The Basics of Portfolio Analytics

By Barry Solomon , last updated August 26, 2011

Portfolio analytics is a metric approach to analyzing investment portfolios by comparing their performance to various market and economic conditions. There are a number of software packages that utilize different tools to accomplish this. So be aware that there is no magic bullet for figuring out where the market is going or even where a particular investment is going. But a good approach with portfolio analytics will afford the investor the best information possible to make educated decisions in the face of changing market and economic conditions regarding the composition of an investment portfolio.

These tools tend to take into account both qualitative and quantitative factors in their analysis. They help investors to examine alternatives under different economic conditions and to deal with uncertainty. They examine different classes of assets and help investors to understand the expected performance of those assets and the associated risks, as well. They also examine the interrelationships of one asset class to another. If different classes tend to perform opposite to one another, they can act as a hedge to protect against the integrated portfolio's downside. On a more micro level, they can help you to examine the choices you have made within any asset class and to adjust your portfolio by buying or selling particular assets.

A portfolio analytic model can simulate the performance of your portfolio based on various economic scenarios and project the returns based on each one. It can project the types of compositional changes that you will have to make to maximize your upside or minimize your downside based on the various projected conditions. They can show you the effect, under each set of economic assumptions, of taking out money or of re-investing it in your portfolio.

These models are based on a set of assumptions about how the market, and asset performance in general, will move in the face of certain changing conditions. For example, most models will measure the impact of changes in the interest rates on the performance of the various classes of assets that make up a portfolio. A portfolio analytic model will generate any number of interest rate scenarios over the term that you are examining and project how the various asset classes will perform in each scenario. The models look at historical performance of the asset classes and project how they will do in each situation and how they will perform against each other. These models are dynamic and will keep repeating this process, incorporating any new data and projecting well, often 20 years, into the future.

The other common element measured by these models is risk. Different investors have different risk tolerances. The models examine factors like leverage, primary versus derivative investments, particular market and sector exposure risks, liquidity of the portfolio, and credit exposure over the investment term to assess the particular risk factors in a portfolio. Again, these are dynamic calculations that measure the percentage risk, as well as performing stress tests based on various projection scenarios. They examine short and long term credit spreads against interest rate projections and the impact on cash flow to the portfolio. Investors will have to take in the data and make decisions based on their own needs and risk tolerance.

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