Using Bond and Equity Volatility Indices for Investment Allocation
By Anthony J. Bitalvo
Risks & Rewards, September 2025
The traditional “60/40” portfolio — 60% allocated to equities and 40% allocated to fixed income — has been a go-to strategy for decades for many investment managers.[1] However, recent market conditions have exposed some of its weaknesses, especially when both stocks and bonds sell off at the same time. Recent investing trends have demonstrated a significant shift in how retail investors manage their money. Over the past five years, an increasing number have started taking additional control of their finances, moving away from set-it-and-forget-it strategies and looking for tools to better navigate changing market environments. This raises the logical question as to whether there are better ways to adjust portfolio risk based on what differential market indicators are showing at different points in time.
This article explores whether two popular volatility indices — the VIX (for equities) and MOVE (for bonds) — show any meaningful relationship. And if they do, maybe that relationship indicates an opportunity for improved asset allocation decisions. This article can be viewed as a thought experiment on using these indices to dynamically adjust an allocation between the traditional 60/40 portfolio and a 100% equity approach.[2] The vision is that such an approach might be especially useful in retirement accounts and other long-term asset portfolios. Note that this analysis excludes the use of borrowing and short-selling strategies.
Description of “VIX” and “MOVE”
Before diving into portfolio ideas, it is important to understand what the VIX and MOVE indices actually represent — and why they matter in the context of risk management.
The VIX (CBOE Volatility Index), often called the “fear index,” measures the market’s expectation of 30-day volatility in the S&P 500, based on several option prices. It is calculated using a range of out-of-the-money call and put options, which reflect how much investors are willing to pay to protect against or profit from large market moves. When the value of VIX is high, it generally means that investors expect more turbulence in the stock market.
The MOVE Index (Merrill Option Volatility Estimate) is essentially the bond market’s version of the VIX.[3] It tracks the implied volatility of U.S. Treasury yields, derived from options on various bond maturities (usually 2-year, 5-year, 10-year, and 30-year Treasury futures). MOVE reflects how uncertain the market is about interest rates and the broader fixed income environment.
Even though these two indices operate in different markets — equities and bonds — they both
serve as real-time gauges of how investors are pricing in risk. And while they are often looked at
separately, they may have something meaningful to say when viewed together.
By looking at both stock and bond market volatility at the same time, a clearer picture of the overall market risk environment may emerge — one that could potentially be used to adjust portfolio allocations in a more dynamic way than simply sticking with a static mix like 60/40.[4]
Although the VIX and MOVE indices come from different markets, there have been notable
times when they have moved in sync, or when one appeared to lead the other. These episodes
tend to occur during times of broader systemic stress, when risk spills over from one market into the other.
Rationale for Using Both MOVE and VIX in Market Risk Assessment
The basis for using the MOVE index comes from the bond market’s history in pricing macroeconomic and systemic risk earlier and/or more accurately than the stock market.[5] This is because bond prices react directly to changes in interest rates, inflation expectations, and credit conditions — all of which are core drivers of financial stability. Institutional investors in fixed income tend to move early on shifts in risk perception, which is why bond volatility, measured by the MOVE Index, can sometimes spike before equity volatility,[6] measured by the VIX. While the stock market may be slower to reflect certain risks due to its focus on earnings and sentiment, the bond market frequently sends earlier warnings, making MOVE a valuable tool for forward-looking risk assessment.
One striking example occurred in early 2023, during the lead-up to the regional banking crisis.
Between Feb. 3 and March 3, the VIX posted a modest gain of just 0.87%,[7] suggesting
calm in equity markets. Meanwhile, the MOVE Index surged over 24% — a sign that bond
market participants were already bracing for trouble.[8] The MOVE Index began climbing days
before the VIX reacted.[9] Not long after, equity markets sold off sharply and the VIX spiked, but investors watching the MOVE Index received an early signal that something was wrong.
Another more recent case happened in April 2025, when the MOVE Index spiked to around 172 (it usually ranges from 80 to 125) amid margin calls and stress in the hedge fund basis trade space.[10] At first, equity markets did not respond. However, VIX caught up shortly thereafter, again reflecting the lag between stress showing up in bonds versus stocks.
These examples suggest that while the relationship between MOVE and VIX is not perfectly consistent, there are moments when MOVE acts as a leading indicator of broader market
volatility. When both indices rise together, it tends to signal a regime shift — from stable to turbulent — where traditional diversification approaches may begin to break down. For investors
looking to adjust risk exposures in advance, that’s a signal worth paying attention to.
Pros and Cons of the 60/40 Portfolio
For decades, the 60/40 portfolio has been a go-to strategy for many long-term investors. It offers a simple, passive balance between growth and stability, and historically, it has performed well. According to Vanguard, a global 60/40 portfolio delivered an average annual return of 6.9% over the past 10 years,[11] with longer-term annual returns typically ranging between 5.6% and 7.6%,[12] depending on the timeframe and geographical tilt. The strategy weathered major events like the 2008 financial crisis and the COVID crash, often rebounding strongly in the years that followed.
But recent performance has disappointed. In 2022, both stocks and bonds fell sharply, and the
classic 60/40 portfolio suffered a 17.5% loss — its worst calendar-year performance since
1937. This challenged the core diversification logic of the strategy. While the portfolio rebounded
with a 17.2% gain in 2023, there was damage to investor confidence in the risk management tenets of the strategy.[13]
Critics have recently argued that 60/40 has become too passive for today’s fast-changing
markets. Bond yields were near historic lows for much of the 2010s and early 2020s, leaving the
40% bond allocation with limited return potential and minimal defense when inflation or interest
rates spiked. In response, some investors have pushed toward 100% equity portfolios, especially for younger savers with a longer time horizon.[14]
But that introduces its own set of risks. While equities have higher return potential, they also
come with far more volatility. The average drop in the S&P 500 during major corrections can exceed 30%, and riding that out is not always practical, especially for investors in retirement who may not be able to afford such steep short-term losses.[15]
This creates both a need and an opportunity for a strategy that is more responsive than 60/40, but not as aggressive as 100% equities. The approach the remainder of this article explores proposes the use of real-time volatility indicators, like the VIX and MOVE indices, to adjust portfolio risk dynamically. This is not a recommendation to abandon traditional strategies, but rather an encouragement to explore whether changes in volatility indicators can offer a smarter way to adapt to the market environment.
Model Development and Back-testing Results
The model described below operates starting with a 60/40 portfolio split and then decides on how the split will be changed based on the historical relationship between the MOVE and VIX indices and their current relative levels. The approach involves the following five steps.
Step 1) Time series for both the MOVE and VIX indices are used to derive average monthly levels for each. The ratio of MOVE to VIX is calculated, and an average historical ratio is derived.
Step 2) The historical MOVE data for each month is used to find the percentage change
between that month and the historical average of the index.
Step 3) For each month, this percentage difference (i.e., between the MOVE value for that month and the historical average) is added to the corresponding VIX level for that month. This results in a VIX value adjusted to capture how the bond market is pricing risk.
Step 4) Convert the adjusted VIX value into a percentage by dividing it by 100. Then, divide the equity risk premium (ERP) by this percentage. Note this is not a Sharpe ratio calculation or a step in a Markowitz-style optimization, but rather a rule-based adjustment where higher perceived volatility leads to lower equity allocation. In this model, the ERP is set to 5.5%, based on forward-looking research by Aswath Damodaran of NYU Stern (2013–2023).[16]
This step translates perceived market volatility into an equity allocation signal. When the adjusted VIX is low, indicating lower expected market risk, the resulting ratio is higher, supporting a greater equity allocation. When the adjusted VIX is high, the ratio drops, and the model reduces equity exposure accordingly. Conceptually, this mirrors how investors demand more expected return to justify taking on more perceived risk. The resulting ratio is scaled in the next step to reflect a volatility-adjusted weighting of equities in the portfolio.
Step 5) This ratio is then divided by the historical average ratio of the MOVE to VIX indices calculated in step 1 and then multiplied by 60 (representing the percentage equity allocation under normal market conditions). This final number is capped at 100 and floored at 0 and represents the percentage of the portfolio allocated to equities for that month, with the remaining percentage allocated to bonds.
Note that this article uses the 60/40 benchmark for the back test, but based on age and risk tolerance, this can be adjusted to 80/20, 70/30, 50/50, and so on; each of these will have slightly different outcomes.
When backtesting this model using this approach and assumptions, the total return between January 2014 and February 2025 was 323.93% for a 14.03% compound annual growth rate (CAGR) with only two down years: 2022 with a -15.34% return and 2018 with a -2.19% return.
This is compared to investing 100% in the S&P 500, which for the same time period returned roughly 237%[17] for an 11.5% CAGR with 2015 producing a 1% return, 2018 with a -5.41% return, and 2022 with a -18.97% return.[18]
These were substantial differences in performance over the period back-tested. It is
important to note the greater upside achieved with less downside volatility. This indicates that such an approach may be worth exploring further.
Implementation Challenges
While the back-tested version of this portfolio shows promising results, it relies on monthly average volatility levels, which are inherently backward-looking. In other words, the data already has realized market stress baked in by the time it is used for allocation decisions. The real value, which may be challenging to unlock, lies in developing a forward-looking indicator that can help adjust the portfolio before the volatility fully materializes.
While the current model adds the percentage deviation of MOVE from its historical average to VIX to reflect bond market stress, one potential limitation is the risk of double-counting, especially in environments where both VIX and MOVE are already elevated. In such cases, adding the MOVE deviation to VIX may exaggerate perceived risk, since both indices could be reflecting the same systemic concern.
A refinement worth exploring is to treat VIX and MOVE as independent measures of market risk, each compared to its own historical average. For example, a volatility ratio could be constructed as follows: Risk Ratio = (VIX / VIXavg) / (MOVE / MOVEavg)
This ratio compares equity risk to bond risk on a standardized basis. If the ratio is above 1, equity risk is disproportionately high, suggesting a need to reduce equity exposure. If it is below 1, bond market stress may justify reducing equities as well. When the ratio is close to 1, a baseline allocation (e.g., 60/40) is indicated.
Several potential approaches may be workable. One idea is to use a shorter-term moving average, such as a 15- or 30-day window, to better capture recent shifts in volatility momentum rather than a long-term average.
Another approach involves applying a momentum signal, where changes in the trajectory of the MOVE or VIX indices act as early warning signs. Alternatively, a threshold-based trigger could be tested; for example, reallocating the portfolio if the MOVE Index rises a certain percentage above its historical mean or moving average.
It should be noted that such an approach could require multiple reallocations per year, and therefore, transaction costs and taxable events will need to be considered in the analysis. Restricting its application to a tax-advantaged account like a Roth or traditional IRA partially helps in this regard.
Concluding Thoughts
At its core, this article is a thought experiment rather than a completed investment framework. It explores an under-discussed relationship between two major volatility indices and suggests ways that relationship could inform real-world asset allocation — particularly in longer-term portfolios like IRAs. The MOVE Index, while often ignored by retail investors, may hold early clues about market stress that the VIX does not fully reflect until later.
This analysis began with a simple question: Can the relationship between VIX and MOVE be used to build a more responsive portfolio strategy? Along the way, it evolved into something broader
— a reflection on how investors might rethink risk, especially in a world where traditional
diversification does not always hold up. While the model outlined here is far from perfect and
lacks the predictive power needed for active trading, it points to a potential middle ground between
the passivity of the 60/40 portfolio and the volatility of 100% equities.
Several concepts and initial observations have been presented. The intention is that this work
serve as a foundation for other researchers and professionals to expand upon, refine,
and develop into a more robust, forward-looking framework. The perfect asset allocation strategy may remain elusive, but exploring the possibilities of incorporating economically meaningful risk signals into portfolio decisions offers a significant opportunity for more efficient wealth management.
Acknowledgments
Special thanks to Professor Robert Goldberg of Adelphi University, whose guidance, support, and thoughtful questions were instrumental in developing the foundation of this project. Much of the initial model was built during my time working under his tutelage. His willingness to dive deep into the data, challenge assumptions, and point me in the right direction made this exploration possible.
This article is provided for informational and educational purposes only. Neither the Society of Actuaries nor the respective authors’ employers make any endorsement, representation or guarantee with regard to any content, and disclaim any liability in connection with the use or misuse of any information provided herein. This article should not be construed as professional or financial advice. Statements of fact and opinions expressed herein are those of the individual authors and are not necessarily those of the Society of Actuaries or the respective authors’ employers.
Anthony John Bitalvo is a graduate student currently pursuing a Master of Science degree in Enterprise Risk Management from Columbia University in New York City. He can be reached at ajb2369@columbia.edu or on www.linkedin.com/in/anthonyjbitalvo
Endnotes
[1] Vanguard. The Global 60/40 Portfolio: Steady as It Goes. Vanguard, 2022. https://institutional.vanguard.com/insights-and-research/perspective/the-global-60-40-portfolio-steady-as-it-goes.html.
[2] Vanguard. The Global 60/40 Portfolio: Steady as It Goes. Vanguard, 2022. https://institutional.vanguard.com/insights-and-research/perspective/the-global-60-40-portfolio-steady-as-it-goes.html.
[3] Schwab. “What’s the MOVE Index and Why It Might Matter?” Schwab Brokerage, 2019. https://www.schwab.com/learn/story/whats-move-index-and-why-it-might-matter.
[4] Nga Pham et al. The Performance of the 60/40 Portfolio: A Historical Perspective. Capital Markets, 2025.
[5] Schwab. “What’s the MOVE Index and Why It Might Matter?” Schwab Brokerage, 2019. https://www.schwab.com/learn/story/whats-move-index-and-why-it-might-matter
[6] Schwab. “What’s the MOVE Index and Why It Might Matter?” Schwab Brokerage, 2019. https://www.schwab.com/learn/story/whats-move-index-and-why-it-might-matter
[7] “Investing.com - Stock Market Quotes & Financial News.” Investing.com, 2025. https://www.investing.com/.
[8] Schwab. “What’s the MOVE Index and Why It Might Matter?” Schwab Brokerage, 2019. https://www.schwab.com/learn/story/whats-move-index-and-why-it-might-matter.
[9] Schwab. “What’s the MOVE Index and Why It Might Matter?” Schwab Brokerage, 2019. https://www.schwab.com/learn/story/whats-move-index-and-why-it-might-matter.
[10] Joy Wiltermuth. “Why Bond-Market Tumult Likely Peaked Wednesday Morning — before Trump’s Tariff Flip-Flop.” MarketWatch, April 9, 2025. https://www.marketwatch.com/story/why-bond-market-tumult-likely-peaked-this-morning-before-trumps-tariff-pause-f93b958d.
[11] Vanguard. The Global 60/40 Portfolio: Steady as It Goes. Vanguard, 2022. https://institutional.vanguard.com/insights-and-research/perspective/the-global-60-40-portfolio-steady-as-it-goes.html.
[12] Vanguard. The Global 60/40 Portfolio: Steady as It Goes. Vanguard, 2022. https://institutional.vanguard.com/insights-and-research/perspective/the-global-60-40-portfolio-steady-as-it-goes.html.
[13] Morgan Stanley. Return of the 60/40. 2025. https://www.morganstanley.com/im/publication/insights/articles/article_bigpicturereturnofthe6040_ltr.pdf
[14] Aizhan Anarkulova et al. “Beyond the Status Quo: A Critical Assessment of Lifecycle Investment Advice.” SSRN Electronic Journal, 2023. https://doi.org/10.2139/ssrn.4590406.
[15] Aizhan Anarkulova et al. “Beyond the Status Quo: A Critical Assessment of Lifecycle Investment Advice.” SSRN Electronic Journal, 2023. https://doi.org/10.2139/ssrn.4590406.
[16] Aswath Damodaran. Damodaran Online. Stern School of Business, New York University. https://pages.stern.nyu.edu/~adamodar.
[17] Schwab. “What’s the MOVE Index and Why It Might Matter?” Schwab Brokerage, 2019. https://www.schwab.com/learn/story/whats-move-index-and-why-it-might-matter
[18] “Investing.com - Stock Market Quotes & Financial News.” Investing.com, 2025. https://www.investing.com/.