A good risk measure should be meaningful to investors. We believe it should be:
- Focused on outcomes – in other words, the destination, not the journey
Historical volatility may be ubiquitous in the investments industry, but it’s hardly relevant to most people.
Worse, short-term volatility is unstable, so that the same portfolio often ends up with a different risk rating over time, sometimes within months!
We, therefore, define investment risk as the standard deviation of projected long-term returns. By “long-term” we mean 10 years, and we present the figure annualised.
Our definition of investment risk is based on projected returns. This means we need to have some method of projecting future outcomes for a given portfolio. We do this using a model that projects returns for several key asset classes.
Our simulation engine doesn’t make assumptions about the shape of every asset class’s distribution, nor their correlations with other assets. These kinds of assumptions are often wrong or too simplistic.
Instead, we remix historical index returns themselves. Each simulation is generated by picking random months from history, one after another. We can append the returns for each asset class in each month as we go along, building up a path.
This captures a lot of the desired behaviour, but not all. To capture phenomena like momentum and mean-reversion, we apply a given chance of using the very next month in sequence.
In this way, we preserve the unique characteristics of each asset class. The simulated projections are consistent with observed history, but not the same.
As a result, our simulations preserve the possibility of real-world extreme events, such as the Financial Crisis of 2008, but crucially don’t assume that the future will be a copy and paste of the past.
Each return path is ten years long, to make them relevant to long-term investors. And we simulate tens of thousands of paths, to ensure stability.