When the market was making new highs week after week in 2023 and 2024, robo-advisors looked brilliant. Low fees? Check. Automatic rebalancing? Check. Tax-loss harvesting? Check. Set it and forget it? Check, check, and check.

But then reality hits. The market drops 10%, then 15%, then crosses the dreaded 20% threshold into official bear market territory. Suddenly, those automated portfolios don't look quite so smart. Your account balance is bleeding red, your robo-advisor isn't calling you with reassurance (because it's a robot), and you're left wondering: do these algorithms actually work when it matters most?

It's a question that financial advisors have been asking since robo-advisors first emerged: "Sure, they work great in a bull market when everything goes up. But wait until we get a real bear market. Then we'll see who's still standing."

Well, we've now had multiple opportunities to find out. The 2018 correction, the 2020 COVID crash, and the 2022 bear market all provided real-world stress tests. The results might surprise you—though probably not in the way you'd expect.

The Uncomfortable Truth About Bear Market Performance

Let's start with the data that makes robo-advisor critics nod knowingly. During the first quarter of 2020, when markets crashed due to COVID-19, Backend Benchmarking collected performance data across 60 automated portfolios. The verdict? The average robo-advisor lagged a simple 60/40 allocation by about 80 basis points—and that's before accounting for fees.

High-profile platforms from Morgan Stanley, Schwab, and Wells Fargo did even worse, underperforming the market by 2-4% during the downturn. For investors who paid fees specifically for "smart diversification" and "active rebalancing," watching their robo portfolios underperform a basic index during the worst crash in decades felt like a betrayal.

The 2022 bear market told a similar story. According to Parameter Insights, U.S. digital advisor usage dropped from 27.7% in 2021 to 20.9% in 2022—a decline of nearly 25%. High-net-worth investors exited at the highest rates, with those holding $500,000 or more dropping from 38.3% usage to just 14.5%. The message was clear: when markets got rough, investors wanted human advice, not algorithms.

So case closed, right? Robo-advisors fail when it matters most?

Not quite.

The Data That Doesn't Make Headlines

While robo-advisors were taking a beating in the financial press, something interesting was happening in the academic research. A comprehensive study published in the journal Production and Operations Management examined actual investor behavior during the COVID crash—and the findings completely contradict the conventional wisdom.

Researchers obtained daily portfolio and transaction data from investors on an online platform, comparing those who used the robo-advisor system against those who managed their own investments. The methodology was rigorous: they matched robo users with self-directed investors who had similar demographics, risk preferences, and portfolio characteristics before the crash. Then they watched what happened when the market imploded.

The results? Robo-advisor users "experienced significantly fewer losses during the market downturn," with the performance advantage coming specifically from the robo-managed assets. The difference wasn't marginal—according to research from the University of Minnesota, robo-advisor users had a 12.67% performance advantage compared to matched human investors during the COVID crash.

Wait, what? How can robo-advisors both underperform benchmarks and outperform human investors during the same crash?

The answer reveals something crucial about what "working" actually means in a bear market.

The Real Battle: Algorithms vs. Human Psychology, Not Algorithms vs. Benchmarks

Here's what the academic research revealed about why robo users performed better: it wasn't because the algorithms were brilliant at timing the market. It's because they prevented investors from doing something catastrophically stupid.

According to the study, "the RA system adjusted its portfolios to hold less risky funds, whereas human investors stayed with their status quo and did not reduce the risk of their portfolios." In other words, the robo systematically de-risked during the crash, while human investors froze like deer in headlights.

Even more telling: "the benefits of disciplined trading mainly manifest during crises." During normal markets, robo users had similar returns to self-directed investors. The advantage only appeared when fear took over and human psychology broke down.

Kenneth Schapiro, CEO of Backend Benchmarking, summarized it perfectly in an interview quoted in the research: "the robos are probably a little more disciplined than individuals."

This discipline advantage isn't theoretical. When markets crashed in March 2020, self-directed investors did what humans always do in crashes: they either panic-sold at the bottom or froze and failed to rebalance. Meanwhile, robo-advisors rebalanced systematically, selling bonds to buy stocks as equities declined, maintaining target allocations regardless of how terrifying the headlines became.

For many investors, watching their robo-advisor buy more stocks while CNBC showed footage of empty city streets and overflowing hospitals felt wrong. It felt reckless. It felt like the algorithm didn't understand what was happening.

But six months later, when markets had recovered and those disciplined rebalancing trades looked prescient instead of reckless, those same investors were glad they didn't have a panic button.

The "Will They Hold?" Question

The most persistent concern about robo-advisors in bear markets isn't about algorithm performance. It's about client behavior. As Craig Birk, CIO of Personal Capital, put it: "We do worry that without access to an advisor, robo clients will have emotional reactions to a bear market or succumb to pressure to adjust to what they believe will best retain assets."

The fear was that when portfolios dropped 30-40%, investors would log into their robo accounts and frantically click buttons to move everything to cash. Without a human advisor to talk them off the ledge, they'd make the classic mistake of selling low and missing the recovery.

This was existential for robo-advisors. If clients fled during downturns, the business model would collapse. As one analyst put it, "My opinion? Robos will not survive a bear market."

So what actually happened?

The evidence suggests robo-advisors passed this critical test better than expected. Betterment and Wealthfront both reported continued growth in customer accounts and net deposits even during the volatile periods. January and March 2016, following the late-2015 market turbulence, were Betterment's best months for customer growth and net deposits.

During the COVID crash, Wealthfront reported three times as many new clients in January 2016 compared to the previous year, and saw fewer changes in risk scores, meaning clients weren't panic-adjusting their portfolios to become more conservative.

How did robo-advisors pull this off without human advisors? Through what one robo executive called "leveraging technology with behavioral psychology."

The Behavioral Playbook: How Robos Keep Clients Calm

Robo-advisors developed sophisticated systems to address behavioral risk during market stress. The strategies aren't subtle—they're built directly into the user experience.

Proactive Communication. When markets drop, robo platforms automatically send emails explaining what's happening and why it doesn't matter for long-term goals. As one Wealthsimple executive described, these messages typically contain "an explanation of what's causing the market to go down and why it doesn't matter."

Targeted Interventions. Platforms track user behavior to identify nervous investors. Those who log in frequently during downturns, who have experienced larger losses, or who have recently started investing receive additional outreach. The goal is to intercept panic before it becomes action.

Friction by Design. Unlike brokerage accounts where you can sell everything in two clicks, robo-advisors often build in just enough friction to make impulsive decisions harder. Want to change your risk score? First, let's show you the good and bad reasons for doing so. Want to withdraw everything? Here's your tax impact preview showing exactly what that will cost you.

Login Monitoring. Robo-advisors track client logins and trigger interventions based on behavior patterns. If someone who normally checks their account monthly suddenly logs in daily during a correction, that flags them for additional support. Popup messages appear tailored to their situation, and some platforms route these users to human advisors if available.

As Betterment's director of behavioral finance explained, "We've used each of these downturns to learn what works." They tested proactive outreach—it didn't work. They tested monitoring logins—that was more effective. Each bear market became a learning opportunity to refine the behavioral playbook.

Interestingly, Wealthfront's executive noted that "some people, when markets are choppy, actually check their account less often, not more. It's the ostrich syndrome." This matters because paying too much attention to your portfolio during volatility correlates with worse decisions. As he put it, "The benefit of an automated service is that we have an increasing number of young people who have decided not to focus their time on their portfolio."

The 2022 Reality Check

But the 2022 bear market—the first real, extended bear market for most modern robo-advisors—revealed the limits of these behavioral interventions.

This wasn't a V-shaped crash and recovery like COVID. It was a grinding, months-long decline that saw both stocks AND bonds fall simultaneously, breaking the traditional diversification playbook. The Fed was raising rates aggressively, inflation was persistent, and there was no clear catalyst for recovery on the horizon.

Under these conditions, many investors—especially affluent ones who knew they had options—decided automated portfolios weren't enough. They wanted someone to explain what was happening, to adjust their strategy, to at least create the illusion that human intelligence was responding to unprecedented conditions.

The mass exodus of high-net-worth investors revealed something important: robo-advisors can prevent panic selling during short, sharp crashes. But during prolonged uncertainty, many investors crave human reassurance that algorithms simply can't provide.

As Parameter Insights noted, "Many who thought they could do it themselves have been quickly disabused of this notion in the face of significant downturns and market volatility."

Where Traditional Robos Fall Short in Downturns

The 2022 experience exposed several specific limitations of traditional robo-advisors during bear markets:

Passive Portfolios in Active Risk Environments. According to a 2023 analysis by the Bank for International Settlements, "over 80% of robo-advised portfolios in the U.S. and Europe exhibited correlation coefficients above 0.9 during the 2022 market downturn, indicating minimal diversification benefit." When everything falls together, traditional diversification doesn't protect you.

Backward-Looking Algorithms. As one wealth management professional explained, "algorithms are ultimately backward looking and have very little ability to be predictive. An asset class that performed well last year may slump the following year." Mean-variance optimization works great until historical relationships break down.

No Tactical Flexibility. Traditional robo-advisors maintain strategic allocations regardless of market conditions. If you're allocated 70% stocks, you're staying 70% stocks whether the market is overvalued and euphoric or oversold and panicking. This rigidity feels appropriate in normal times but constraining when conditions shift dramatically.

Cash Drag During Recovery. Some robo-advisors, notably Schwab Intelligent Portfolios, hold significant cash allocations (6-30% of portfolios). While this provides a cushion during declines, it "will probably be a negative over longer periods" as it causes portfolios to lag during recoveries.

Generic Strategies for Unique Situations. Every bear market is different. The COVID crash was about pandemic uncertainty. The 2022 decline was about inflation and rates. Traditional robo-advisors apply the same rebalancing rules regardless of the specific nature of the downturn, missing opportunities for more nuanced responses.

The Next Generation: Adaptive Strategies for Bear Markets

This is where the robo-advisor market is evolving in ways that address these fundamental limitations. The distinction isn't between robo-advisors and human advisors—it's between static algorithms and adaptive systems.

According to research on Adaptive Investment Approach, "investors can constantly adjust their investments to reflect market conditions such as the volatility of investments, the return or the current condition of the market (Bull or Bear)." The key is using systematic rules that respond to regime changes rather than maintaining fixed allocations.

This approach, based on the Adaptive Market Hypothesis proposed by MIT Professor Andrew Lo, recognizes that "intelligent but fallible investors constantly adapt to changing market conditions" and that "macro factors and market sentiment" drive returns in ways traditional efficient market theory doesn't account for.

What does this look like in practice?

Regime-Aware Allocation. Rather than fixed percentages, portfolios that identify the current market regime—risk-seeking ("risk on") or risk-avoidance ("risk off")—and adjust accordingly. In bull markets, higher equity exposure. In bear markets, rotation toward defensive sectors, treasuries, or cash.

Volatility-Based Risk Management. Systems that monitor market volatility and "make calculated adjustments to a portfolio's allocation in an effort to reduce risk exposure" when volatility spikes. This isn't market timing—it's systematic risk management.

Momentum and Trend Following. Rather than buying and holding regardless of trends, strategies that rotate toward assets showing positive momentum and reduce exposure to assets in confirmed downtrends. Research shows momentum performs "fairly consistently across both up and down markets".

Defensive Sector Rotation. In bear markets, systematic rotation toward defensive sectors like consumer staples, utilities, and healthcare that tend to hold up better during downturns, rather than maintaining fixed sector exposures.

Surmount represents this new generation of programmable platforms that enable these adaptive approaches. Rather than forcing you into preset portfolios that rebalance mechanically, it lets you define rules-based strategies that respond to market conditions.

Want a portfolio that increases bond allocation when equity volatility exceeds specific thresholds? Build it. Want sector rotation that shifts toward defensive holdings when market internals deteriorate? Create it. Want strategies that move to cash or inverse positions during confirmed bear markets? Define those rules and automate the execution.

The difference is fundamental: traditional robo-advisors give you a thermostat that maintains a constant temperature. Programmable platforms give you a smart system where you define the logic for how to respond to changing conditions.

The Behavioral Edge Remains—With Better Strategies

Here's what the research and real-world evidence tells us about robo-advisors in bear markets:

The behavioral discipline advantage is real. Academic research confirms that robo-advisors prevent the panic selling and portfolio freezing that plague self-directed investors during crashes. This matters more than beating benchmarks by 50 basis points.

Traditional static portfolios have limits. Maintaining 70/30 allocations regardless of market regime means you're taking the full brunt of bear markets without tactical adjustments. For many investors, especially those with shorter time horizons or lower risk tolerance, this isn't optimal.

The future is adaptive, not passive. The robo-advisors that survive and thrive won't be those with the lowest fees or prettiest apps. They'll be the ones that combine behavioral discipline with strategic flexibility—preventing panic while enabling intelligent adaptation to changing conditions.

One size doesn't fit all bear markets. The COVID crash required staying the course and rebalancing. The 2022 bear market rewarded tactical defensive positioning. Future downturns will have their own characteristics. Having systematic rules that can respond appropriately matters more than rigid adherence to strategic allocations.

Think of it this way: the first generation of robo-advisors solved the problem of expensive, conflicted human advisors charging 1% to put you in actively managed mutual funds. They automated the basics—diversification, rebalancing, tax-loss harvesting—at a fraction of the cost.

But "working" in a bear market requires more than just maintaining your allocation while markets fall. It requires the discipline to avoid panic selling combined with the intelligence to adapt your strategy when market conditions fundamentally change.

So Do They Work? It Depends What You Mean By "Work"

If you're asking whether robo-advisors beat the market during bear markets: no, most don't. They're not designed to. They're designed to capture market returns at low cost while preventing you from self-destructing.

If you're asking whether robo-advisors keep you invested and help you avoid panic selling: yes, the evidence shows they do this better than self-directed investing.

If you're asking whether traditional preset-portfolio robo-advisors are optimal for navigating different types of bear markets: no, their inflexibility is a real limitation, especially during prolonged downturns or unprecedented market conditions.

If you're asking whether newer adaptive robo-advisor approaches can provide both behavioral discipline AND intelligent strategy adjustment: yes, this is where the technology is evolving.

A comprehensive review of robo-advisor research identifies performance as one of four key research streams, noting that "robo-advisors offer significant opportunities for financial companies with the potential to transform the wealth management industry"—but only if they continue evolving beyond simple passive rebalancing.

The verdict on robo-advisors in bear markets isn't that they failed. It's that the first generation proved the behavioral concept but revealed the need for more sophisticated strategies. As one portfolio manager at Wealthsimple explained, "We've set a different expectation than a lot of the industry does—outperforming the market is not part of our value proposition." The promise is diversification, transparency, low fees, and behavioral discipline.

For many investors, that's enough. If you're young with decades until retirement, if you're disciplined enough to ignore your portfolio during crashes, if you believe in passive indexing through all market conditions, traditional robo-advisors work fine in bear markets. They won't protect you from losses, but they'll prevent you from making them worse.

But if you want the behavioral benefits of automation combined with tactical flexibility to respond to different market environments—if you think bear market strategies should be different from bull market strategies—then the answer isn't abandoning robo-advisors. It's upgrading to platforms that let you program your own rules for how to navigate different conditions.

The question isn't whether robo-advisors work in bear markets. It's which type of robo-advisor you're using and whether it matches your actual needs when markets get ugly.

Because the next bear market is coming. It's not a matter of if, but when. And the platform you choose now will determine whether you navigate it with disciplined adaptation or rigid inflexibility.

About Surmount: Surmount goes beyond traditional robo-advisors by enabling programmable, rules-based investment strategies. With transparent pricing and integration with existing brokerage accounts, Surmount combines the behavioral discipline of automation with the tactical flexibility sophisticated investors need to navigate any market environment. Learn more about building adaptive strategies.

Disclosure: Surmount does not provide financial advice and does not issue recommendations or offers to buy or sell any security. Investments in securities are subject to risk. Past performance does not guarantee future results. Investors should consider all risk factors and consult with a financial advisor before investing.