For an overview of the Probability Range and enabling Advanced Risk Modeling, see Calculating the Probability Range.
In This Article
Advanced Risk Modeling (ARM) calculates the six-month range based on historical data in conjunction with capital market assumptions. Each security is filtered into one of four return modes and modeled accordingly.
Advanced Return Mode CategoriesImportant: Advanced Return Mode categories are only available when ARM is enabled.
Riskalyze filters each investment into one of four return mode categories (Beta-weighted, Tactical, Interest Rate Sensitive or Average Return). Advisors are empowered and encouraged to toggle between the various return modes or select the return mode that is believed to most precisely incorporate the investment’s underlying strategy. To do this, the advisor simply needs to click on the investment to view the dropdown. Inside this drop down the advisor can select which return mode to use, and hit save.
Regardless of the Return Mode, we use actual volatility and correlation data from Jan 1, 2008, to present. If an investment has less history than that, we use extrapolation methodology.
Beta-weighted investments are identified by our methodology as being traditional or passive in nature. Individual stock, equity-focused ETFs, mutual funds, and annuity sub-accounts are often included under this label.
With the Beta-weighted return mode, we use beta to normalize returns to the S&P, which allows advisors a mechanism for incorporating their beliefs, biases or stress tests on standard investments via updating the market assumptions. Advisors simply input the direction (+/-) and magnitude of changes to the 6 month Standard and Poor's assumption and our technology models the portfolio accordingly with the help of in-house computed beta statistics.
➡️ Interest Rate Sensitive
For interest-rate sensitive investments, we use correlation to the 10 Year US Treasury rate to model bonds and other interest rate-dependent securities, and we use actual volatility and correlation data from Jan 1, 2008, to present. If an investment has less history than that, we limit the amount of anti-correlation the investment can provide to the overall portfolio, to err on the side of safety. Interest rate-sensitive investments (Bonds) are identified by our methodology as having a high correlation with changes to the 10 year US government bond yield. We use correlation to the 10 Year US Treasury yield to identify interest rate sensitive securities. This allows advisors a mechanism for incorporating their beliefs, biases or stress tests on interest-rate sensitive investments (typically bond ETFs/mutual funds) via updating the market assumptions. Advisors simply input the direction (+/-) and magnitude of changes to the 10 year US Gov bond yield and our technology models the portfolio accordingly. Our methodology will not apply interest rate market assumptions (stress tests) indiscriminately to all 'bond' investments; only those that have a history of being highly correlated to the 10 year US Gov bond yield. For example, some tactical, foreign, floating rate, etc. bonds will not be arbitrarily tied to interest rate assumptions.
For tactical investments, we use upside downside capture ratios, volatility and correlation data from Jan 1, 2008, to present. The upside-downside capture ratio calculations are examined over four distinct market environments. Our analysis confirms that calculating capture ratios over short frequencies (think daily, weekly or monthly data points) is not as robust as calculating capture ratios throughout or during various market trends. Calculating capture ratios through different market trends is objective and gives tactical managers multiple opportunities to have their strategies prove themselves. So, instead of having one upside downside capture ratio based on Jan 1, 2008 - present capture statistics, our methodology takes into account the upside-downside capture ratios over 4 different market periods.
The upside and downside capture ratios for tactical investments are calculated from actual trading history from the following market environments:
- January 2008 through February 2009 (Bear Market)
- March 2009 through April 2011 (Bull Market)
- May 2011 through September 2011 (Bear Market)
- October 2011 through present (Bull Market)
For newer tactical strategies the capture ratio will be affected to the extent that a tactical strategy did not participate in any of the four market environments. For example, a strategy with a 2012 start date will not include data that allows for downside capture calculations since the strategy has yet to experience a bear market environment, thus downside capture will be correlated to upside capture until which time as the strategy navigates a bear market.
Read more about Riskalyze's Tactical Methodology.
➡️ Average Return
Average Return examines the returns since June 2004 (or since inception for younger securities) for their average annual return performance. For an in-depth look at Average Returns, see our Knowledge Base article.
This calculation methodology is based on a return scenario for the S&P 500 and the direction/change in the 10 Year Treasury Rate over the next 6 months. As we do not want to predict what the return scenario will look like in the near term, the default scenario is called "Long-Term Consensus." That scenario is designed for advisors who want to use the bedrock assumption of financial advice — that the long-term of the future will be something like the long-term of the past.
The Long-Term Consensus for the S&P 500 is +7.64% annually (including dividends), so we normalize it to 6 months by calculating a reverse compound. We believe that there is no long-term consensus on the direction or magnitude of change on the 10 Year Treasury yield, so our default is set to "flat." Our default market assumption uses a 6-month return for the Standard and Poor's 500 of 3.75% and a "flat" interest rate environment.
You can easily choose from another preset scenario, or enter your own S&P 500 and 10 Year Treasury Rate scenario, to recalculate the risk in the portfolio using the Market Assumptions menu. (available only when ARM is toggled on. See image below)
Pro Tip: Many advisors will use market assumptions to stress test their portfolios. To find out more about stress testing portfolios with market assumptions, Click Here.
We are often asked, "Why did you choose Jan 1, 2008, to Present for volatility and correlation data?"
We chose that timeframe for three reasons:
- Most of the funds popular with advisors have that much data, and many don’t have more than that;
- It’s a very diverse timeframe with good, bad and ugly market environments (2008 market crash, 2011 sideways market, and 2012-13 bull markets);
- Our backtesting and real-world testing have proven to us that weighting recent volatility and correlation data is more robust than the alternatives.
Interestingly, these market assumptions even managed to nail one important individual stock. We think nailing an individual stock should be rare in any market assumptions, but if you built a 100% AAPL portfolio in August 2012, the Six Month Probability Range would have been –37% to +51%. Moreover, as we all know, AAPL dropped 36% over the following six months.
No market assumptions or portfolio analytics can quantify 100% of the risk. But we’re confident that our Six Month Value at Risk can empower you to quantify 95% of the risk probabilities — and that’s a powerful way to build confidence and deliver on expectations for your clients.