Practical analysis for investment professionals
04 May 2020

If an Investment Strategy Looks Too Good to Be True, Look under the Hood

Could a portfolio invested 51% in the S&P 500 Index yield the same returns as one that’s 100% invested?

In mid-March 2020, a financial adviser told one of the authors that recent analysis published by a large investment management firm found that it could.

In other words, the strategy delivers the same portfolio return at only half the volatility.

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At a time when market volatility exceeds 2008–2009 financial crisis levels, such a strategy has an understandable appeal. Given the potential implications, we gave the research a closer look.

According to the analysis, $100,000 invested 100% in the S&P 500 Index under a buy-and-hold strategy on 24 March 2000 would have grown to $310,570 as of 31 December 2019. The alternative strategy invested 51% of the $100,000 in the S&P 500 Index on 24 March 2000. The research didn’t indicate what happened to the remaining 49%, but we found that the returns they report are generated if we put the $49,000 under a mattress, so it assumes a 0% return. The portfolio was rebalanced to 51% market weight on 9 October 2002, 9 October 2007, and 9 March 2009. In between those dates, the portfolio value fluctuated freely.

The 51% market-weight strategy grew the $100,000 investment to $311,560 on 31 December 2019. So the 51% market-weight strategy slightly outpaced the 100% market-weight strategy with about half the portfolio risk, just as the financial adviser said.

What jumped out at us was the serendipity of the three rebalancing dates. Those from 2007 and 2009 correspond to a market top and bottom, respectively.

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As recent COVID-19–related volatility demonstrates, determining the optimal time to buy or sell is difficult. For example, we may have bought on 11 March 2020 after the S&P 500 Index fell 4.9%, only to see it drop 9.5% the next day. Investors, therefore, are not likely to rebalance on the precise dates specified.

So how would different dates impact the 51% market-weight strategy? While we could not perfectly replicate the results, we managed to produce something similar using total returns from the SPDR S&P 500 Index ETF (SPY), which made sense as a proxy since it is investable and closely tracks the S&P 500.

In our study, the 100% market-weight strategy yielded  $304,122 as of 31 December 2019. To slightly beat that portfolio, we also needed to invest 51% in the market on each rebalancing date. That resulted in a portfolio value of  $306,311 at the close of 2019.

Using the 51% market weight and our data, we tested how sensitive the portfolio is to rebalancing a little early or a little late. First, we rebalanced the portfolio one calendar week before each of the original rebalancing dates. That gave us a portfolio value at the end of the measuring period of $292,772, 3.7% lower than the 100% market-weight strategy. Next, we rebalanced the portfolio one calendar week later than the original dates. This yielded a portfolio value at the end of 2019 of $278,587, which is 8.4% lower than the 100% market-weight strategy.

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Adjusting the rebalancing dates by two calendar weeks and the results are even worse. Two weeks early and the $100,000 becomes $281,559 — 7.4% less than the 100% market-weight strategy. Two weeks later and it equals $262,884, or 13.6% less than the 100% market-weight strategy. More generally, the result holds for virtually all (~98%) possible one- and two-week shifts of the rebalance dates.

So what’s the takeaway?

To pull off the 51% market-weight strategy requires extreme market timing: the specific rebalancing dates must be chosen perfectly. Failing that, we’re better off with a buy-and-hold strategy that is 100% invested in the market.

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Opinions expressed herein are solely those of the author and do not reflect the views and opinions of Compass Lexecon or its other employees.

All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

Image credit: ©Getty Images / Giorez

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About the Author(s)
Clifford S. Ang, CFA

Clifford S. Ang, CFA, is a Senior Vice President at Compass Lexecon, an economic consulting firm. He specializes in the valuation of businesses and hard-to-value assets primarily in the context of litigation. He has worked on hundreds of engagements involving firms across a broad spectrum of industries. Ang teaches the equity and bond valuation courses at DataCamp, an interactive data science learning platform. He has published and presented on numerous valuation-related issues. Ang is the author of the financial modeling, data analysis, and data visualization textbook Analyzing Financial Data and Implementing Financial Models Using R, which is published by Springer. The second edition of the book is scheduled to be released in Spring 2021. He is a CFA charterholder and holds an M.S. in finance. He is a member of the CFA Institute, a member of the CFA Society San Francisco, an abstractor for the CFA Digest, and has been a volunteer in support of the CFA program. He is also a member of the Rutgers University Big Data Advisory Board and Olin Business School Alumni Board at Washington University in St. Louis. His website is and his e-mail is [email protected].

Merritt Lyon

Merritt Lyon is a PhD student in statistics at the George Washington University. His research interests are in random structures, applied probability, and statistical learning. His professional experience involves developing and applying machine learning models, most recently for use in the residential mortgage market.

3 thoughts on “If an Investment Strategy Looks Too Good to Be True, Look under the Hood”

  1. This is a pretty fuzzy analysis. Even with a comparative cumulative relative return of -13.6% for the 51% market-weight portfolio, the investor might realize a superior absolute or risk-adjusted return, given the opportunity to invest the other 49% of her capital in an alternative portfolio. Why not rerun the analysis with the assumption that the other 49% of capital went into Treasuries (an investment that almost certainly would have lower risk as measured by sigma than the SPY portfolio)?

  2. This would be interesting to run with a couple of changes (I’m going to play with these when I have a little more time later today…). Assume the cash is in T-bills which would give it a couple percent interest for at least a portion of this window (You could use BSV and SPY for simplicity). I think people are, on average, terrible at market timing and get swept up in all kinds of theories about what’s around the corner. I’d like to see this based on a more traditional rebalance scheme such as annually or with a percentage trigger. I hypothesis that this would look a lot less favorable in those circumstances even with some additional cash income.

  3. Recast the same facts and it sounds as true as it likely is…not

    “Hey, you. Come here. Did you know that 100 dollars invested five years ago is now 333 dollars.

    What if I told you I had a little financial secret 8 ball that could tell you exactly when and how to rebalance. This magic ball would tell you how to become a MARKET TIMER.

    And IF you had perfect market timing like every MARKET TIMER does THEN you get achieve the same 333 with only having put 50 dollars down. That’s right. Same outcome with only half the money.

    What do you do with the other 50? Well, let’s be fair. This secret 8 ball didn’t come cheap so maybe I take 25 and then you just LOCK in the other 25 as ALPHA. Book it when it shows up, this is my last secret ball so it’s yours now. I am out of here with my 35.”

    You guys nailed it on the head. It’s not about what you rebalance the 50 into at all. That doesn’t matter. What matters is the presumption that perfect hindsight bias of identifying a peak and trough can lead to perfect foresight of the next peak and trough. In other words, do you really believe he has a secret 8 ball. Why does he need your money?

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