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A new hybrid method with data-characteristic-driven analysis for artificial intelligence and robotics index return

Yue-Jun Zhang1,2, Han Zhang1,2, Rangan Gupta3

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Forecasting artificial intelligence and robotics index returns is crucial for market stability. A new hybrid model, EEMD-PSO-LSSVM-ICSS-GARCH, effectively predicts these complex, time-varying returns.

Keywords:
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Area of Science:

  • Financial econometrics
  • Artificial intelligence applications
  • Robotics market analysis

Background:

  • Forecasting returns for the Artificial Intelligence and Robotics (AIRO) Index is vital for financial market stability and AI industry growth.
  • Existing methods may not fully capture the complex, time-varying nature of AIRO index returns.
  • Investors require reliable references for AI index investments.

Purpose of the Study:

  • To propose innovative hybrid methods for forecasting AIRO index returns.
  • To account for the multiple structural, time-varying, and nonlinear characteristics of the index.
  • To enhance the accuracy and reliability of AI index return predictions.

Main Methods:

  • Ensemble Empirical Mode Decomposition (EEMD) for index return decomposition.
  • Modified Iterative Cumulative Sum of Squares (ICSS) algorithm for structural breakpoint identification.
  • Hybrid forecasting models combining Particle Swarm Optimization-Least Square Support Vector Machine (PSO-LSSVM) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) type models.

Main Results:

  • AIRO index returns exhibit complex structural, time-varying, and nonlinear characteristics.
  • The proposed hybrid forecasting method (EEMD-PSO-LSSVM-ICSS-GARCH) demonstrates optimal forecasting performance.
  • The model effectively captures the high complexity and mutability of the AIRO index returns.

Conclusions:

  • The AIRO index presents significant complexity, necessitating advanced forecasting approaches.
  • The novel EEMD-PSO-LSSVM-ICSS-GARCH model offers superior predictive accuracy for AIRO index returns.
  • This research provides a more reliable tool for investors in the artificial intelligence and robotics sectors.