Visualize risk driver#
Visualize risk code#

In the example above, International SOS took this simple concept and applied it to their interactive map of travel risk. It is generally accepted that red is bad/stop and green is good/go.Įxample: International SOS – Interactive Travel Risk Map This is so widely known you shouldn’t even need a key or legend. The most widely-recognized way would be using a traffic light system. To communicate your analysis, visualization is vital and very easy to implement. What is the level of impact should it occur?īased on those two answers, you should be able to rank each risk.

When judging the priority of a potential risk, you should consider two questions: Prioritizing them will give your ERM a focus, meaning risks can be mitigated quicker through more informed decision making. This is where the visualization of risk prevention data is key. While senior management may understand the importance of Enterprise Risk Management (ERM), companies struggle communicating its value to stakeholders, often resulting in poor or uninformed decisions. I don’t believe it’s core to the point of the piece.Modern businesses must navigate through a vast range of risks, whether it’s the IT department avoiding hacks or the financial department minimizing the threat of recession.

Visualize risk code#

If you want to include mean reversion, volatility clustering etc, feel free to modify the code (written in R) and use whatever data-generating-process you want. I used very simple, straightforward assumptions about the risk and return here. This is why time horizon is such an important part of determining the right risk level for an investor. In the long term, the average matters more. In the short term, the variance in outcomes dominates the chance you’ll lose money. It’s only when we invest over longer periods of time that we begin to see higher risk investments dominate lower ones. This is the closest I could get to Andy’s original graph - it took time. But the median and good outcomes are substantially higher. However, the bad outcomes in the high-stock portfolio (the lowest red dot) is only slightly worse than in the low-stock portfolio. You can see that the 20% stock portfolio doesn’t have a huge range of outcomes, but the 80% stock portfolio does. The graph below shows the cumulative return distributions for 20%, 50% and 80% stock portfolios over a 7 year investment horizon. Note how initially the bad outcomes involve losses, but over time even the worse cases gets better? Sometimes even positive? The dots on each graph correspond to the 20th, 50th, and 80ths percentile outcomes in each case. As we invest for longer and longer, the mass of probability smears upwards: our upside odds improve. Let’s start with a 50% risky asset portfolio, and look at the cumulative return distribution at each year from 1 to 10.

What if we take those same portfolios, and invested for longer periods of time? these are expected returns over just a one year horizon.

Visualize risk driver#

In the short-term, the dominant driver of loss size is the variance of the portfolio. Notice how they all seem like they’re at about roughly the same place, compared to the difference in ranges? This shows the much greater potential for downside in higher risk portfolios. The dot represents the average expected return. In this case, expected risk and return over a one year investment horizon. The graph below is a realistic version of the graph. If you want to modify this code, you can fork it here yourself. When we say 100% risk, that’s the 100% risky asset. The risk asset has a mean annual return of 6% and volatility of 17%. Well done.īut… it was still misleading! Notice how it still looks like the highest risk portfolio was best: the potential downside of each portfolio is pretty much the same, but the high risk portfolio has substantially more upside? That’s not an accurate portrayal of risk and return 1.Īll the graphs below were created by creating different risk level portfolios by blending a risk (and return) free asset with a risky, higher returning one. To communicate the risk visually, he included probability distribution of potential outcomes vertically, which is a very nice touch. Investors do often have the perception that the highest return portfolio is best, ignoring the risk. Andy Rachleff’s post on how the standard efficient frontier graph often misleads investors resonated with me. So I’m in favor of anything that gives investors a better intuition of what risk really is. Risk involves communicating not just that many outcomes are possible, but how likely they are. About Blog Research Talks Contact Visualizing risk, return, and timeīut risk… risk is more difficult.