Pub. 7 2016 Issue 4

Below is a list of our top 25 sectors with the lowest correla- tions to the general economy. In addition, we have included a volatility measure as a proxy for risk letting you know what areas you might need to move with caution. Putting Cross-correlations Into Action Banks should attempt to correlate income, property values or market values to have an understanding of how various sec- tors interact with each other. We correlated the above sectors to the general economy, and we also look at similar data based on loan type, asset class (such as looking at how the investment portfolio moves relative to real estate), specific NAICS code, and geography. There are market indices such as commercial real estate REITs, transportation, utility and others that can at least get your credit team in the right ballpark of how different sectors move together. Bankers can use the industries that apply to the bank, and as long as your data is representative and homogeneous enough, bankers can create a correlation matrix in Excel (using the “correl” function) in order to view the relationship of every sector on every other sector. In this manner, lending and credit teams can focus on those sectors with low correlations. Weight each sector by the outstanding loan amount and apply the cross-correlations and bankers now have a more sophisticated tool for managing their loan portfolio. Breaking your credit portfolio into various loan types is interesting, but may not be instructive enough to serve to manage risk. Understand and construct your loan portfolio using correlation analysis and your bank can gain a significant strategic advantage against community banks that are not paying attention to how their credit risks align.  Chris Nichols is theChief StrategyOfficer for CenterState Bank, a $5 billion, publicly traded Florida bank. As Chief Strategy Officer, Chris specializes in predictive analytics, marketing, pricing, technology/innovation, risk management and creating superior bank performanc