Dynamic Decision Model of Real Estate Investment Portfolio Based on Wireless Network Communication and Ant Colony Algorithm

Abstract

From reform and opening to the comprehensive construction of a well-off society, the rapid growth of the national economy and the advancement of urbanization have promoted the rapid development of China’s real estate industry. The real estate industry has become a pillar growth point in the development of the national economy. At the same time, China’s real estate markets also continue to mature. However, due to the short development time of my country’s real estate market, imperfect management mechanism, irregular organization, and other issues, coupled with the fierce competition and internationalization of the market investment environment, the risk of investment accumulation in the real estate industry is also increasing. Therefore, in real estate investment decision-making, it is of far-reaching significance to study how to control real estate investment risks and promote the healthy and stable development of the real estate industry. The purpose of this article is to build a set of investment portfolios based on the ant colony algorithm to diversify risks and obtain returns, so that the constructed investment portfolios will minimize the risk when the return reaches a certain amount of time. This article first gives a general introduction to wireless network communication and then analyzes the risk of real estate project investment. First, the variance is used as a measure of risk to establish a dynamic model of the real estate development project portfolio, and the ant colony algorithm is introduced to the investment risk of real estate development projects. In the dynamic analysis, an improved portfolio model was established, and the two were compared through case analysis. The experimental results show that under the condition of the same net present value and investment payback period, the ant colony algorithm based on variance is invested in lot H. The ratio is obviously higher, and the capital investment ratio of lot H based on the ant colony algorithm is obviously lower. The difference between the two is 30.1%.