At Piedmont, one of our key tools in the investment research process is our quantitative Alpha Forecast Model, a stock selection model. This model serves as an objective representation of our investment philosophy and provides a systematic tool for filtering a large universe of stocks. It acts as a quick and efficient information filter and is designed to complement our fundamental research by filtering out stocks with the greatest excess return potential.
The Alpha Forecast Model used at Piedmont is a regression based multifactor model that attempts to forecast alphas (excess returns) for a universe of stocks. The factors that go into the equation are intuitive, generate long-term excess returns, are consistent and predictable and have low correlation with other factors in the model. The model, like our process, is dynamic: the weightings of each of the factors are adjusted monthly ensuring that stocks found attractive by the model reflect changing company fundamentals as well as the market price of risk. The outputs of this dynamically adjusted model are used to create buy lists for our portfolios.
Quantitative Analysis – Optimized Products
Piedmont employs a specific technique for forecasting stocks’ excess return potential for its “Optimized” products (Midcap Core and Large Cap Value). The model is a fundamentally-based, quantitative algorithm driven by earnings expectations, insider transactions, valuation and cash flow measures. We employ an alpha scoring process based on each model’s investment coefficient (IC) and cross-sectional distribution of our investable universe by each model (Z-score). The goal of the process is to consistently deliver the following set of attributes to each client’s portfolio:
The “ideal” stock has:
- Earnings growing faster than consensus expectations;
- Strong and improving cash flow to support continued earnings growth;
- The stock is under-valued relative to its peers; and
- Corporate insiders are buying their own stock.