MACHINE LEARNING'S IMPACT ON ASSET PRICING AND DERIVATIVE STOCK MARKETS IN THE USA AND AUSTRALIA
Keywords:
Machine Learning,, Asset Pricing, Derivative Markets, Stock Prediction,, Financial Technology,, USA, AustraliaAbstract
This study investigated the influence of machine learning (ML) techniques on asset pricing and derivative stock markets in the United States and Australia from 2010 to 2024. Using a comprehensive dataset of stock prices, derivative contracts, and macroeconomic indicators, we employed various ML algorithms to analyze pricing patterns, predict market trends, and assess risk factors. Our findings revealed that ML significantly enhanced the accuracy of asset pricing models and improved the efficiency of derivative markets in both countries. However, the impact was more pronounced in the US market due to its higher trading volume and technological adoption rate. This research contributes to the growing body of literature on the intersection of artificial intelligence and financial markets, offering insights for investors, regulators, and policymakers.
