| dc.description.abstract | This research presents an in-depth exploration of a wide array of algorithms, techniques, methods and models
used for forecasting asset values. Significantly, the study introduces an unprecedented approach, featuring a dedicated
model for precise price forecasting and another for recommending optimized strategies. By assessing and contrasting the
approaches and outcomes of asset value prediction across different fields, this paper study aims to harness the power of
Artificial Intelligence (AI) in forecasting asset prices and tailoring investment strategies. Implemented system integrates
the Prophet Model for precise price forecasting and employs Genetic Algorithms for investment strategy generation.
Through a systematic evaluation of the system, we demonstrate its capacity to provide accurate asset price predictions,
outperform traditional investment strategies and mitigate risks effectively. Empirical unit testing showcased impressive
results such as gold model with a 4.76% MAPE and an R-squared value of 0.9795 and oil model with notable metrics such
as a Mean Absolute Error of 6.80, and Root Mean Squared Error of 10.92. Every single user, across the board, either
strongly agreed or agreed that the investment recommendations provided valuable insights and 92.4% perceiving system
predictions as very accurate. It further delves into the challenges and limitations, such as the quality of data used and model
interpretability, underscoring the imperative for robust, compliant and interpretable forecasting models. Additionally, the
study explores future directions in the domain, advocating for the expansion of asset classes and the integration of Natural
Language Processing (NLP) into the system. | en_US |
