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Approaching 2023, the experts were in near unanimity that the fourth quarter of 2022 was little more than a dead cat bounce and that once the inevitable recession hit, the bear market would quickly take the S&P 500 Index to new lows. Instead, the first six months have seen the Nasdaq-100 ETF, Invesco QQQ rise nearly 39% while IVV, the iShares S&P 500, gained 16%. 

The ETF reports on ValuEngine for ETFs that follow market benchmarks provide a side benefit in writing market analyses. They are a window to implicit forecasts for 3-, 6- and 12-month forecasts VE models are making for each benchmark’s ETF portfolio. This is because the ratings and projections combine bottom-up constituent analysis with analyses of the historical price movements of the ETF in different market environments. This empowers us to provide both looks back and share our model’s views on that which lies ahead. 

The benchmark indexes and ETFs analyzed here are:

1. The S&P 500 Index representing US Large Cap, the ETF is iShares’ IVV;
2. The S&P 400 MidCap Index representing US MidCap; the ETF is SPDR’s MDY;
3. The Russell 2000 Index representing US Small Cap; the ETF is iShares’ IWM
4. The Russell 1000 Large Cap Growth Index; the ETF is iShares’ IWF;
5. The Russell 1000 Large Cap Value Index; the ETF is iShares’ IWD;
6. The Nasdaq-100, constructed as an index using the top 100 non-financial stocks with primary listing on the Nasdaq, but now regarded as the premier US Big Tech Index; the ETF is Invesco QQQ.

All historical data are as of 06/30/2023.

In contrast, here is the data table as of 12/31/2022 that we published in this blog this past January..

The 6-month returns represent the first half of 2022. Comparing it to the same chart six months ago provides several underlying analytic observations beyond the reversal of the direction of returns. 

1. The order of returns for the six-month period was virtually reversed in terms of style and cap size. Large cap Tech (QQQ) and Large/Mid cap Growth (IWF) crushed everything while the best-performing ETFs of the sextet at yearend 2022 lagged Large/Midcap Value (IWD) and Midcap (MDY) lagged badly, The opposite was true in 2022.

2. The ValuEngine predictive model predicted the reversal in the leadership, having rated the growth ETFs, QQQ and IWF with ratings of 4 (Buy).In contrast, in the same January blog, IWD and MDY had been rated 2 (Sell).

3. Our predictive model is predicting even more so of the same for the six-to-twelve-month period ahead. QQQ, Invesco Nasdaq-100, and IWF, iShares Russell 1000 Growth, have our highest rating of 5 (strong buy) while IWD and MDY remain rated as 2 (Sell).In street parlance, they are potential “sources of funds” which means that current holdings in either or both could be sold, then re-deployed to IWF and/or QQQ. The last sentence is just an explanation, not a recommendation.

4. From a valuation perspective, QQQ and IWF are very expensive as compared with S&P 500 ETF, IVV. This is true using all metrics from traditional financial ratios and dividend yields to ValuEngine’s valuation model. This historical over-valuation is a major reason, many market pundits have predicted the onset of a tech bubble and subsequent crash. On a predictive basis, I believe such predictions are premature at best but anything is possible. 

5. On the other end of the valuation spectrum is IWM, the iShares Russell 2000 Small Cap ETF. Greater than two-thirds of its holdings are undervalued according to our valuation model. Remarkably, given the historical relationships between small cap and large cap stocks, IWM has an identical dividend yield to IVV and a 20% lower price-to-book-value ratio. Historically, the Russell 2000 small cap index has averaged about 33% of the dividend yield of the S&P 500 and about twice as high on the basis of price-to-book ratio. Investors using mean reversion as a factor may anticipate that eventually, we will hit a period where small cap significantly outperforms large cap. Given that IWM currently has a 3 (Hold) rating, such a commitment looks to be premature for now.

In 2022, we noted the following return differentiation between winning and losing industry sectors in the market. We repeat the table here.

The same table for the first six months of 2023 flips most of the above-average ETFs to below-average and vice versa as shown here.

1. The bottom three Select Sector SPDR ETFs in terms of price change at yearend are now the top sector ETFs for the first half of 2023. Those ETFs are: XLK, Technology, XLC, Communications Services, and XLY, Consumer Discretionary. On the other end of the spectrum, XLE, Energy, and XLU, Utilities are the only sector ETFs to post positive returns in 2022. They were the two worst performers in the first half of 2023 with returns of -7.7% and -7.9% while the S&P 500 rose 16%  

2. The 2022 year-end ValuEngine ratings did not fare nearly as well as our benchmark predictive ratings. The three ETFs with buy ratings, XLF, XLE, and XLU, all posted losses for the first six months of 2023. Not one of them has maintained its buy rating at midyear. 

3. The Financial Sector ETF, XLF, and XLRE, the REIT ETF, have the greatest percentage of undervalued holdings. They are also undervalued by traditional metrics. However, neither is rates as a buy by our predictive models.

For the first time, we now include metrics on so-called “Smart Beta” or factor ETFs in the midyear review, as follows:

Smart Beta ETFs are comprised of groups of stocks index providers have determined as most representative of a particular factor regime reflecting market movements. include quality (earnings consistency and financial strength), momentum, volatility, dividend growth, dividend yield along with size and valuation. 

The top two performers for the first six months of this year and also during the past 12 months (excluding benchmark ETF IVV) were QUAL, the iShares US Quality ETF, and IWO, iShares Russell 2000 Small-Cap Growth ETF. Both are also rated 4 (Buy) for the next 6-to-12 months by our predictive model. 

MTUM, the iShares US Momentum ETF, gets our top rating of 5 (Strong Buy) for the year ahead despite performing miserably in an up market. Reassuringly, VYM, the high-dividend-yield ETF had the highest dividend yield, 3.2% while SPLV, the Invesco S&P 500 Low Volatility ETF indeed had the lowest volatility of 16.4%.

I find it fascinating that for the 5-year period ending June 2023, not one of the eight “Smart Beta” ETFs outperformed IVV, the S&P 500 ETF on an annualized basis, and only one, QUAL, outperformed IVV on a 6-month and 12-month basis. Perhaps the engineers that created these “Smart Beta” indices based upon historical data were not all that smart when it came to constructing factor index ETF smart enough to outperform in the future. As a 40-year quant, I have concluded that what a quant does best is to predict the past with ever greater precision. As we all know from fund disclaimers, past performance is not necessarily indicative of future performance.

FINAL NOTE – A Tribute to Harry Markowitz

As a quant, I would be amiss not to take this opportunity to pay tribute to the great Harry Markowitz.Harry died on June 22 of pneumonia and sepsis at a San Diego hospital.

I state without fear of contradiction that Harry created the field of quantitative investment research when he first published his article “Portfolio Optimization” in 1952.It became a staple for financial analysts around the world.He made it clear through empirical research why investors should diversify investments based upon asset price history covariances using combinations of assets called portfolios rather than simply buying individual securities. Gradually his work helped changed the emphasis of professional investors from simply buying “prudent” securities to optimizing the risk-return ratios in investment portfolios.

The framework he helped pioneer showed the correlation between low-risk investments and low returns, and high-risk investments and higher returns. This innovative theory earned him the 1990 Nobel Prize in economics alongside William Sharpe and Merton Miller.Even this honor falls incredibly short of representing the magnitude of his continuing and consistent contributions to the industry.When Richard Michaud created an optimization technique that expanded upon Markowitz optimization by using stochastics to create efficient reasons, Markowitz openly welcomed the innovation as an improvement upon his basic thesis and offered Michaud encouragement. 

I had the privilege of meeting Harry in 1989 when he was consulting with DICAM, the asset management arm of Daiwa Securities.Beyond his incredible grasp of multivariate optimization, what impressed me most was the man’s simple kindness and humility. Reading other tributes to Harry, these attributes have been confirmed repeatedly.

Rest in Peace, Harry

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