Objective-based investing: making your own luck

One topic investment managers tend to avoid discussing is the role of luck in investment outcomes. However, chance can often play an inordinately large part in successfully meeting current and future financial goals. Serendipity shouldn’t factor into your organisation’s success, right? Unfortunately, there are many ways misfortune can strike an investor, and they tend to be interrelated with the concept of sequencing risk – or the order in which “bad things” happen. In this sense, risk perhaps is best defined not by the volatility of returns but rather by the possibility that there may not be enough money available when needed.

Here are a few (hypothetical) worst nightmares:

• A Central Bank has a real (i.e. after inflation) income requirement but sees its real purchasing power diminished by a sudden period of hyperinflation.
• A new retiree incurs an investment loss early in retirement, which reduces his portfolio’s value both by negative market performance and withdrawals needed to fund living expenses.
• A defined benefit pension fund with significant near-term liabilities suffers a dramatic loss due to falling equity markets (similar to the Global Financial Crisis).
• A sovereign wealth fund may have large holdings in illiquid assets during a credit crunch but also may require cash to invest in a pre-planned project.
• A retiree makes conservative financial decisions but unfortunately runs out of money – ironically, living longer is often seen as a potential stumbling block in terms of long-term financial security (also known as longevity risk).

The problem with all these scenarios is not necessarily that a negative event occurred, but rather that the event happened at the wrong time given the investment risks being taken. Unfortunately, traditional ‘set-and-forget’ 60/40 asset allocation strategies that aim to “diversify away” such risks have proven insufficient at solving this problem.

Is there a better way?

Objective-based investing seeks to overcome these issues. We use SAA to determine a long term risk/return profile and asset allocation mix, but dynamically adjust this allocation to act on short to medium term opportunities and risks. In a perfect world, managing portfolios dynamically to just one simple objective would be enough. But in the real world, investors often have multiple objectives within particular risk constraints – with some being completely contradictory and at cross-purposes with one another! For example, an investor may have a five-year investment horizon with a 5% return objective, significant aversion to negative returns in a given year, and the desire to consistently outperform a particular market index. Some investors may not explicitly know their return requirements, risk tolerance, or even their time horizon, and it is critical for us as fund managers to effectively translate investor purpose into concrete financial terms.

To help solve the problem of multiple, competing objectives, we have developed a systematic and differentiated method to maximise our chances of success (or minimise the probability of failure). And despite many people’s worst fears, mathematics is essential in eloquently solving this problem. We analyse a number of return targets over several investment horizons, scoring each hypothetical asset mix with a weighted risk of not achieving the return target. The end result is an overall risk score that assesses potential failure of the portfolio to achieve multiple objectives. This score can be then be considered in a similar way to other risks we manage.

By improving traditional asset-allocation techniques (focusing on objectives, not set-and-forget), incorporating sophisticated risk and return enhancement (dynamically adjusting our asset allocation), and using a framework that makes it possible to achieve multiple objectives (within reason), we believe we can reduce the distribution of outcomes and minimise the role of luck in the success of our portfolios.