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2018 | OriginalPaper | Buchkapitel

The Application of Artificial Intelligence in Financial Evaluation

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Abstract

Artificial intelligence is a new subject which has been applied in many fields. With the rapid development of China’s market economy, more and more investors participate in the stock market, which they hope to share the fruits of economic growth through equity investment. Under such circumstances, people like to evaluate the financial to gain more financial income. Although, the human trader is more rational than the machine when doing a comprehensive analysis. But there are too much data and information in this economic subject. It is hard for people to figure it out all by manual. So they try to apply artificial intelligence in this field, especially financial evaluation. In this paper, we will use the Shanghai Composite Index as a representative of the financial community, using macroeconomic indicators and artificial intelligence methods to predict the trend of the stock market. The application of artificial evaluation will be helpful to analyze the financial data more accurately in daily times.

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Literatur
1.
Zurück zum Zitat Bahrammirzaee, A.: A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems. Neural Comput. Appl. 19(8), 1165–1195 (2010)CrossRef Bahrammirzaee, A.: A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems. Neural Comput. Appl. 19(8), 1165–1195 (2010)CrossRef
2.
Zurück zum Zitat Kaastra, I., Boyd, M.: Designing a neural network for forecasting financial and economic time series. Neurocomputing 10(3), 215–236 (1996)CrossRef Kaastra, I., Boyd, M.: Designing a neural network for forecasting financial and economic time series. Neurocomputing 10(3), 215–236 (1996)CrossRef
3.
Zurück zum Zitat Kou, G., Peng, Y., Wang, G.: Evaluation of clustering algorithms for financial risk analysis using MCDM methods. Inf. Sci. 275, 1–12 (2014)CrossRef Kou, G., Peng, Y., Wang, G.: Evaluation of clustering algorithms for financial risk analysis using MCDM methods. Inf. Sci. 275, 1–12 (2014)CrossRef
4.
Zurück zum Zitat Ruan, D., Fedrizzi, M., (eds.): Soft Computing for Risk Evaluation and Management: Applications in Technology, Environment and Finance, vol. 7, pp. 321–327. Physica, Heidelberg (2012) Ruan, D., Fedrizzi, M., (eds.): Soft Computing for Risk Evaluation and Management: Applications in Technology, Environment and Finance, vol. 7, pp. 321–327. Physica, Heidelberg (2012)
5.
Zurück zum Zitat Rouhani, S., Ghazanfari, M., Jafari, M.: Evaluation model of business intelligence for enterprise systems using fuzzy TOPSIS. Expert Syst. Appl. 39(3), 3764–3771 (2012)CrossRef Rouhani, S., Ghazanfari, M., Jafari, M.: Evaluation model of business intelligence for enterprise systems using fuzzy TOPSIS. Expert Syst. Appl. 39(3), 3764–3771 (2012)CrossRef
6.
Zurück zum Zitat Strong, A.I.: Applications of artificial intelligence & associated technologies. Science 5, 6 (2016) Strong, A.I.: Applications of artificial intelligence & associated technologies. Science 5, 6 (2016)
7.
Zurück zum Zitat Wu, D.D., Chen, S.-H., Olson, D.L.: Business intelligence in risk management: Some recent progresses. Inf. Sci. 256(3), 1–7 (2014) Wu, D.D., Chen, S.-H., Olson, D.L.: Business intelligence in risk management: Some recent progresses. Inf. Sci. 256(3), 1–7 (2014)
8.
Zurück zum Zitat Omoteso, K.: The application of artificial intelligence in auditing: Looking back to the future. Expert Syst. Appl. 39(9), 8490–8495 (2012)CrossRef Omoteso, K.: The application of artificial intelligence in auditing: Looking back to the future. Expert Syst. Appl. 39(9), 8490–8495 (2012)CrossRef
9.
Zurück zum Zitat Kisi, O., Shiri, J., Nikoofar, B.: Forecasting daily lake levels using artificial intelligence approaches. Comput. Geosci. 4(1), 169–180 (2012)CrossRef Kisi, O., Shiri, J., Nikoofar, B.: Forecasting daily lake levels using artificial intelligence approaches. Comput. Geosci. 4(1), 169–180 (2012)CrossRef
11.
Zurück zum Zitat Rutkowski, L., et al. (eds.): Artificial intelligence and soft computing. In: Proceedings of 15th International Conference, ICAISC 2016, Part II, Zakopane, Poland, vol. 9693, Springer, 12–16 June 2016 Rutkowski, L., et al. (eds.): Artificial intelligence and soft computing. In: Proceedings of 15th International Conference, ICAISC 2016, Part II, Zakopane, Poland, vol. 9693, Springer, 12–16 June 2016
12.
Zurück zum Zitat Niu, H., Wang, J.: Volatility clustering and long memory of financial time series and financial price model. Digital Signal Proc. 23(2), 489–498 (2013)MathSciNetCrossRef Niu, H., Wang, J.: Volatility clustering and long memory of financial time series and financial price model. Digital Signal Proc. 23(2), 489–498 (2013)MathSciNetCrossRef
13.
Zurück zum Zitat Abuel-Naga, H.M., Bouazza, A.: Numerical experiment-artificial intelligence approach to develop empirical equations for predicting leakage rates through GM/GCL composite liners. Geotext. Geomembr. 42(3), 236–245 (2014)CrossRef Abuel-Naga, H.M., Bouazza, A.: Numerical experiment-artificial intelligence approach to develop empirical equations for predicting leakage rates through GM/GCL composite liners. Geotext. Geomembr. 42(3), 236–245 (2014)CrossRef
Metadaten
Titel
The Application of Artificial Intelligence in Financial Evaluation
verfasst von
Haipeng Zhu
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-60744-3_11