۱- Introduction

۲- Establishment of Internet of Things investment decision platform database

۳- Investment decision model based on big data mining technology

۴- Example analysis

۵- Conclusion

References

Abstract

With the continuous improvement of the global securities market, the market competition is unprecedented fierce. In the aspect of investment decision support system, there is an urgent need to continuously absorb new information processing technologies and improve the scientific and standardization of decision-making, so as to achieve the goal of improving investment decision-making efficiency and stabilizing investment returns. Firstly, this paper introduces the defect that the database, model base and knowledge base are designed and implemented independently in the traditional decision support system. Then, constructing a unified and efficient data processing platform for Internet of Things based on DMFS technology, which realizes the integration of database and model, and innovatively establishes a data mining model facing market big data, dynamically analyzes and proposes investment decisions. Finally, the operating income data of a listed company in recent ten years are selected for simulation, which verifies the efficiency of the model system in processing dynamic data and the stability of investment income.

INTRODUCTION

With the continuous development of the global economy, the market situation is becoming more and more complex, and the investment decision-making of enterprises becomes more and more difficult [1]. As the most critical and important decision in all the decisions of an enterprise, mistakes in investment decisions will lead to huge losses for the enterprise. Investment decision usually refers to the investment decision made by the investor after investigation, analysis and demonstration of the enterprise or project [2]. Therefore, how to realize the accurate analysis of the investment prospect has become the research focus of most scholars[3]. He studied the investment decision-making optimization framework for energy-saving renovation of several buildings under the constraint of fiscal budget[4]. Proposing a multi-objective optimization model with economic objective as net present value and profit time and environmental objective as energy saving and emission reduction objective, and designing an intelligent optimization method combining particle swarm optimization and genetic algorithm, searching the investment strategy for transformation [5]. Gao constructed an analysis opinion model based on evidential reasoning rules, which taking stock reports of financial analysts as input and generates portfolio strategies through evidential portfolio[6]. Sevastianov and Dymova introduced Dempaser-Shafer theory and fuzzy set theory into an expert trading system that simulates human decision-making process, providing suggestions for traders to buy and sell stocks or other financial instruments by considering factors such as price history, technical analysis indicators, and recognized trading rules [7].