If a picture is worth a thousand words, then an action is worth a thousand pictures. At SGI we follow a disciplined approach to guide our investment actions. Our Optimized strategy has four encompassing steps which start and ends with risk management.
Understand Market Risk
Our first step is crucial. We initiate a market risk assessment. This helps us to better understand what risks are present in the market and how those risks may affect equities. Specifically, we utilize an equity risk covariance matrix and cross correlations among all equities to identify total equity risk. There are obvious differences in equities. Some are more volatile, others more stable in their price patterns and how each company relates to one another. Utilizing optimization we are better able to understand the relationships between each company and the market. Understanding these relationships ensures we are able to more effectively take advantage of the opportunities to reduce risk and position our strategy on the efficient frontier.
Constraints are optimal when they bring more diversification, protection and suitable exposure while maintaining a higher transfer coefficient and ultimately greater return. To this end, we have spent significant effort and gained invaluable experience enabling us to have created an optimal constraint process. Following our process we answer the hard questions, i.e., how many securities are optimal to manage risk? How much exposure is best in any one name, industry or sector of the market? Having answers to these types of questions empowers SGI to manage with clarity and enhanced perspective.
Low Volatility Alpha Model
We know there are many different definitions of alpha. To us, alpha is the active return of an equity security. To estimate future returns of an equity security is not trivial. There are many factors that contribute to equity returns and they may vary from security to security. We believe there are unique drivers for low volatility stocks. Our alpha stock selection model diversifies among multiple factors that perform well, or successfully predict returns, across multiple economic and business cycles as well as across different industries and sectors. These factors may include valuation metrics, growth estimates, profitability, momentum and liquidity factors, etc.
To consistently enhance our active return estimates, we constantly research our factors to ensure each has significant power to predict future returns and that we have adequate factor diversification. The goal in creating a low volatility alpha model is not to perfectly predict returns, but to ensure the alpha model can take advantage of the steepness of the efficient frontier curve. By so doing, we feel we are able to create more optimized low volatility portfolios.
Fundamental Overlay Process
There is a difference between real world portfolio management where difficulties exist, e.g., taxes and trading costs, and academic or paper portfolios. A strategy must be scalable, flexible and incorporate such difficulties. The ability to professionally manage equity portfolios can only be fully appreciated through real world experience. At SGI we have such expertise and value wisdom over knowledge to efficiently construct optimized low volatility portfolios that effectively manage equity risk.
We feel strongly that quantitative alpha and risk models cannot adequately capture all of the future drivers of expected returns and risk. For example, a risk model will not tell you that the CFO or chairman recently resigned. Quantitative models must have a reality check.
Our fundamental overlay process ensures our optimized risk and return characteristics are fully capable of being implemented. We analyze the trading ability (avgerage daily volume, percentage change, tick data, etc.) and alpha ability (traditional fundamental analysis) of each stock we buy or sell. We feel this extra effort is unique and substantially helps manage risk throughout the investment process and minimize portfolio drawdowns.