How High Efficiency of the Chilean stock Market Does Impact on Energy Transition? Research Using Deep seek AI Optimization

Abstract

The aim of the study is to determine the impact of efficiency and integration of the Chilean stock market on Energy transition using Deep Seek AI optimization. The novelty of the research lies in the systematization of aspects of efficiency and integration of financial markets that are heavily dependent on renewable energy sources. The methodology is based on the Kramer-von Mises method and market performance assessment tests using Deep Seek AI optimization. Using two recent network expansions in the Chilean electricity market, it was found that market integration has led to a convergence of prices between regions, increasing electricity production. It is proved that the methods of behavioral theory are the most promising for studying the effectiveness of Chili markets. The main results show that there is a problem of reducing electricity production from renewable sources between demand centers as a result of crises. The emphasis of market integration on investment effects is studied. It is concluded that the market integration and high efficiency of the Chilean stock market increase the efficiency of resource allocation due to the benefits of trade and stimulate the emergence of new renewable energy sources. The practical significance of the research results lies in the application by regulators of aspects of efficiency and integration of financial markets in the transition of the economy to renewable energy sources.

Keywords

• ai
• deep seek
• artificial general intelligence
• optimization
• clean energy
• eugene fama
• chile
• integration
• efficiency
• stock market