Auditable Appraisal: Best Practice

This class builds on data science methods, software tools, and thinking patterns – adding the needed protocol to produce fully reproducible valuation reports:

  1. Overview and impact of the auditable valuation paradigm;

  2. Workbook protocol, audit trail principles;

  3. Reconciling to traditional practices;

  4. Transforming ordinal predictor variables;

  5. Estimating confounding bias;

  6. Case study practice and templates;

  7. Contrasting review with audit;

  8. Checklist of user and regulatory audit applications.

  9. Best practices and standards compliance

The integration of the use of spreadsheets with the analyst package R and RStudio, as well as applying the most current R packages available for valuation and risk assay will be presented.

Risk analytics for client use are integrated with the carry-through of reliability estimation from assumptions, problem definition, market set delineation, algorithm choice, interpretation and the audit function.

Valuation for portfolio purposes is enabled, and basics of client portfolio requirements are reviewed.  The investor viewpoint is highlighted.

Stats, Graphs and Data Science 1 & 2 are prerequisites for this course.