and management analysis: major financial indicators for the reporting period | the current ratio |
the asset–liability ratio | ||
accounts receivable turnover | ||
inventory turnover | ||
increase the rate of the main business revenue |
Passing Rate | Passing Time | Review Inquiries | Audit Replies | Legal Replies | Number of Samples | |
---|---|---|---|---|---|---|
Information technology | 66.98 | 254.72 | 5.51 | 4.64 | 3.06 | 318 |
High-end equipment | 76.92 | 219.31 | 5.85 | 4.77 | 3.54 | 13 |
New materials | 82.05 | 241.18 | 5.54 | 4.26 | 3.6 | 39 |
New energy | 70.33 | 257.55 | 5.77 | 4.35 | 3.15 | 91 |
Energy saving and environmental protection | 70 | 251.80 | 5.53 | 4.59 | 3.21 | 120 |
Biomedicine | 62.71 | 258.22 | 5.99 | 4.81 | 3.62 | 177 |
Others | 41.78 | 254.25 | 5.03 | 4.36 | 3.03 | 146 |
Total | 63.61 | 253.99 | 5.60 | 4.59 | 3.24 | 904 |
Accuracy Rate | Precision Rate | Recall Rate | |
---|---|---|---|
Feature selection | 0.6835 | 0.9730 | 0.8030 |
All features | 0.6859 | 0.9640 | 0.8015 |
Review Inquiries | Audit Inquiries | Legal Inquiries | Passing Time | |
---|---|---|---|---|
Training results | 0.3748 | 0.3744 | 0.4089 | 0.4126 |
Fitting results | 0.0831 | 0.2118 | 0.2067 | 0.0218 |
MAE | 515.8704 | 361.8981 | 248.3763 | 8.26 × 103 |
MSE | 2.50 × 103 | 1.15 × 103 | 536.2318 | 1.15 × 106 |
RMSE | 50.0357 | 33.8409 | 23.1567 | 1.07 × 103 |
Description of Risk | Main Feature |
---|---|
Review inquiries | Compliance status: secondary titles, tertiary titles, quaternary titles, the number of characters; the number of sub-common characters; the number of sentences; the attributes of science and innovation; the asset–liability ratio |
Audit inquiries | Compliance status: secondary titles, tertiary titles, quaternary titles, the number of characters; technology status: the number of characters; the proportion of financial vocabulary; the proportion of sub-common characters; the number of sub-common characters |
Legal inquiries | Compliance status: secondary titles, tertiary titles, quaternary titles, the number of characters; the proportion of common vocabulary; the proportion of financial vocabulary; the proportion of sub-common characters; the number of financial vocabularies |
Review time | The number of vocabularies; the number of adverbs; the number of common vocabularies; similarity; the proportion of adverbs; the proportion of sub-common characters; compliance status: tertiary titles, the number of sentences |
Accuracy Rate | Precision Rate | Recall Rate | |
---|---|---|---|
Dimension reduction variables | 0.6816 | 0.9333 | 0.8053 |
All variables | 0.7273 | 0.9839 | 0.8175 |
Review Inquiries | Audit Inquiries | Legal Inquiries | Passing Time | Initial Underpricing | |
---|---|---|---|---|---|
Fitting results | 0.1489 | 0.2007 | 0.1990 | 0.0157 | 0.0193 |
MAE | 2.9979 | 1.8473 | 1.4740 | 45.8540 | 0.0651 |
MSE | 13.7366 | 5.5815 | 3.0562 | 7786.5685 | 0.0133 |
RMSE | 3.7063 | 2.3625 | 1.7482 | 88.2415 | 0.1154 |
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Zhang, L.; Wang, C.; Liu, X. Intelligent Risk Evaluation for Investment Banking IPO Business Based on Text Analysis. Information 2024, 15, 498. https://doi.org/10.3390/info15080498
Zhang L, Wang C, Liu X. Intelligent Risk Evaluation for Investment Banking IPO Business Based on Text Analysis. Information. 2024; 15(8):498. https://doi.org/10.3390/info15080498
Chicago/Turabian StyleZhang, Lei, Chao Wang, and Xiaoxing Liu. 2024. "Intelligent Risk Evaluation for Investment Banking IPO Business Based on Text Analysis" Information 15, no. 8: 498. https://doi.org/10.3390/info15080498