Site icon Early Retirement Now

How to “Lie” with Personal Finance – Part 4: Risk Parity

earlyretirementnow.com

July 29, 2026 – I’ve written several posts in the “How to Lie with Personal Finance” series, all dealing with common misconceptions and, well, sometimes outright lies in the personal finance world: General Personal Finance Lies, Homeownership Lies, and Diversfiction Lies. Today I collected a set of lies for another interesting topic. Recently, I’ve heard and read a lot about an ostensibly innovative asset allocation strategy, Risk Parity, and its advantages, especially for retirees. Among some of the purported benefits are lower volatility, less stock market exposure, and higher sustainable withdrawal rates. The rationale for the superiority of this asset allocation is that it covers all the bases and hedges against different economic regimes, i.e., high growth vs. low growth and high inflation vs. low inflation. Some folks claim you can raise your safe withdrawal rate from 4% to 5% if you use Risk Parity in your retirement portfolio. So, why haven’t I proclaimed victory over Sequence of Return Risk yet? Mainly because there is a lot of hype, false advertising, and misunderstandings about Risk Parity. Here are several reasons to be skeptical…

1: Risk Parity is no Super-Secret Hedge Fund Weapon

As a former finance professional, I laughed out loud when I heard that Risk Parity is being sold as some super-secret weapon that only elite hedge fund tycoons like Bridgewater’s Ray Dalio figured out. At least that’s what Tony Robbins insinuates in his book “MONEY Master the Game: 7 Simple Steps to Financial Freedom.” If you don’t want to buy the book, here’s a short summary. Tony Robbins sells Risk Parity as having extracted the secret sauce from one of the famous hedge fund tycoons, and he’s now letting us in on this financial superweapon. That’s a bunch of hooey! Every finance student will learn about Risk Parity in Finance 101. It’s like someone asked the Ferrari chairman what the secret to building great cars is, and he responds, “A combustion engine and four wheels.” While Ferraris certainly have four wheels and a combustion engine (except for that ugly new electric Ferrari Luce that looks like a Volvo), the chairman didn’t really give away any proprietary information about their engines, transmissions, aerodynamics, design, etc. Only the most useless generic information that will certainly not give you a heads-up. Of course, Tony Robbins still runs with this and beats the drum (literally and figuratively) about Risk Parity.

In the FIRE/Personal Finance community, we got our friend Frank Vasquez, who touts Risk Parity as a brilliant and innovative way to think about diversification on his Risk Parity Podcast and on several guest appearances on other podcasts. He’s made that point on Bigger Pockets, Forget About Money, ChooseFI, Afford Anything, and likely more podcasts. But that’s all mostly bogus. Quite the opposite: naive Risk Parity relies solely on the variance-covariance matrix and will not cut it in the highly competitive field of asset management and high finance. Truly competent asset managers will consider risk and expected return estimates to trade off risk versus return; more on that below.

Most importantly, while Risk Parity may be one ingredient in Bridgewater’s hedge fund, you don’t grow your hedge fund empire to Bridgewater’s size with only Risk Parity principles. Hedge funds are all about alpha, not some static strategic asset allocation that anyone can replicate. You don’t need 1,300 employees (as of the most recent 2025 estimate, according to Wikipedia) to run something as trivial as Risk Parity, which any intelligent college student with basic Python or MATLAB skills can calculate on their home computer. Put differently, a Risk Parity strategy is only as good as the underlying returns. If you feed in a bunch of zero expected return streams into Risk Parity, you still have zero expected returns. Risk reduction is useless if the returns are not there. Of course, Bridgewater has all the know-how to squeeze additional alpha out of the financial market, whether through market timing, stock picking, sector rotation, etc., to add enough extra returns to Risk Parity to make it competitive. If you implement the “dumb” Risk Parity model floating around on the interwebs, you get subpar results.

Also, the timing is peculiar. Risk parity was all the rage twenty years ago in the mid-2000s because we were living in the “Goldilocks” economy where all major asset classes were doing well in the Post-Dot-Com-Crash era, and a Risk Parity portfolio garnered quite attractive returns. Then, the global financial crisis struck; equities took a nosedive, and the commodity bubble burst around the same time. In fact, the bellwether GSCI commodity index is still about 50% below its peak in nominal terms (and the GSG ETF more than that). Adjusted for inflation, the picture is even bleaker. Recently, the decade-long bond bull market came to an abrupt end with the inflation shock of 2022 and the swift Federal Reserve rate hikes. So, Risk Parity fell out of favor. A simple Stock/bond portfolio would have given you all the diversification you needed. I worked in institutional asset management until 2018, and Risk Parity was a non-entity at that time. But hey, this is the perfect time to drop a new old asset management catch phrase on the naive and gullible retail investor, after the smart money has long ago said goodbye. The Dunning-Kruger financial influencers are ready to spread this nonsense!

Side Note: What exactly is Risk Parity?

A standard exercise in basic finance and portfolio management is to calculate the risk contributions of different portions of a portfolio. It’s an easy application of elementary statistics and matrix algebra. The contribution has a pretty neat and intuitive interpretation, and we can derive it in two different ways: the absolute contribution to the portfolio variance and the marginal contribution to the portfolio risk, which both give you the same result. I put together a brief technical note in PDF format and posted it here.

Let’s go through a simple numerical example with just two asset classes, stocks and bonds. Assume stocks and bonds have annualized standard deviations of 16% and 6%, respectively, and a correlation of 0.10. If we plot the marginal risk contribution of equities as a function of the equity weight, we notice something peculiar. Of course, a 100% equity portfolio should have 100% risk coming from equities. But adding bonds, and even substantial percentages of bonds, to the portfolio hardly makes any dent in the equity contribution. The curve is almost flat between 60% and 100% equity weight. Even a 60/40 portfolio still has more than 90% of its risk coming from stocks. What’s going on here? This is an artifact of how we aggregate variances: even though equities have a standard deviation of “only” about 16/6=2.67 times the bond standard deviation, the equity variance is 7.1x the bond variance (=2.67 squared!), so equities will always dominate the risk attribution in a stock/bond portfolio, unless you vastly overweight bonds. Thus, in this example, you’d need to go down to roughly a 27% equities and 73% bond portfolio to equalize the risk contribution and achieve Risk Parity.

Equity risk attribution (y-axis) as a function of the equity weight (x-axis).

But alas, this chart above is really only a cheap party trick. It could be abused by charlatans to tell me that something needs to be done about the massive equity risk in my portfolio, when it really doesn’t. Rational and honest investors will instead look at the risk budgeting math the following way. In the chart below, let’s plot the actual portfolio risk (standard deviation) as a function of the equity weight and then also add the equity contribution (i.e., multiply the blue line by the percentage contribution in the previous chart). A 60/40 portfolio has only about 10% annualized risk, roughly 37% less than the 100% equity portfolio. So, diversification with 40% bonds lowered your risk by almost exactly that number. True, as a percentage of that reduced risk, equities still contribute 92% of the risk, but the risk is certainly much lower than before. Bonds helped with diversification much more than what a gullible retail investor would have deduced from the previous chart.

Absolute Risk (y-axis) as a function of the equity weight (x-axis).

The danger of Risk Parity is that you apply too much diversification, by moving out of high-return equities and into low-return bonds and commodities. Diversification then becomes Di-WORSE-fication. Also, leverage doesn’t help, more on that later in item #7!

For the record, though, I generally like the idea of hedging against different economic risks, but the performance in practice, for the average retail investor without the advanced toolkit of Ray Dalio’s hedge fund, is disappointing; more on that later.

Economic quadrants: asset classes that perform well in these environments.

2: Risk Parity is rife with “Hindsight Bias”

My fraud sensors go off whenever someone mentions a new portfolio allocation innovation. Then, I always ask myself, “Did you optimize this portfolio with knowledge unavailable at the beginning of the simulation period or with the benefit of hindsight?” That is certainly the case with some (or all?) of the various Risk Parity approaches floating around. The Hindsight Bias in Risk Parity portfolios is visible in at least two dimensions: 1) what asset classes to include, and 2) what weights we pick for those asset classes. Then I ask myself how this new strategy performed “out-of-sample,” i.e., did the outperformance continue when we exposed this new portfolio to subsequent return patterns? Most of the time, the results are disappointing.

For example, the All-Weather, aka All-Seasons, portfolio suffers from this hindsight bias. Tony Robbins unapologetically admits that the All-Weather strategy was optimized by examining the 1984 to 2013 time span and tailoring the returns to what worked best then. The Golden Butterfly portfolio has also existed since the early 2010s. It probably originated from the PortfolioCharts site, which uses data starting in 1970. The Golden Butterfly weights also seem to work well over the 1970s to early 2010s time span, but then sputter noticeably once people went from the benefit of hindsight to putting actual money at stake in a real portfolio.

But, alas, once people popularized those new portfolio weights, the returns didn’t look so great anymore when you go from the benefit of hindsight to putting actual money on the line. Let me demonstrate that with the All Weather portfolio: I’ll calculate the returns between 1984 and 2013, then compare how you’d have done since then (Dec 31, 2013 to June 30, 2026). Also, for completeness, I’ll throw in the return stats for pre-1984 and the entire horizon. And quite impressively, the All Weather portfolio blew everything else out of the water during 1984-2013. It had a Sharpe Ratio of 0.71 and close to 7% returns with only 8% volatility. That’s roughly the same return as the S&P fetched over the entire period, but with half the equity risk. I’m very impressed! But alas, since this amazing portfolio made the rounds on YahooFinance, the performance has been lackluster, significantly trailing the 75/25 and 60/40 portfolios since 2013. The average return was only 3.29% above inflation, and the Sharpe Ratio was very weak.

Asset class and portfolio returns during different time windows. All returns are real, i.e., CPI-adjusted. The All Weather portfolio was optimized to perform well in 1984-2013.

I find this recent All Weather performance quite astonishing because we did observe all of the economic regimes: high growth and low growth, i.e., one of the longest economic expansions on record up to the pandemic. Then a deep recession in 2020 and a slowdown in 2022. Likewise with inflation: We’ve had low and stable inflation and high inflation. Specifically, the two equity bear markets covered both bases, i.e., a demand shock with disinflation during the pandemic in 2020 and an inflation spike and rapid FOMC policy rate hike in 2022-2023. Even in this ideal testing ground for the Risk Parity approach, the venerable old 60/40 portfolio mopped the floor with the All-Weather portfolio. The 75/25 did even better. It’s peak-time hindsight bias: the overfitted portfolio that did so well with the benefit of hindsight sputters when you run it “out of sample.”

Also noteworthy: Over the entire 155-year time span from 1871 to 2026, the All Weather strategy is just mediocre, both in total returns (CPI+4.16%, almost a full two percentage points behind the 75/25) and in risk-adjusted returns: 0.29 Sharpe vs. 0.33 Sharpe for the 60/40 and 75/25 simple stock/bond portfolios. Also, All-Weather didn’t perform that well in the 1871-1983 era. How would an investor in 1984 have known that All-Weather would do so well over the subsequent 30 years? Without a time machine, nobody in the 1980s would have found this appealing.

3: Most Risk Parity strategies posted on the web aren’t really Risk Parity at all

The asset allocations that are often sold as Risk Parity aren’t Risk Parity in the mathematical sense at all. Risk Parity means the marginal contribution to the overall portfolio standard deviation is equal across all asset classes, as described in the section above. None of the allocations I’ve seen satisfy that criterion. For example, in the table below, I calculate the 120-month (4/2016-3/2026) risk attribution for several Risk Parity strategies. None of the purported RP strategies spread their risk equally across the asset classes. The All Weather portfolio comes close to 33% equity risk attribution, but bonds (57%) are well above the target, while commodities (7.4%) are below one third, no doubt a result of hindsight bias (see item 2 above) because riding the duration bet since the early 1980s was so much more lucrative than volatile commodities in the 1984-2013 window. Likewise, the Golden Butterfly and Golden Ratio portfolios have around two-thirds of their risk come from equities, but only around 16-19% from bonds, 11-17% from commodities, and -1% for the DBMF (trend-following) ETF. That’s not a typo; a risk contribution can indeed be negative.

Risk Attribution for different asset allocations. 120 months from 4/2016 to 3/2026.

Another giveaway that all these strategies are Risk Parity in name only is that their portfolio weights never seem to change. And I am not talking about occasionally replacing one ETF with another. The asset class weights should move substantially because the variance-covariance (VCV) matrix used to calculate those weights changes over time, both due to variances and covariances/correlations. For example, the chart below shows the risk parity portfolio weights calculated from a 120-month rolling VCV, using the three assets S&P 500, Long-Term Treasury Bonds, and Commodities (mimicked through SPY, TLT, GSG ETF returns and simulations before actual returns start). The weights are all over the place, unlike the completely static allocations recommended by risk parity fans. In fact, there is some financial research (Moreira, A. and Muir, T. (2017), Volatility-Managed Portfolios. The Journal of Finance, 72: 1611-1644. https://doi.org/10.1111/jofi.12513) that shows that dynamically shifting asset weights in response to volatility changes can generate more attractive return profiles. But that potential all goes out the window if you force the portfolio weights to stay constant over time, as done in the fake-Risk-Parity portfolio marketed on the web.

Risk Parity Weights (SPY = S&P 500, TLT = LT Bonds, GSG = Commodities). Calculated annually with 120-month rolling VCV matrices. 1926-2026.

Of course, I’m not saying that “risk non-parity” in Frank’s Risk Parity portfolios is a huge problem. Quite the opposite, it’s not a bug; it’s likely a feature because some of the asset return results would have looked even worse if you had insisted on strict Risk Parity weights. Specifically, because the Golden Butterfly and Golden Ratio portfolios still maintain a decent equity allocation (40-42% weight), they will perform reasonably well. The fact that the All Weather portfolio has a risk contribution of only 35% from equities creates a huge drag in my retirement withdrawal simulations. More on that later.

Thus, a better, more appropriate label for these strategies should then be “Risk Budget(ed)” or “Risk Aware” or “Risk-Managed” strategies, rather than Risk Parity. That’s because Risk Parity is a mathematically well-defined term and none of the strategies satisfy this very unambiguous condition. The fact that Risk Parity fans don’t know or don’t want to know this is a red flag. I would not trust my money or my readers’ money to advice from this “finger painting” corner of the personal finance community.

4: Risk Parity fans ignore and/or misunderstand their own principles

Isn’t it peculiar that the Risk Parity proponents lecture the rest of us about proper risk budgeting, but then don’t even realize that they put their own portfolios together without much thought about risk budgeting. Take, for example, Frank Vasquez’s Golden Ratio portfolio. Frank wants to allocate 42% to equities, which I find a bit lean, but so be it. He likes to allocate this to both large-cap growth and small-cap value, and he then picks 21% each. That seems ad hoc. The VIOV fund now accounts for 37.2% of the portfolio risk, while the VUG only accounts for 33.1%. Wouldn’t it have been more appropriate to use risk parity in the equity bucket, i.e., allocate a bit more to VUG than VIOV to account for the different volatility levels?

The same story, only more extreme, is present in the Golden Butterfly portfolio. Here too, 20% each goes to large-cap blend and Small-Cap Value. But the risk contributions are 28.6% for large-cap and 37.4% for the much more volatile small-cap fund. Is this intentional? Why do you want more risk budget on the VIOV? And if you thought things couldn’t get worse, the All Weather portfolio takes the cake with two such inconsistencies: First, both gold and commodities get 7.5% of the portfolio weight, but gold adds much more to the portfolio risk (5.8%) than commodities (1.6%), and that doesn’t even count the fact that part of the commodity index includes gold, so get even more gold risk through the backdoor. We find a similar mismatch in the bond portion: Long-term bonds account for 48.5% of the risk, but intermediate bonds only 8.5%.

So, not only do the across-asset-class risk budgets deviate wildly from Risk Parity, but even the within-asset-class risk budgeting is completely ad hoc. It’s like they pull these portfolio weights out of their nose, risk budgeting and Risk Parity principles be damned. Either the inventors of these Risk Parity strategies are so thick that they didn’t notice it, or they knew but were too lazy or incompetent to properly calculate the weights according to Risk Parity principles – you be the judge.

Side note: all these results clearly depend on the return window you use for the calculation of the VCV. Quantitatively, the results will differ if you use a different horizon, different VCV construction methods (e.g., exponentially-weighted moving average, GARCH, TGARCH, etc.), but qualitatively, they all produce similar inconsistencies.

5: Risk Parity looks unattractive for retirees

Frank Vasquez proposes a 5%+ safe withdrawal rate due to the purported improvement in the diversification of Risk Parity. I disagree with that claim and recently wrote about this topic in my Safe Withdrawal Rate Series, Part 64. Risk Parity alone produces mostly disappointing results in safe withdrawal rate simulations for early retirees. You can significantly improve the results by adding Small-Cap Value stocks. But then any improvement in retirement safety is not due to Risk Parity, but only because of the stock-picking alpha inherent in the Fama-French SMB and HML factors. Actually, a simple 75/25 portfolio with a mild SCV bias would have easily outperformed the Risk Parity + SCV portfolio. So even if you’re truly convinced that the Small-Cap Value style comes back into fashion, you’d be better off skipping the Risk Parity method and rather implementing SCV into your simple 75/25 portfolio. From the retirement safety perspective, the Risk Parity really faces a catch-22: If SCV works, you should do 75/25 + SCV rather than Risk Parity. If SCV doesn’t work, the simulation results look worse than under the traditional 75/25 portfolio.

The Risk Parity shell game: outperformance (if any) is due to the historical SCV premium, not Risk Parity! Failsafe Withdrawal Rate estimates, 50-year horizon, 25% final asset cushion, post-1926 retirement cohorts.

But just for the record: I showed in my post last year (Part 63) that mixing in a momentum strategy can improve the SWR simulation results. Only 10% is a bit too lean, but 50% momentum and the remaining half in the S&P 500 had very impressive results. But again, no Risk Parity is necessary to achieve that.

6: Recent Risk Parity returns look disappointing

I have a very simple rule: if you want to show me your portfolio allocation expertise, don’t bother showing me simulated returns of how your portfolio would have done in the past. I can top that by pretending I had invested in Nvidia ten years ago, which could have easily afforded me a 20+% safe withdrawal rate. If you deviate in any way from a very generic allocation like 60/40 or 75/25, only actual live returns matter. So, I looked at the returns of the eight strategies that Frank Vasquez posts on his site Risk Parity Radio. For the longest time, he published his live strategy returns in table format. The last time I saw detailed returns was in early 2025, and I was able to take screenshots of the monthly returns between July 2020 and February 2025.

But Frank has since discontinued that transparency, likely due to disappointing results. So, I took Frank’s returns up to 2/2025 and added the simulated returns via the testfol.io links he provided. One other major assumption: Since the Levered Golden Ratio started a year later, I backfill the first twelve months with the testfolio simulations, so that all strategies have the same starting point. I ignore the OPTRA strategy because that one only started in 2024. So I am left with seven Risk Parity strategies. I also ignore the partial month of 7/2020 and start the simulations on 7/31/2020. I also construct my 75/25 and 60/40 portfolios. For people who are interested, I posted the return data on Google Sheets; please see here. Please note that this sheet is read-only for you.

Here are the return stats:

Return Stats 7/31/2020-6/30/2026: Seven of Frank Vasquez’s Risk Parity portfolios vs. the simple 60/40 and 75/25. Longest drawdown figure in red = “longest drawdown still ongoing in 6/2026. Final portfolio after 5% withdrawals is CPI-adjusted.

In the chart below, I plot the drawdowns over time: CPI-adjusted returns, but only buy-and-hold, no withdrawals yet! The 60/40, 75/25, Golden Ratio, Golden Butterfly, and All Seasons all had similar drawdowns in 2022, nearly down to the %. But the Risk Parity portfolios took longer to recover. As mentioned above, the All Seasons portfolio is still underwater from the 2022 bear market. The more adventurous Risk Parity portfolios fared even worse. For example, the Aggressive 50-50 had a 60+% drawdown and is still more than 35% below the peak. I just hope no one used this garbage portfolio in their own retirement.

Real. CPI-adjusted drawdowns, 7/2020-6/2026: Seven of Frank Vasquez’s Risk Parity portfolios vs. the simple 60/40 and 75/25.

Drawdowns look even worse if you model the Risk Parity portfolios with regular monthly withdrawals. Here are the portfolio values over time if you had retired in late July 2020. Only the 75/25 portfolio recovered from the drawdown. 60/40, Golden Butterfly and Golden Ratio also still look OK, but most other portfolios are seriously damaged and will likely run out of money unless the current bull market continues indefinitely.

Real, CPI-adjusted portfolio values (7/2020=100) when withdrawing 5% p.a.: Seven of Frank Vasquez’s Risk Parity portfolios vs. the simple 60/40 and 75/25. 7/2020 to 6/2026.

Risk Parity fans might object that the last six years are not really a representative sample. I agree with that, but not in a way they will like. In these 71 months we’ve experienced most of the 4/2020-12/2021 bull market, an entire bear market 1/2022-10/2022, and the subsequent amazing bull market since the October 2022 trough. So, we’ve seen more than one full market cycle. If anything is not representative, it’s that Risk Parity performs so poorly over a slightly biased sample with essentially two bull markets and only one shallow, garden-variety bear market without a recession. Wait until you run this in retirement and you actually experience five bull markets and five bear markets. You will likely do a lot worse!

Also, the bear market, which was inflationary and certainly took a toll on the simple stock/bond portfolios, should have catapulted the Risk Parity portfolios ahead of the 60/40 and 75/25. But Risk Parity sputtered, despite purportedly hedging against all the different macroeconomic risks. If your exotic Risk Parity portfolio gets clobbered during such calm times, wait until we go through the next bear market! Can you imagine how the 3x leveraged equity ETFs do if we ever were to go through a repeat of the dot-com crash?

So, long story short, I understand why Frank Vasquez needed to take down his live sample portfolio return stats. They are such an unmitigated disaster that now he only links to the testfol.io simulated results that start with the backfilled data (mostly in January 2000). But his live returns are atrocious. Especially considering that he wants to withdraw not 5% but 6%-8% of some of his now-decimated portfolios, he will face the difficult decision when he wants to retire (pardon the pun) some of the underperforming portfolios on his blog. Unsavory financial actors sometimes play this game, i.e., start multiple sample portfolios and run them for a few years. Then quietly retire the ones that performed poorly and market their financial prowess with the one or two that did well. But Frank is really zero for seven in his sample.

Most importantly, stay away from all of the exotic Risk Parity portfolios peddled by Frank, especially the ones involving leveraged ETFs.

7: Risk Parity portfolios are inefficient

Risk Parity’s inefficiency doesn’t come only from some of the terrible ETF choices, like expensive leveraged ETFs with a lot of churning and transaction costs (UPRO, TMF, UDOW, UTSL, etc.) or overpriced and underperforming trend-following ETFs (e.g. KMLM, DBMF, etc.). There is another way in which Risk Parity violates fundamental financial principles. Because we consider only the variance-covariance (VCV) matrix in portfolio construction and ignore expected returns, we are bound to overweight low-return assets and underweight high-return assets. The effect of this assumption is that with almost mathematical precision, Risk Parity portfolios must be inefficient.

In fact, one can prove mathematically that a Risk Parity portfolio lies on the efficient frontier if and only if all assets have the same Sharpe Ratio and all correlations are equal. This is not the case in the real world. Equity ETFs have much higher Sharpe Ratios than commodity funds. Correlations are very different across asset classes: likely negative between commodities and bonds and slightly positive between equities and commodities. Because the necessary and sufficient condition for efficiency is violated in all practical applications, we can be assured that Risk Parity is mathematically, certifiably inefficient.

Let’s look at the following numerical example to quantify this inefficiency. Assume we take as our asset universe the equity funds SPY (S&P 500 = large-cap blend), VIOV (Small-Cap Value), and VUG (large-cap growth), SHY (T-bills), IEF (intermediate Treasury), TLT (Long-term Treasury), GLD (gold), and GSG (commodities). I use the 10-year backward-looking risk matrix and assume the following (nominal) expected returns going forward:

Let’s plot the efficient frontier and also the expected returns and risk of different portfolios. For the Risk Parity portfolio, I assume 1/3 of the risk budget coming from equities (thus, 1/9 shares from each of the equity funds), 1/3 of the risk coming from fixed income (1/6 each from IEF and TLT), and 1/3 of the risk coming from commodities (1/6 each from GSG and GLD). Notice that this portfolio skipped the T-bill fund. I also include one “Risk Parity w/SHY” portfolio, which will spread the fixed income portion equally among the SHY, IEF, and TLT funds, but even though SHY only has 1/9 of the risk budget, it gets more than 50% of the weight under Risk Parity, due to the low volatility of the T-bill return series. Not a very sensible portfolio; please take that with a grain of salt. In any case, here’s the efficient frontier chart; see below:

Efficient Frontier constructed with expected returns and 10y-rolling VCV.

Ignoring expected returns and potentially reserving too much space in your portfolio for assets with low average returns makes Risk Parity a suboptimal investment. So, let’s repeat everybody: Risk Parity is an inefficient portfolio allocation method.

8: We don’t have enough uncorrelated assets!

The ultimate dream of financial professionals is to find uncorrelated return sources and then use them to build ever more impressive and efficient portfolio return stats. If you could find 100 uncorrelated return streams, each with a Sharpe Ratio of 0.5, then an optimally weighted portfolio would fetch a Sharpe Ratio of 0.5 times the square root of uncorrelated assets, i.e., 5.0. What’s not to like about that? The sad state of the world is that most retail investors are really stuck with two, maybe three major asset classes that are worthwhile feeding into a Risk Parity process. Number 1 and 2 are equities and bonds, respectively, with decent Sharpe Ratios, about 0.3-0.4 in equities and 0.2-0.3 in bonds. For very technically astute and experienced investors, I recommend trading the volatility premium; see my options trading landing page.

But beyond that, as a retail investor, you quickly run out of options (pun intended). A long time ago, you could have used some stock-picking flavors (small-cap, value, momentum, quality, etc.) as additional factors. However, they became so popularized that any reliable outperformance is now arbitraged away. Commodities in general, and gold in particular, come to mind, but both are highly volatile and have low average returns. Both commodities in general and gold in particular have occasional decade-long drawdowns. For example, gold had a real, CPI-adjusted drawdown between 1980 and 2024 (536 months, almost 45 years), with a peak-to-bottom fall of 83%. Commodities have certainly rallied recently, but make no mistake: Commodities peaked in 2008 and have been in an 18-year drawdown, with a peak-to-trough drop of 89%. Despite the recent rally, commodities are still almost 70% below the 2008 peak today. So, commodities in general and gold in particular don’t exude much confidence. I’m fine with my 75/25 portfolio and supplementing that with my options trading alpha!

Cumulative Total Returns, Real CPI-Adjusted. Stocks, vs. Commodities vs. Gold.

Of course, the Risk Parity crowd will show you portfolios with numerous additional ETFs, say, preferred shares, high-yield bonds, international stocks, emerging market stocks, REITs, China A shares, etc., but these aren’t exactly uncorrelated assets. They are simply combinations of your existing asset classes. For example, preferred shares are a mix of stock and fixed-income returns, and not at all a new, uncorrelated asset class (pro tip: check their performance during the Global Financial Crisis!). Emerging markets are a mix of equities and commodity exposure. So, recycling existing financial risk factors and throwing in ever more low-quality, high-expense exotic ETFs with low expected returns will not help the Risk Parity cause; it will only make the low-expected-return problem even worse.

9: Bonus Lie – You can create extra returns out of nowhere (new: 7/31/2026)

The newest Risk Parity shtick I’ve heard is that through an intriguing artifact in the construction of geometric average returns, you can actually increase the expected return of a diversified portfolio. For free and out of nowhere. Basically, Frank Vasquez wants to use this technique to boost the expected returns of Risk Parity portfolios. Specifically, during a recent discussion, Frank claimed that he miraculously and significantly raised Risk Parity returns by applying the principle of Shannon’s Alpha (sometimes called Shannon’s Demon, but I try to avoid that term and the negative connotation). It has to do with the mechanics of how geometric returns aggregate over time and how volatility penalizes those returns (remember “mu – 0.5 sigma^2”). To keep things simple and keep the flow, I will leave out the mathematical details, though.

First, Shannon’s Alpha does not apply here because it’s used in cases where you have only one single risky asset plus a risk-free asset and where frequent rebalancing back to target weights seemingly creates phantom returns, as if out of nowhere. But a similar principle, volatility pumping, would generate a qualitatively similar effect in portfolios with several risky and imperfectly correlated assets, which could be applicable to Risk Parity. So let’s get our terminology straight and study that effect. One application would be to spread the portfolio’s equity portion across several different ETFs. How much extra alpha can I generate with volatility pumping? How about very little in the best case in theory and negative alpha in practice?

First, even in the ideal case with perfect laboratory-condition return patterns, the alpha will be quite small. Let’s take an example of two assets with log-normal returns, each with 18% volatility and a correlation of 0.85. The continuous rebalance premium is 0.25 x 0.18^2 x (1 – 0.85) = 0.001215 = 0.1215% annualized. It’s not zero, but a far cry from the 6% or so additional returns that some people generate with their ticky-tacky numerical examples on the internet, usually assuming far more volatile returns (50%+) and zero correlation. So, let’s say that a 75/25 portfolio might have a 5% real expected return p.a. over the long-term (6% from equities, 2% from bonds) and a Risk Parity portfolio like Golden Butterfly with expected returns of 6%, 6%, 2%, 1.5%, and 2% real returns in the VTI, VIOV, TLT, SHY, GLD ETFs, respectively, will get you a 3.5% expected return. Add to that a rebalancing alpha of 0.12% spread over 40% of the portfolio, then you get only about 0.05% extra return. That’s not enough to overcome 1.50 percentage points in lower returns relative to the 75/25 portfolio.

But it’s even worse, because the tiny volatility pumping effect would be swamped in the real world by at least a number of other effects:

  1. Potentially higher expense ratios when shifting from a cheap, blended, and broad ETF to smaller, exotic funds, e.g., one growth and one value fund. Or one large and small-cap fund, etc.
  2. Transaction costs from rebalancing continuously, i.e., commissions, bid-ask spreads, tax drag, time and effort, bookkeeping and tax-reporting costs, etc.
  3. Other effects, like momentum in asset returns, can make frequent rebalancing counterproductive. In other words, if there is even the slightest asset return momentum, there is an advantage to letting deviations from target weights run rather than rebalancing too frequently that can far outweigh the tiny vol pumping alpha. And notice that there is noticeable asset class momentum, as I pointed out recently in the SWR Series, Part 63.

To showcase how there is no alpha left after accounting for all those pesky non-laboratory-perfect conditions, let’s compare the returns of holding just a passive 100% portfolio of the IVV ETF (iShares S&P 500, blended) and two equal portions of S&P 500 Value and S&P 500 Growth, which in equal shares make up the S&P 500 again. Let’s check the simulation results. I’m using the Frank-Vasquez-approved site testfol.io, which he uses for his own simulations. I calculate the returns between 5/31/2000 (first available full month for all three ETFs) and 6/30/2026, both for a 100% IVV and a 50% IVW + 50% IVE with different rebalancing assumptions: 1) daily, 2) weekly, 3) monthly, 4) quarterly, 5) semi-annually, 6) annually, 7) every two years, 8) every five years, and 9) no rebalancing at all. The link to the simulations: Part 1 and Part 2. I currently have the free version of testfol.io only, where I can simulate only five portfolios at a time; hence, the stats are spread over two parts. But I quite like the simulation tool, so I might even sign up for the paid version.

Here are the results:

IVV vs IVE+IVW at different rebalance intervals.

Well, Frank will now object that Volatility Pumping works better among the entire portfolio, not just the 40% equities. And it’s true that the vol pumping effect is stronger with less correlated assets. OK, let’s check that case too. Here are the simulation results for three portfolios: Golden Butterfly, 60/40, and 75/25. We have data from 1993 until 2026. I copied and pasted Frank’s own testfolio link and used the same assumptions ($10,000 starting capital, adjusted for inflation, $42 a month in distributions, etc.) to simulate all three portfolios at the nine rebalance frequencies (1=daily, 2=weekly, …, 9=never). The links to the simulations are here: GB Part 1 and Part 2, 60/40 Part 1 and Part 2, 75/25 Part 1 and Part 2.

Here are the return stats. Notice that for this exercise with cash flows, we should look at the money-weighted returns (MWRR), i.e., the internal rate of return (IRR) of the cash flows over time (initial investment, withdrawals, and final portfolio value). Though the CAGR would produce qualitatively similar results, shifted by just a few basis points. Again, the results are disappointing:

75/25, 60/40, and Golden Butterfly at different rebalance intervals.

To summarize, the Shannon Alpha doesn’t apply here. Volatility Pumping may apply but is a red herring, because a) it’s too small to matter, so momentum matters more than rebalancing alpha, and b) even if it were larger, vol-pumping also lifts the 75/25 expected returns, so it cannot bridge the massive expected returns between Risk Parity and traditional portfolios. Also notice the inconsistency: Frank only rebalances his Risk Parity portfolios once a year, invalidating any use of vol-pumping. This is a recurring pattern we see with trolls: they pick up something on the internet. They don’t understand the math, statistics, finance, or economics behind it. They don’t understand the limitations. They take it out of context and then run with it!

Risk Parity has become a Risk Parody!

This vol-pumping issue is a prime example of Brandolini’s Law, a.k.a., the Bullshit Asymmetry Principle. It takes me about ten times, maybe 100x more time and effort to refute the nonsense spread by internet trolls than it takes them to come up with it. Of course, I can’t right every wrong on the web. But this was a fun project!

Conclusions

The general idea of Risk Parity isn’t entirely bad; I’ve occasionally found it useful in intra-asset-class allocation decisions, e.g., allocating a certain percentage to various equity styles with very similar Sharpe Ratios and correlations, where the Risk Parity method is very close to efficient. But most investors should stay away from it.

Risk parity can potentially do the most damage to folks still accumulating because your equity allocation will likely be too meek. Most young investors will do best with a 100% equity portfolio: they should actually embrace volatility and use the occasional deep drawdowns to dollar-cost average, i.e., use Sequence of Returns Risk to their advantage. That’s what I did in my personal accumulation history; in the roughly 18 years of my high-earning career at the Federal Reserve and on Wall Street between 2000 and 2018, the S&P 500 performed below average (about 3.2% if adjusted for inflation and including dividends), but by keeping up with regular investments during the steep drawdowns in 2002/3 and 2008/9, I vastly improved my investment results, buying the dips.

For retirees, not all risk parity portfolios will be that bad. Especially over shorter horizons, say 30 years, some of the Risk Parity portfolios fared all right. The Golden Butterfly and Golden Section portfolios would have performed about as well as a 75/25 portfolio in the standard Bengen or Trinity study, i.e., a 30-year horizon and zero final asset value if you simulate the returns with the best-case scenario with historical Fama-French factor returns. That said, even in this scenario, with very unrealistic expectations that small-cap value outperformance could repeat, a 5% withdrawal rate would seem too aggressive. And once you scale back the unrealistic assumptions about the small-cap value premium, you’re back to roughly the same safe withdrawal rate as with a simple 75/25 portfolio.

Intriguingly, the “OG” Risk Parity portfolio, i.e., All Weather/All Seasons, as popularized by Ray Dalio and Tony Robbins, and likely the closest you can get to the mathematical Risk Parity weights, would have performed quite poorly in every arena: over both the 30-year and 50-year retirement horizon in long-term simulations, as well as in live returns on Frank’s webpage. It’s the stereotypical throwing-out-the-baby-with-the-bathwater issue, i.e., you reduce short-term volatility, but you replace it with the long-term risk of running out of money due to poor average real returns. The All Seasons portfolio hasn’t even recovered from the 2022 bear market!

In my opinion, Risk Parity is a useless concept unleashed on unsuspecting, naive retail investors hungry for financial and technical buzzwords. Stay away from it and simplify your portfolio. 100% stocks is all you need while accumulating, and 75/25 is likely all you need in retirement. That portfolio has been the most robust and reliable portfolio in retirement for the last 150 years. Most complications beyond that simple portfolio will be a crapshoot in the best case and a drag on your retirement safety in the worst case. For the record, I do recommend an options trading overlay to the technically skilled investors, as described in the series on that topic, but it’s not necessary for the typical investor.

Do I believe I will convince Frank or some of the other Risk Parity true believers? Probably not, because they painted themselves into a corner. Frank called his podcast “Risk Parity Radio,” so I don’t think he’s going to walk back anytime soon. He falls into the “foolish consistency” trap he so often points out. But maybe I can save a few unsuspecting investors from the foolish finance trap that is Risk Parity.

Update 8/15/2026: My response to Risk Parity Radio ep. 532

Frank posted his response. Or non-response. For example, he doesn’t link to my specific blog posts, which is quite unprofessional. Obviously, he doesn’t want his listeners to go to my site and check out the well-researched posts. In contrast, I have no hesitation pointing to his work, because I have nothing to hide from my readers. He can’t address any of the specific issues I raised. His rant is a collection of red herrings and strawman arguments. My detailed responses to Frank’s podcast:

Fake comment: I had an unfortunate incident with one of Frank’s supporters who made a comment under Frank’s name. I always take down inappropriate comments as soon as I become aware of them, as I did here. Frank makes a lot of hay out of this fake comment issue because Frank cannot mathematically refute anything I wrote. Frank doesn’t have the math, statistics, and finance skills to discuss at my level; hence the distraction. Also noteworthy: that same poster, from the same IP address, threatened me with violence; see these two comments:

“you better not f* up or there will be consequences in real life. I hope you’re mature and responsible enough to understand that and own it”

“So Karsten, you better be right because if you aren’t, I’m going to find you in real life!”

So, I would ask Frank to scale down his toxic and hateful rhetoric and also tell his supporters to chill when they post on my site.

Small-Cap Value discussion: The SCV discussion is a strawman argument. As I mentioned in both of my Risk Parity posts, they are not about Small-Cap Value (SCV) stocks. If you believe that SCV outperforms as impressively as it has historically, then, as I showed in my post, you should use a 75/25 portfolio with SCV bias, which would have handily outperformed both the standard 75/25 portfolio and Risk Parity as well. So, to answer Frank’s question, if I now want to attack Morningstar because they see SCV potentially outperforming, the answer is no. My beef in this discussion isn’t about SCV; it’s about Risk Parity. Frank likes to conflate these two issues and then claim he has the support of all sorts of internet influencers when he doesn’t.

Also, I’m writing this again for the gaslighting-damaged Frank fans: I don’t hate value stocks. I allocate 50% to value and 50% to growth in my blended index funds. I can even see value stocks partially catching up again, offsetting some of the losses over the last 20 years. I have simulated that scenario in my SWR Series, Part 62, and even with a generous SCV premium (small stocks at 1.2% annually & value stocks at 0.8% annually), the extra risk isn’t worth the extra return. I wouldn’t bet my retirement on it; hence, I employ an unbiased portfolio in blended index funds that covers all bases, i.e., a continued AI-fuelled bull market, a revival of value stocks, and everything in between.

Gold: The same issue applies here: I wrote a post in my SWR Series, Part 34, where I simulate safe withdrawal rates when adding 10-15% gold. Frank has publicly admitted that he likes that blog post. Well, either he lacks the reading comprehension to understand it, or he didn’t read it til the end, where I again point out this important caveat:

“So, the widely-cited exotic [Risk Parity] portfolios don’t exactly deliver any notable improvement in the safe withdrawal stats. I’d stay away from them! If you want to use gold to hedge against sequence risk, shift some of the equity portion [of your 75/25 portfolio] into gold. But stay away from the “sexy” portfolio allocations recommended by the internet gurus and motivational speakers!”

Risk Parity doesn’t have a monopoly on gold. If gold (or SCV or momentum, or any other exotic flavor) has a positive marginal effect, it doesn’t create an automatic rationale to do Risk Parity. In all cases I have studied so far, you’re still better off adding that style to a simple 75/25 portfolio, but avoiding Risk Parity.

Bill Bengen’s new book: Bill Bengen doesn’t recommend value stocks, only small-cap stocks. With the historical outperformance of small-cap stocks (which he also extrapolates to micro-cap stocks), Bill believes he can squeeze out more expected returns. The same caveat as with SCV and gold applies again: If you believe the small-cap revival hype (I don’t, FYI), shift some of your 75/25 portfolio into small-cap stocks, but stay away from Risk Parity. Also noteworthy, Bill Bengen very explicitly notes that the elevated equity price/earnings ratios require caution and lower withdrawal rates, refuting Frank’s longstanding religious belief that the CAPE doesn’t matter. Finally, much of the increase in Bengen’s SWR isn’t due to a better asset allocation, but to shifting the success criterion from 100% safe to mostly safe. No miraculous new research on retirement safety has emerged. It’s mostly shifting the goalposts, accepting higher failure rates, and forcing more flexibility.

Creepy Uncle Frank: Frank discusses my consumption and withdrawal rate patterns at length, as if he knew my life in retirement intimately. He doesn’t, but nevertheless, Frank is serving his listeners creepy stuff like this:

“He’s got this option strategy that he’s been working on and now has opened a financial advisory practice and has registered with the SEC for that. And according to their most recent disclosure, they’ve already got $24 million under management and are charging a 0.8% AUM fee on it. […] He’s just living off dividends and interest and then adding a side hustle to that. And if you’re only spending about 2% of your invested assets, you really don’t need a safe withdrawal rate strategy or any big analysis to do that.” RPR, Ep. 532

I have made this point many times: I initially used my blog as my personal (and public) notebook for early retirement planning between 2016 and my early retirement date in 2018. I could just call it a day now and shut down my blog because I’ve clearly solved my own retirement-safety issue. Out of intellectual curiosity and as a public service to the community, I keep going. I had incredibly perfect timing, retiring in 2018. Today’s retirees, especially those who don’t have the same post-retirement earnings options I had, may not be as lucky and may still benefit from my content.

Regarding the “stage 4 retirement police” comment, I should note that I make a modest amount of money from my business activities, but the bulk of my withdrawals comes from my portfolio. I consider neither the blog, nor the advisory business, nor the options trading income to be a permanent and guaranteed income stream, at least not for decades into retirement and certainly not for the entire duration of my retirement. I enjoy the extra income as long as it lasts, but I’m prepared to shut it down to zero and live completely off my portfolio at any point. This is how I structured my retirement budget, factoring in a safe withdrawal rate of about 3.25-3.50% from the portfolio to sustain a 50+-year retirement. If I make something extra, it’s only a windfall and will not materially increase my consumption behavior. For folks who are trained in economics, you will recognize this as the permanent income hypothesis. I’m sure Frank studied it too but never internalized it. 

So, Frank’s warnings like “don’t listen to ERN, he lives like a miser” are really laughable. It’s just gaslighting. My wife and I live very luxuriously, and we don’t constrain our spending. It’s made-up fantasy land, like so much else on his podcast.

Summary: Frank suffers from “confirmation bias disease.” He reads bits and pieces from around the internet, runs with the parts he likes, and ignores everything he doesn’t like or doesn’t understand. This has been true for gold, SCV, Bengen’s book/small-cap stocks, Shannon’s Alpha, and many more issues. 

Just like a liar can’t keep all his lies straight, Frank’s “analysis” is rife with logical inconsistencies: insisting on mean-reversion in valuations within equities, i.e., according to Frank’s crystal ball, cheap SCV stocks will outperform, but the CAPE ratio, a valuation metric for the overall stock market (and statistically much more reliable and stable than SCV, by the way) is suddenly completely irrelevant, because he found one counterexaple in 2011 (which isn’t really a counterexample). Or, invoking Shannon’s Alpha/Vol Pumping, which relies on fast rebalancing of portfolio weights, but insisting also on rebalancing only once a year in his sample portfolios and simulations. Or insisting on Shannon’s alpha, which relies on an iid return distribution without serial correlation, but then also promoting momentum strategy ETFs like KMLM or DBMF, which heavily rely on trending returns, which would create a negative alpha in Shannon’s model. 

So, Frank has really painted himself into a corner. He can’t refute anything I wrote. Maybe he should just focus on different aspects of personal finance and leave the quantitative parts to, you know, retired quants like me.

Thanks for stopping by today! I’m looking forward to your comments and suggestions below!

Title Picture Credit: pixabay.com

Exit mobile version