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Stock prediction and investment portfolio optimization method and system, computer and storage medium

A combinatorial optimization and stock technology, applied in computer and storage media, stock forecasting and investment portfolio optimization methods, and system fields, can solve problems such as low convergence of solution sets, poor algorithm combination optimization ability, and low global search ability, etc., to achieve improved Benefits, optimization, quality improvement, and risk reduction effects

Pending Publication Date: 2022-03-08
JINAN UNIVERSITY
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AI Technical Summary

Problems solved by technology

Due to the large fluctuations in stock data, there are certain differences between future data and historical data, so using historical data to configure does not meet the actual needs, and there are shortcomings such as low global search ability of the solution and low convergence of the solution set.
At the same time, many intelligent optimization algorithms can optimize investment portfolios to a certain extent, but the algorithms themselves still have problems such as poor combination optimization capabilities and optimization results that do not meet the needs of implementation

Method used

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  • Stock prediction and investment portfolio optimization method and system, computer and storage medium
  • Stock prediction and investment portfolio optimization method and system, computer and storage medium
  • Stock prediction and investment portfolio optimization method and system, computer and storage medium

Examples

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Embodiment 1

[0070] Such as figure 1 As shown, a kind of stock prediction and portfolio optimization method described in this embodiment comprises the following steps:

[0071] S1. Create a support vector machine regression model;

[0072] S2, applying the fusion algorithm DETS based on tabu search (TS) and differential evolution (DE) to optimize the parameters of the support vector machine regression model;

[0073] The differential evolution algorithm can perform random parallel global search, can effectively solve complex global optimization problems, and has little dependence on the initial value, so it is suitable as a front-end initial solution generation algorithm. As a global step-by-step optimization algorithm, the tabu search algorithm can accept inferior solutions and has good climbing ability, so it is suitable as a back-end optimization algorithm.

[0074] The differential evolution algorithm and the tabu search algorithm are integrated. In this embodiment, the out-of-bound...

Embodiment 2

[0147] Such as Figure 6 As shown, a kind of stock forecasting and portfolio optimization system described in this embodiment includes a creation module 1, an optimization module 2, a stock forecasting module 3, and a portfolio module 4;

[0148] in,

[0149] The creation module 1 is used to create a support vector machine regression model;

[0150] The optimization module 2 is used to optimize the support vector machine regression model created by the creation module 1;

[0151] The stock prediction module 3 adopts the optimized support vector machine regression model to predict the stock;

[0152] The investment portfolio module 4 combines the fusion algorithm DETS and Pareto sorting theory to obtain an algorithm NSDE-TS suitable for multi-objective optimization, and combines it with forecast data to generate a stock portfolio plan that meets actual requirements.

Embodiment 3

[0154] A computer described in this embodiment includes a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the program, the steps of the above method for stock forecasting and investment portfolio optimization are realized. .

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Abstract

The invention discloses a stock prediction and investment portfolio optimization method and system, a computer and a storage medium, historical data and prediction data are fused into new data to improve the defects of a historical data set by adopting a fusion algorithm DETS based on tabu search and differential evolution, then investment portfolio configuration is carried out through combination of the fusion algorithm DETS and a Pareto sorting theory, and the optimization of the stock prediction and investment portfolio is realized. Therefore, the two difficulties of difficult prediction and difficult combinatorial optimization are solved, the defects that an existing investment combinatorial optimization algorithm focuses on historical data and has low global search ability of solutions, high time complexity, low solution set convergence and the like are avoided, the solving speed and the optimization quality of the solution set are greatly improved, and the purposes of improving the income and reducing the risk are achieved.

Description

technical field [0001] The invention relates to the technical field of stock investment forecasting, in particular to a stock forecasting and portfolio optimization method, system, computer and storage medium. Background technique [0002] In terms of stock forecasting models, traditional stock forecasting mainly uses linear programming algorithms to solve the problem. It is a basic analysis method for establishing a linear model between stocks and influencing economic factors, and using the stock's own time series data for forecasting, and establishing a univariate time series model. Technical analysis methods such as autoregressive conditional heteroscedastic models. Most of the existing research on new stock forecasting adopts the method of fusion machine learning. Hui proposed a GA-BP neural network stock forecasting model based on real number coding by combining genetic algorithms. However, this method has low optimization of machine learning parameters and unstable re...

Claims

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Application Information

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IPC IPC(8): G06Q40/04G06Q40/06G06N3/12
CPCG06Q40/04G06Q40/06G06N3/126
Inventor 张学聪樊锁海鲁嘉
Owner JINAN UNIVERSITY
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