Introduction to Portfolio Risk Management

From both a mathematical and emotional perspective, large losses have a much larger impact than large gains on the probability that you will achieve your long term investing goals. Consider a portfolio with a value of 100 that in Year 1 experiences a 25% loss in value. To return to a value of 100, in Year 2 it must earn a 33% return.

To make this painfully practical, consider this example:
If our equally weighted model portfolio had avoided the 2008 market downturn (say, by heeding the warning we published in May 2007), the ending value in 2017 (after 15 years) of an original investment of 100 would have been 454 instead of 322 — a 41% difference. As we have emphasize ad infinitum since we began publishing in 1997, when it comes to achieving long-term investing goals avoiding large drawdowns is critical.

We believe that an effective risk management plan has three key elements.

The first is a portfolio that is well-diversified across broadly defined asset classes, in order to maximize the probability of achieving an investor's long-term real rate of return target within acceptable shortfall and other constraints.

As we have seen, constructing such a portfolio can entail the use of advanced asset allocation methodologies, as well as techniques to limit the impact of parameter estimation errors (i.e., the values assigned to expected asset class returns, risks, and correlations or other measures of their interrelationships).

An alternative and much simpler approach is to equally allocate one's portfolio to a mix of passively managed index products that cover a wide range of broadly defined asset classes.

The second element of an effective downside risk management plan is an automatic rebalancing strategy that keeps actual portfolio weights close to their long-term targets.

Our preferred approach is to undertake rebalancing (which incurs transaction costs) only when one or more asset classes has exceeded or fallen below its target weight by more than a trigger percentage (e.g., an actual weight of 5% or 15%, versus a target weight of 10%). For the asset classes most above and below their respective target weights, we also employ an adjustment factor (typically 2.5%), to rebalance to either slightly below (for the most overweight asset class) or slightly above (for the most underweight asset class) their respective target weights. Assuming mean reversion in returns over time, this can add a small amount to a portfolio's long-term compounded real rate of return.

While diversification and systematic rebalancing are necessary elements of an effective downside risk management plan, they are not by themselves sufficient.

We therefore use a third risk management approach, which we call "episodic rebalancing." This is driven by our global macro forecasts and asset class valuation analyses, and is based on our assumption that financial markets are a complex adaptive system, in which equilibrium is the exception rather than the rule, and therefore substantial asset class over and undervaluations can and do occur.

We further believe that overvaluation are easier to identify than the undervaluations, because in the case of the former there is a wealth of historical valuation data that can be used (undervaluation involves much more uncertainty).

We continually assess current and expected asset class valuations based on fundamental factors, the degree of alignment in investor narratives and behavior, and, at a longer time horizon, the potential uncertainty and valuation impacts of the complex interactions between technological, economic, environmental, military, social, demographic, and political trends and uncertainties.

When these multiple perspectives indicate substantial asset class overvaluation and/or a very elevated level of systemic risk (as they did in
March 2000 and May 2007), we recommend the use of risk management techniques that ogo beyond diversification and rebalancing, and include moving into to short term government securities (i.e., cash), gold and other defensive positions, and/or the purchase of put options and other derivatives.

This naturally raises the question of how, having moved out of one or more asset classes, an investor should decide when to reverse this action. The extent of this challenge crucially depends on the standard an investor uses to measure his or her performance. If it is an external benchmark, then the investor must worry not only about moving out of an asset class too soon, but also about getting back in too late, lest he or she underperform. In contrast, an investor who seeks only to earn the long-term return needed to achieve his or her goals faces an easier decision.

When an asset class is substantially overvalued, it is far more important to avoid a large loss than to hold out for another month of gains. And when if this asset class declines in price to a level below its reasonable value (i.e., if the price correction overshoots), an investor focused on achieving long term goals has flexibility in deciding when to reinvest, since from this low base the expected asset class returns will be higher than those assumed in the portfolio analysis that set the long-term asset class weight. Compared to an investor worried about underperforming an external benchmark, our long-term target return focused investor will therefore be less likely to reinvest too early.

In sum, effective portfolio risk management is critical to achieving an investor or fund's long-term real return objective, and the financial goals (not to mention hopes and dreams) that depend on it.

Now let’s move on to the implementation of your asset allocation strategy, and the not-always-obvious distinctions between active and passive investing.

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