TARFA: A Novel Approach to Targeted Accounting Range Factor Analysis for Asset Allocation

  • 0Institute of Finance and Technology, University College London, London WC1E 6BT, UK.

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Summary

This summary is machine-generated.

This study introduces the TARFA valuation framework, integrating traditional and modern methods to identify key accounting factors driving superior investment returns. The novel framework consistently outperformed market returns, enhancing asset allocation strategies.

Area Of Science

  • Finance
  • Investment Management
  • Financial Accounting

Background

  • Company valuation is crucial for investment decisions and portfolio management.
  • Existing valuation methods require integration of traditional and modern approaches for enhanced accuracy.
  • Identifying key return-driving factors is essential for optimizing investment strategies.

Purpose Of The Study

  • To introduce a novel valuation framework (TARFA) for comparable company analysis.
  • To identify investor-preferred, return-driving accounting factors.
  • To provide actionable insights for optimizing asset allocation and portfolio performance.

Main Methods

  • Integrated traditional and modern valuation approaches.
  • Analyzed 68 accounting measures to identify key return drivers.
  • Developed general and sector-specific TARFA models.
  • Introduced the Relative Equity Score for identifying undervalued equities.

Main Results

  • The TARFA framework identified three key accounting factors driving superior returns.
  • Both general and sector-specific TARFA models consistently outperformed population returns.
  • The general TARFA model demonstrated superior performance in broader market contexts.
  • Key financial ratios showed stability over time.

Conclusions

  • The TARFA framework offers a robust, integrated approach to company valuation.
  • The identified accounting factors and Relative Equity Score enhance the ability to find undervalued equities.
  • The framework provides valuable tools for investors and analysts to optimize portfolios.

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