Can we increase the Safe Withdrawal Rate with Risk Parity? – SWR Series Part 64

July 27, 2026 – Welcome back to a new part of my Safe Withdrawal Rate Series. In my 10-year quest to study safe withdrawal strategies and find ways to hedge or at least alleviate Sequence of Return Risk, I’ve come across a lot of purported “solutions.” Some actually work to at least some degree. For example, a reverse glidepath can improve outcomes. Momentum strategies look promising. But most proposed solutions to Sequence Risk are ineffective (e.g., dividend yield, bucket strategies, small-cap value stocks, etc.). The flavor of the season right now seems to be Risk Parity. My blogging colleague Frank Vasquez has been making the rounds on various podcasts over the last year or so, touting the benefits of Risk Parity, a supposedly brilliant and innovative portfolio construction method that will miraculously increase your safe withdrawal rate in historical simulations. Supposedly up to 5% or more. I’m less optimistic, though. Let’s take a closer look…

Risk Parity Intro

I am working on a separate post that will serve as a deep dive into the mechanics of Risk Parity. I will publish that shortly. Until then, I can already give you a mathematical and technical explanation; please refer to the PDF file here.

The intuitive explanation of Risk Parity is that you diversify away from an equity-heavy portfolio and try to find other uncorrelated assets. Normally, that involves a much larger allocation to nominal bonds but also commodities generally and gold in particular. Other exotic styles, like crypto, come to mind. In addition, one can also throw in tactical asset allocation strategies (e.g., managed futures/momentum) to serve as low- or even zero-correlation assets. The idea of Risk parity is that, first, you aim for a lower portfolio volatility, so hopefully you’ll experience shorter and shallower drawdowns. Second, you also spread your risk more elegantly across the so-called “four economic quadrants” (see the diagram below) when you expand your asset universe. For example, with gold and commodities, you may also capture diversification potential during times of high inflation, where a pure stock-bond portfolio might have suffered. Tony Robbins had a piece on YahooFinance to describe this in more detail.

So, this all makes intuitive sense. Risk Parity is a serious enough proposal to check if it can help us improve the performance of retirement portfolios. Let’s get started…

Risk Parity Simulations – Basics

If you’re an avid reader of this blog, you’ll know that I already simulated Risk Parity portfolios a long time ago when I studied gold in Part 34. The results back then were mostly disappointing. I’ve made some improvements in my Google Sheet since then, so let’s take another look at Risk Parity and see if anything has changed. I will test a variety of portfolios, namely:

• The classic 60/40 portfolio: 60% US large-cap equities (e.g., SPY, VOO, or IVV tickers), 40% US Intermediate Treasury Bonds (e.g., VGIT or IEF tickers).
• My preferred portfolio: 75% equities, 25% bonds, which has a bit more earnings power and, despite the higher short-term fluctuations from the larger equity portion, actually reduces the risk of running out of money during a multi-decade-long retirement.
• The “OG” Risk Parity portfolio, i.e., Ray Dalio’s/Tony Robbins’s All Seasons/All Weather portfolio: 30% equities, 40% long-term bonds (e.g., TLT, GOVZ, or VGLT tickers), 15% short-term bonds/T-bills (e.g., SHY or BIL tickers), 7.5% gold (GLD, GLDM, etc.), and 7.5% commodities (e.g., GSG)
• The Golden Butterfly portfolio: 20% each in US large-cap blend (e.g., VOO, IVV, SPY), US Small-Cap Value Stocks (e.g., VIOV), 3-month T-Bills (BIL, SHY), Long-term Treasury Bonds (e.g., TLT, VGLT), and Gold (GLD, GLDM).
• Frank Vasquez’s Golden Ratio Portfolio: 42% in US equities: 21% each in large-cap growth (e.g., VUG) and small-cap value (e.g., VIOV), 26% in long-term Treasury Bonds (e.g., VGLT), 16% gold (e.g., GLD), 10% in managed futures (e.g., DBMF), and 6% in 3-month T-Bills. More information here.
• Expense ratios for these portfolios are 0.03% for the 60/40 and 75/25 portfolios, and 0.0773% for the All Weather portfolio. The two “Golden” portfolios have expense ratios that depend on how exactly we model the small-cap value portions; more on that below.

Note that historically, Frank has had different allocations for the 10% portion in his Golden Ratio portfolio. He first started with international REITs (ticker REET), but then switched to DBMF, which is a trend-following strategy. The DBMF creates a lot of headaches: We have no backtest for the DBMF fund, so we’d need to make some assumptions here. The easy way out would be to assume that DBMF simply mimics a commodity fund, like the GSG ETF, that would line up very well with the Commodity asset class in my SWR toolkit. But that’s a bad fit. The recent returns of the DBMF don’t look anything like the GSG ETF, by design. The DBMF regularly shifts in and out of different asset classes depending on asset class momentum.

So, I propose the following method to replicate the DBMF: First, I use the actual DBMF returns since 2019 but also backfill the returns to include the simulated returns used on the Tesfolio.io site that Frank uses for his return simulations (Ticker DBMFSIM). I ran a factor model to see if and how much exposure the DBMF has to the trend-following strategy I proposed in my post last year (Part 63). There is quite a bit of correlation between the strategies. The best fit I could generate used 67% of my momentum strategy, -28% S&P 500, -18% 10Y Benchmark Bonds, and +5% Gold (and thus about 73% T-bills to fill the portfolio’s net exposure to 100%). The DBMF and simulated return chart are below. Notice that the replication is a lot smoother than the actual DBMF fund, so we should take the SWR simulations involving this factor with a grain of salt. With the actual DBMF, if it had been available during the entire simulation window, we would have had more sequence risk due to higher volatility and worse drawdowns.

I also like to simulate two different retirement scenarios:

1. The standard, 30-year retirement horizon with zero final asset value target, as in the Bengen and Trinity studies.
2. A more FIRE-realistic scenario: a 50-year horizon and a 25% final portfolio value target, i.e., you like to leave a bequest worth one quarter of today’s portfolio value, adjusted for CPI inflation. That’s the scenario I currently use for my wife and me.

A few more simulation details: The 60/40, 75/25, and All Weather portfolios are very easy to model in the SWR Simulation Toolkit. The relevant portfolio percentage allocation translates one-for-one into the asset class schema in my toolkit. For the Golden Butterfly and Golden Ratio, there is more explaining to do. The Golden Butterfly has a total of 40% in US equities, but because 20 percentage points come from small-cap value (SCV) stocks, I need to include the Fama-French factor exposures of the VIOV ETF, which are 1.03 on the SMB and 0.57 on the HML. Multiply those by 20% allocated to the VIOV, and we get 20.60% and 11.40% allocated to the SMB and HML factor, respectively. Likewise, for the Golden Ratio portfolio, 21% each goes to the VUG and VIOV. But VUG has SMB=0.04 and HML=-0.36, while VIOV again has SMB=1.03 and HML=0.57. That means the net SML exposure is 22.47% and the net HML exposure is 4.41%. Also note the 10% allocation to the DBMF Sim series. As an additional test case for SCV, I also include a 75/25 portfolio where 55% of the portfolio is in S&P 500, and the remaining 20% goes to Small-Cap-value stocks; more on that later.

Disentangling Risk Parity vs. Stock Picking

Two of the three Risk Parity portfolios rely on Small-Cap Value stocks. In addition, Frank balances the 21% small-cap value stocks with 21% large-cap growth stocks. As I’ve written in a previous post, Part 62, the inclusion of such stock-picking strategies raises a few issues.

Of course, we can always just plug in those Fama-French factor returns. But that comes with two caveats: First, back in the 1920s nobody knew about the efficacy of small-cap value stocks. Unless someone traveled forward in time to read the relevant academic research from the 1980s on the small-cap premium and the 1990s on the value premium, and then back in time to the 1920s, nobody would have implemented that strategy. Second, as I pointed out in a post in late 2024, the reliable outperformance in small-cap and value stocks gave way to rather disappointing returns recently: small-cap stocks have not outperformed large-cap stocks for the last 45 years.

Even worse, over the past 20 years, value stocks have underperformed growth stocks. I am not saying that they will never turn around again, but there has been no statistically significant outperformance in SCV in the 1980-2026 return window. How anyone would want to confidently budget for a vast SCV outperformance going forward is a mystery to me.

So, in light of these SCV headaches, let’s start by simulating the Risk Parity strategies without the stock-picking flavor. Specifically, I like to understand how much of the Risk Parity performance in historical simulations is truly due to better portfolio construction and how much is due to the alpha (fancy finance lingo for outperformance) of your stock-picking strategy. Everything else would be junk science, i.e., throwing a lot of stuff at the wall, trying until something comes out I like, and then declaring victory without understanding why exactly your new strategy works. If Risk Parity is such a brilliant new asset allocation and diversification tool, it should not have to rely on stock picking. After all, VIOV, VUG, and VOO are all highly correlated, so lumping them together in one VOO allocation shouldn’t invalidate any of the Risk Parity qualities.

So, let’s look at the simulations while, for now, ignoring the SCV stock-picking alpha…

Safe Withdrawal Rate Simulations: Risk Parity Only, no Stock Picking

In this base case, I simulate five portfolios: 60/40, 75/25, All-Weather/Seasons, Golden Butterfly Light, and the Golden Ratio Light; i.e., the Risk Parity portfolios use only the broad equity benchmark, with no stock picking included. But I do include the momentum/managed-futures return series in the Golden Ratio portfolio.

The weighted expense ratios for the two Golden portfolios are 0.0680% for Golden Butterfly and 0.0454% for the Golden Ratio. These are quite low because both portfolios rely only on the very inexpensive ETFs. Also, the DBMF (which would have a substantial 0.85% expense ratio) has its expense ratio already baked into the factor model estimates.

Let’s start with the classic Bengen-style and Trinity-Study exercise: 30 years retirement, with a $0 final value success criterion.

• The 75/25 portfolio had a failsafe withdrawal rate of 3.83%. A 60/40 had slightly lower rates, but they were surprisingly close. All Risk Parity portfolios were below that, with safe withdrawal rates between 3.35% and 3.51%. But admittedly, results look a little bit better if focusing on post-1926 cohorts. The All-Weather and Golden Ratio portfolios slightly beat the 75/25 and 60/40.
• Failure rates of the 4% Rule were all above 10% for the Risk Parity portfolios, but still acceptable at 6.13% for the 75/25.
• No person in their right mind would retire with a 5% withdrawal rate. The failure probabilities are all between 39% and 50%.
• Notice that the failure probabilities for both the 4% and 5% WR are higher if the CAPE is elevated (greater than 20) than in the unconditional case. For example, the All-Weather portfolio has a 6.33% failure probability overall but a 14.48% failure probability when the CAPE is high. This flies in the face of the prominent claim that Risk Parity makes you independent of macroeconomic shocks and equity valuations. Apparently, the Risk Parity portfolio cannot hedge out all the risk from overvalued stocks!

And next, the results for the 50-year horizon, with a 25% final portfolio value cushion:

• The 75/25 has a safe withdrawal (failsafe) rate of 3.24%. 60/40 is markedly below at 3.01%. All Risk Parity portfolios are terrible, ranging from 2.45% to 2.71%.
• A 5% withdrawal rate would be unacceptable and almost certain ruin for all five portfolios, whether simple 60/40, 75/25, or the three Risk Parity portfolios. Even 4% withdrawals would be way too aggressive and lead to very high failure probabilities.
• Failure probabilities rise when the CAPE is higher. Even for the Risk Parity portfolios.

Without SCV, the Risk Parity strategies are all pretty much nothing-burgers: suboptimal retirement portfolios. The All-Weather/All-Season portfolio is thus retired (pardon the pun) as a completely useless portfolio for my retirement. Sorry, Tony Robbins and Ray Dalio! But there is still hope for the “golden” portfolios with some stock picking alpha, so let’s keep simulating…

Safe Withdrawal Rate Simulations: Risk Parity plus Stock Picking

Because the GB portfolio now relies on the slightly more expensive VIOV fund, I adjust the expense ratio to 0.082% for the Golden Butterfly portfolio. The GR portfolio uses the VOG and VIOV funds, so the expense ratio is now 0.0601%. When adding the stock picking, I consider three different cases in my simulations that I can all model with my SWR Toolkit, as described in Part 62:

1. No alpha from HML and SMB. I keep the HML and SMB factors in the simulations, but I use the HP-filtered returns to shut down the historical alpha to a zero average. The idea here is that both factors are now well-known, have essentially zero correlation with any macroeconomic risks (like growth and inflation), and thus no longer demand nor deserve a risk premium. If we simulate how today’s retirees might fare if historical return patterns repeat, we’d assume that the SCV is over and switch it off with the HP-Filter, while keeping the rest of the return patterns, i.e., equity and bond risk premiums alive.
2. Same as option 1, but I do add an annualized alpha of 0.7% to both the HMB and SMB factors. For the VIOV ETF, that would generate a weighted outperformance of just above 1.12% per year. That’s not bad. Paul Merriman once told me he’d be happy if SCV outperforms by 1% every year going forward.
3. Historical Fama-French SMB and HML returns. As I pointed out, the Fama-French factor returns were amazingly attractive over the first several decades, but have since moderated. It’s unlikely that we’re going to repeat the impressive returns pre-2006 (for HML) and pre-1982 (for SMB). So, use the simulation results with a grain of salt.

Let’s start with the Golden Butterfly portfolio. I first report the simulation results for the 30-year horizon. To declutter the tables, I now include only the 75/25 baseline and the GB portfolios with the three assumptions about the SCV factor returns.

• Failsafe withdrawal rates are between 3.33% and 3.44% for the GB portfolio, far below that of a simple 75/25. True, you could do a little bit better when a) using the raw HML and SMB returns and b) looking only at the post-1926 era with a 4.08% withdrawal rate. But you’re still miles away from a 5% safe withdrawal rate!
• Also notice that while Risk Parity with historical SCV patterns looked really great for the 1929 cohort (5.92% vs. 3.85% in the 75/25 portfolio), you now introduce another headache, namely the 4.08% failsafe rate for the 1930s decade (for the 1937 retirement cohort) and the 4.28% rate during the 1940s. So, even though you solved the initial Great Depression stock market fall, you then introduce worse results in the subsequent events. It’s like squeezing a balloon.
• Clearly, the Golden Butterfly portfolio performed well during the 1960s and 70s, almost by construction because it was tailored to perform well during the inflationary post-1970 period.
• Intriguingly, two of the GB portfolios had lower failure rates for a 5% WR when conditioning on CAPE>20 than in the unconditional case. However, the 4% Rule failure rates do show the familiar pattern where higher equity valuations cause greater failure rates.
• Regardless, all failure probabilities of the 5% Rule are unacceptably high for most retirees.

Moving on to the more FIRE-appropriate 50-year horizon:

• Golden Butterfly portfolios had inferior safe withdrawal rates, between 2.4% and 2.57% during the entire simulation period. Even focusing only on the post-1926 era, and assuming the raw SCV data, you stay below the failsafe of the 75/25.
• The failure rates of a 5% withdrawal rate are all insanely high: about 67% for 75/25 and almost certain ruin for the Golden Butterfly portfolio: between 72% and 82%.

Next, the same tables for the Golden Ratio portfolio, starting with a 30-year horizon:

• The Golden Ratio portfolios had failsafe withdrawal rates in the 3.49% to 3.58% range, much lower than the 75/25 portfolio. But admittedly, post-1926, the results look better. The best-case scenario would be a 4.22% withdrawal rate for the most optimistic Golden Ratio portfolio. Not bad!
• Quite intriguingly, the two GR portfolios with the SCV raw returns did better in terms of failure probabilities under the 5% withdrawal rate.
• Just like the Golden Butterfly, the Golden Ratio portfolio performed well during the 1960s and 70s, again by construction. It was backfitted to optimize the portfolio stats during the 1970s, so by extension it also solves some of the 1960s headaches.

Finally, the 50-year horizon stats:

• Over the entire simulation period, the Golden Ratio portfolio performed very poorly, with safe withdrawal rates between 2.66% and 2.78%, almost 50 basis points below the 75/25. That’s a 14%-18% lower retirement budget than the 75/25 portfolio.
• By “scrubbing” the data a little bit, i.e., looking at only the raw data SMB and HML and only post-1926, you get to a 3.29% SWR, slightly better than the 75/25 portfolio.
• The Failure Probabilities of all Golden Ratio portfolios were terrible at 50%+. Not even the 1970s produced a 5% safe withdrawal rate, but you got close at 4.87% in the ideal case with raw Fama-French returns.

Safe Withdrawal Rate Simulations: Stock Picking, but no Risk Parity

If you so enjoy small-cap value stocks and you believe that we’ll have a renaissance of this style again, you don’t need Risk Parity to get that benefit. Risk Parity doesn’t have a monopoly or patent on Small-Cap Value. Paul Merriman and Larry Swedroe certainly wouldn’t think so. Thus, let me do the same exercise for the simple 75/25 portfolio: I replace 20 percentage points of the S&P 500 equity portion with small-cap-value stocks (e.g., the VIOV ETF). As before, I simulate portfolios under the three alternative SMB and HML return assumptions, i.e., HP-filtered, HP-Filtered plus 0.7% alpha, and historical (=raw) returns.

Here are the results for the 30-year retirement:

• Not surprisingly, the HP-filtered SMB and HML series don’t produce any gains. Quite the opposite: adding more risk with zero extra return slightly decreases the failsafe. But you also slightly decrease the failure probabilities. So, you make the worst outcomes slightly worse, but alleviate the not-so-bad outcomes. Interesting result!
• The SCV with a 0.7% annualized alpha (about 1.12% extra returns estimate for the VIOV ETF) does almost as well as the 75/25.
• Finally, the SCV raw returns provide some relief from Sequence Risk. You increase the SWR to 3.94% (all cohorts) and 4.13% (post-1926). The failure rates of the 4% Rule improved with the 0.7% alpha and raw returns SMB+HML. If you’re a strong believer in the small-cap value factor, I won’t judge you for mixing this into your retirement portfolio.

And next, the results for the 50-year horizon, with a 25% final portfolio value cushion:

• The 75/25 with the most optimistic SCV assumption (raw return) performed quite well. The failsafe rate is now 3.31% (unconditionally) and 3.74% if considering only post-1926 data. That’s a significant boost relative to the 75/25 portfolio. But you know what? That’s also a significant boost relative to the most optimistic SCV assumptions under Golden Butterfly (3.16%) and Golden Ratio (4.13%).

So the lesson learned: The Risk Parity strategy performance poses a truly intriguing catch-22: Either you do only Risk Parity, in which case all return stats suck, across the board, whether All-Seasons, Golden Butterfly, or Golden Ratio. Or you hope and pray for the miracle of Small-Cap-Value stocks, in which you do have a slight edge over the classic 75/25. However, in that case, all the Risk Parity plus SCV still underperforms a 75/25 plus SCV. It’s almost comical how hopeless the case for Risk Parity is.

Objections from the Peanut Gallery

I already know how some Risk Parity fans are going to attempt to dispute my research, so here are my replies to the standard fare of the cheap shots from the Peanut Gallery:

“Portfoliocharts has better-looking simulation results!”

Yes, but that’s because the simulation window there starts only in 1970, so that site conveniently ignores some of the historical worst-case scenarios: 1907, 1911, 1929, 1937, 1964, 1965, and 1968. PortfolioCharts, while clearly visually very appealing with beautiful charts and tables, is really only a garbage-in, garbage-out affair. If you want your portfolio to do well in PortfolioCharts.com simulations, you will seek all the usual suspects: small-cap stocks (which had a fantastic run in the 1970s), gold (which also had a nice run after gold ownership was legalized in 1975 and the pent-up demand caused a great run and nice diversification benefits during the terrible 1970s malaise), and commodities. But that will overfit your asset allocation. If the future looks different from the 1970s, you could have some very frustrating outcomes. It’s much safer to pick an allocation that’s been robust to all of the various market events, not just the 1970s.

“SCV is such a crucial ingredient in Risk Parity, you can’t disentangle Risk Parity and SCV!”

If you think that, you demonstrate that you don’t understand the mechanism behind Risk Parity (or finance in general). The funds VOO, VIOV, and VUG are all highly correlated, much more so than the inter-asset-class correlations, say, between stocks, bonds, and gold. Lumping the equity funds together in one simple fund will not undo the benefits of Risk Parity, which relies on spreading risk around the maximum range of asset classes. The fact that Ray Dalio’s All-Weather OG Risk Parity portfolio doesn’t mention SCV tells you that you can indeed disentangle the two items.

“We should ignore the pre 1926 simulation results because the Fama-French database didn’t start until July 1926!”

That is a very weak argument for several reasons. First, I have the simulation assuming 1.12% annual outperformance of the SCV equity style (i.e., scenario 2 with 0.7% alpha in the SMB and HML), and those simulations are still disappointing. Second, a portfolio that started in 1919 still has most of its history subject to the HML and SMB factors (especially in the 50-year simulation), even though there were a few zeros over the first few years. As long as all the other return series are available, we should run the simulations and assume that the 1900-1925 equity returns were just the index return. If Fama and French couldn’t find the pre-1926 data with today’s research methods, the average retail investor wouldn’t have found the stats to put together a small-cap value portfolio at that time either, so it’s a natural assumption to set the HML+SMB to 0% pre-1926. Lastly, I can guarantee you that if the shoe were on the other foot, i.e., the 1900s and 1910s results had looked much better for Risk Parity than for 75/25, the influencers would be touting that fact and would insist on including the earlier period, citing the very reasons I spelled out above. Besides, even the post-1926 return stats aren’t that impressive for Risk Parity.

Addendum: July 27, 7:30 AM

People in the comments section raised a few issues:

1. Rebalancing: My portfolios are rebalanced monthly. As I showed in Part 39, there is no discernible alpha (excess return) from varying that frequency: If you go to quarterly or annual rebalancing, you may slightly increase or decrease your SWR. It’s a crapshoot. It’s mostly the luck of the draw when you rebalance around the turning points. Sometimes you get lucky with less frequent rebalancing. But then you’d likely also get lucky with a 75/25 portfolio and infrequent rebalancing. So, the rebalance risk would apply to both RP portfolios and the 75/25.
2. Frank’s Portfolios aren’t really Risk Parity: I know. I will point that out in the upcoming “How To Lie” post, as issue #3. Unfortunately, going more toward Risk Parity will only worsen the outcomes. I show that in issue #7: Risk Parity portfolios are inherently inefficient because they only look at variances and covariances, not average returns, so the more you go toward Risk Parity, the worse your Sharpe Ratio gets.
3. Leverage: None of the portfolios I presented here have leverage. Introducing leverage would be a terrible idea. You increase your average returns but also increase your volatility, thus worsening your Sequence Risk. I simulated Frank’s “Aggressive 50-50” portfolio (33% each in UPRO and TMF and 17% each in PFFV and VGIT), and the safe withdrawal rate dropped to below 2% in the 1960s for both 30- and 50-year horizons. The reason for this terrible performance is that, for example, the UPRO increases volatility 3x, but excess returns over the risk-free asset grow much more slowly than 3x due to trading costs, churning, whipsaw effects, etc. More leverage means worse Sharpe Ratios and worse retirement outcomes.

Summary

There you have it. I’m not very convinced that Risk Parity is a useful strategy for retirees, and I believe it’s even more dangerous for people in the accumulation phase, but that’s a topic for another day. Pure Risk Parity without stock-picking alpha in the form of Small-Cap Value stocks is largely useless. The All Weather/All Season strategy is systematically much worse than 75/25. The other two strategies, GB and GR without SCV, are potentially competitive with 75/25 over a 30-year retirement horizon and for retirees who are willing to deplete their portfolio if you ignore the pre-1926 era. A 4% withdrawal rate isn’t completely safe, but some retirees with flexibility could potentially try it.

The GB and GR portfolio with SCV had no failures of the 4% rule in the post-1926 simulations, but note the caveats: there is no guarantee that the SCV premium is going to repeat again, now that all smart money chasing easy alpha knows about this flavor. I also want to reiterate the same caveat from above: the DBMF had worse return characteristics, i.e., more volatility and more extreme drawdowns than the momentum strategy I used in the simulations. The actual Golden Ratio performance may not be as good as in the simulations because of that. With all those caveats, I would not increase my withdrawal rate over that of the simple 75/25 portfolio if using the Golden Ratio portfolio.

Over a longer horizon (50 years) and with a modest bequest target, the All-Weather strategy is hopelessly inferior to 75/25 and 60/40, and even the two Golden portfolios are significantly behind the simple 75/25 portfolio. Under no circumstances would a 5% withdrawal rate be safe over the longer horizon. The failure rates of, say, the Golden Ratio portfolio would have been around 60%. So, not even the best possible stock-picking scenario, using raw returns for HML and SMB, would have been anywhere close to safe for a retiree. The Golden Butterfly failure rates would have been between 72 and 82%. Only a certifiable charlatan would recommend this strategy to unsuspecting retirees and claim a 5% withdrawal rate is safe. In fact, even a 4% withdrawal rate would be pushing your luck over 50 years.

In my professional opinion, Risk Parity as a retirement portfolio is a scam because it hides a completely different asset allocation trick, i.e., backfilling your simulation data with the Small-Cap Value stock-picking flavor. The purported outperformance of that stock-picking alpha creates all the benefit. So, the great irony is that even in the few instances where Frank’s Golden Ratio portfolio or Tyler’s Golden Butterfly portfolio looked competitive, it’s not because of the Risk Parity part. It’s entirely due to the SCV part, while the Risk Parity element of your portfolio actually hurts you at the margin. Let’s repeat, everyone…

The parts of the Golden Butterfly and Golden Ratio simulations that did well did so not because of Risk Parity, but despite it.

I like the diagram below showcasing the Risk Parity shell game. While it’s true that the Golden Ratio portfolio had a decent safe withdrawal rate over 50 years (3.29%, post-1926), even slightly higher than the 75/25 portfolio (though a far cry from the 5% claim), looking at the marginal(!) impacts of making one change at a time, you notice that SCV always improves the results and Risk Parity always reduces your Safe Withdrawal Rate:

Thus, intriguingly, even if you believe that SCV will work again and will work as well as in the 1920s through 1980s, however insane that assumption may be, the best path forward is not Risk Parity: Rather, you’d simply still prefer a 75/25 where the 75% equities consist of 55% VOO and 20% VIOV. Not that I would recommend that, but conditionally on your SCV wet dreams, you should just do SCV only and ignore the Risk Parity part.

So, long story short, I warn my readers, in the sharpest possible tone, to stay away from Risk Parity. It’s an inferior and suboptimal allocation method. People who push this approach and claim the safe withdrawal rate is 5% have cooked the books to come to that conclusion. I will have some more fun facts about the false advertising and misunderstandings that the Risk Parity crowd likes to spread. It will appear in a future installment of my “How to Lie with Personal Finance Series.” Stay tuned!

Please leave your comments and suggestions below! Additionally, be sure to explore the other parts of the series; see here for a guide to the different parts so far!

Title Picture Credit: WordPress AI + ERN edits