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financial performance and sustainability factors, which
are increasingly influential in investment decision-
making while reducing investment risk(Hoepner et al.,
2017).
7 FUTURE WORK
Several researchers have recently applied different
models for predicting global companies' financial
performance and stock prices in diverse sectors. The
domain being contemporary, new applications with
accurate forecasting is the demand of end users.
Considering these, the researcher suggests future
work involving the following.
• Feature Engineering: Explore new techniques to
identify and extract relevant features the data. This
can provide additional insights and improve models'
performance.
• Applying Alternative Data Sources: An
Investigation to integrate alternate data sources to
capture second-period data. The Analysis will
provide unique perspectives to enhance model
prediction capabilities.
• Real-time Prediction: The Scope to develop models
conducting real-time prediction exists by streaming
real-time data using a fast interface algorithm.
• Interpretable and Explainable Models: Focus on
developing interpretable and explainable models that
can provide insights into the factors driving share
price predictions. This is particularly important for
regulatory compliance, risk management, and
gaining trust from investors and stakeholders.
• Robustness and Generalization: Enhance the
robustness and generalization capabilities of share
prediction models to handle various market
conditions, including market crashes, economic
downturns, or abnormal events. Investigate
techniques for model recalibration and adaptation to
changing market dynamics.
• Real-world Evaluation: Validate share prediction
models in real-world scenarios and compare their
performance against benchmarks and industry
standards. Conduct rigorous evaluation using
historical data and consider factors like transaction
costs, slippage, and trading volume impact.
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