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Imputation of Missing Values in the Fundamental Data: Using MICE Framework

Author

Listed:
  • Balasubramaniam Meghanadh

    (CRISIL GR&A)

  • Lagesh Aravalath

    (CRISIL GR&A)

  • Bhupesh Joshi

    (CRISIL GR&A)

  • Raghunathan Sathiamoorthy

    (CRISIL GR&A)

  • Manish Kumar

    (CRISIL GR&A)

Abstract

Revolutionary developments in the field of big data analytics and machine learning algorithms have transformed the business strategies of industries such as banking, financial services, asset management, and e-commerce. The most common problems these firms face while utilizing data is the presence of missing values in the dataset. The objective of this study is to impute fundamental data that is missing in financial statements. The study uses ‘Multiple Imputation by Chained Equations’ (MICE) framework by utilizing the interdependency among the variables that wholly comply with accounting rules. The proposed framework has two stages. The initial imputation is based on predictive mean matching in the first stage and resolving financial constraints in the second stage. The MICE framework allows us to incorporate accounting constraints in the imputation process. The performance tests conducted on the imputed dataset indicate that the imputed values for the 177 line items are good and in line with the expectations of subject matter experts.

Suggested Citation

  • Balasubramaniam Meghanadh & Lagesh Aravalath & Bhupesh Joshi & Raghunathan Sathiamoorthy & Manish Kumar, 2019. "Imputation of Missing Values in the Fundamental Data: Using MICE Framework," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 17(3), pages 459-475, September.
    • Handle: RePEc:spr:jqecon:v:17:y:2019:i:3:d:10.1007_s40953-018-0142-7
    DOI: 10.1007/s40953-018-0142-7
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    References listed on IDEAS

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    1. Paul Kofman & Ian Sharpe, 2000. "Imputation Methods for Incomplete Dependent Variables in Finance," Econometric Society World Congress 2000 Contributed Papers 0409, Econometric Society.
    2. Paul Kofman & Ian Sharpe, 2000. "Imputation Methods for Incomplete Dependent Variables in Finance," Research Paper Series 33, Quantitative Finance Research Centre, University of Technology, Sydney.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Multiple imputation; MICE; Fundamental data; Accounting and financial statement;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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