Whitefield believes that consistent and successful investment outcomes can be provided with the greatest reliability through a defined and disciplined process.

Our investment process has five stages:

Raw Data Collection We utilise a range of data sources across a variety of subject matter including historical company financials, broker forecasts and revisions, economic data, raw materials data and market data.

Proprietary Stock Models Our proprietary stock models combine proprietary valuation inputs and assumptions with consensus data in a manner designed to minimise our own judgment biases through the accurate assessment of long term drivers of shareholder value creation.

Data Processing Our customised analytical processes and measures utilise the raw data and stock model outputs, and have been designed to suit our ultimate purpose of assessing companies’ relative Quality and Intrinsic Value.

Stock Classification Based on the outputs of our data processing analysis, stocks in our coverage universe are assessed, ranked and allocated against our Structural Attractiveness (SA) and Price-to-Value-Cycle (PVC) criteria. These quantitative conclusions are qualitatively assessed by analysts and either confirmed or overruled based on a rigorous set of criteria designed to minimise the influence of our own judgment biases.

Portfolio Construction & Risk Management Whitefield’s portfolio is then constructed by the Portfolio Manager using the SA and PVC assessments and with reference to our overarching portfolio framework which utilises the most profitable and suitable combinations of SA and PVC classes in the light of our experience and process back-testing.

We also embrace a philosophy of continuous process enhancement to ensure that our methodology is best able to satisfy our objectives in the light of technological advancements and changes in the market environment. Our process of continual enhancement draws upon the experience of our investment personnel, an active process of methodology research and review and rigorous empirical testing of enhancements prior to implementation.