Table 4.
DBN applications in financial research
| Models | Targets | Markets | Data | Results | Innovation | References |
|---|---|---|---|---|---|---|
| DBN | Stock price trend prediction | Stock | The data are smoothed. | The new DBN combination proposed in this chapter has the lowest error rate. | A new neural network model for time series forecasting with high accuracy is proposed. | Kuremoto et al.92 |
| DBN | Stock price prediction | Stock | Historical trading data for the 400 stocks in the S&P 500 index | The model constructs systematic trading that outperforms the basic buy-and-hold strategy. | An automatic stock decision support system is established by using DBN and oscillatory box theory. | Zhu et al93 |
| DBN | Stock price prediction | Stock | S&P 500 Index (January 1, 1985 to December 31, 2006) | The results obtained by deep neural networks are better and more stable than the basic results. | New deep learning algorithms are used to predict financial stock data | Batres-Estrada98 |
| DBN | Forecast of financial distress of the company |
Corporate Finance |
Financial data for 966 French firms | The classification accuracy of the model is 76.8% | Deep learning and support vector machine are combined. | Lanbouri and Achchab95 |
| DBN | Exchange rate price forecast |
Foreign exchange | Weekly data for the three exchange rates GBP/USD, Indian Rupee/USD, and Brazilian real/USD | Compared with traditional methods, FFNN is more suitable for forecasting exchange rates and their effects. | An improved DBN algorithm (FFNN) is proposed to forecast the exchange rate | Shen et al.96 |
| DBN | Forecast of the weekly movement direction of the Treasury portfolio |
Treasury bond futures |
Daily and two-week average price data for 5 and 10-year Treasury futures. | The portfolio has a trade size of 10 units and a profit of 10 units, which is about 90,000 dollars. | Using the DBN of stack-constrained Boltzmann mechanism, an intermediate frequency trading strategy is designed |
Sharang and Rao97 |
| DBN | Financial time series methods |
Stock | Sample of financial series data of closing prices of all stocks in Shanghai and Shenzhen stock markets during the 100 working days prior to October 20, 2012 |
The accuracy of financial data samples selected by DBN model in quantitative decision analysis of financial time series data can reach 90.54% | Presents an improved modeling based on DBN and decision algorithm | Zeng et al.99 |