Machine Learning Based Return Prediction for Digital Financial Portfolios

With the continuous growth of the national economy and the expansion of market demand, traditional inance has gradually turned to digital transformation, and the emergence of digital inance has brought new breakthroughs to the economy.With the continuous development of the times, in order to meet the needs of the market, digital inance and commercial investment are constantly integrated.Therefore, this paper selects the returns and risks of digital inancial investment as the research topic, and predicts the investment returns of the ive major online banks by analyzing the digital inancial portfolio investment return prediction system.The machine learning algorithm is introduced to optimize the digital inancial portfolio investment return prediction system.The investment return rate is predicted by the optimized digital inancial portfolio investment return prediction system, and then compared with the actual investment return rate.The experimental results show that the predicted value of the traditional digital inancial portfolio investment return prediction system for the online bank inancial management return rate differs from the actual return rate by 1%-2%, while the predicted value range of the digital inancial portfolio investment return prediction system for the online bank inancial management return rate is the same as the luctuation range of the actual return rate.From the experimental data, it can be seen that the digital inancial portfolio investment return prediction system based on machine learning can effectively improve the prediction ability of the digital inancial portfolio investment return prediction system, making the predicted value closer to the actual value and increasing the reliability of the prediction.This paper provides reference value for the optimization and improvement of the digital inancial portfolio investment return prediction system and contributes to the development of digital inance.