BMYMP - Healthcare Dashboard And The Side Effects Of CURE

2023-11-16 12:25:19 ET

Summary

• Pharmaceuticals/biotechnology and life science tools are close to their historical baseline in value and quality.
• Healthcare equipment is the most overvalued subsector.
• Ten healthcare stocks cheaper than their peers in November.
• CURE: Why most investors should stay away from this healthcare ETF.

This monthly article series shows a dashboard with aggregate industry metrics in healthcare. It also may serve as a top-down analysis of sector ETFs like the iShares U.S. Healthcare ETF ( IYH ) and the Health Care Select Sector SPDR ETF ( XLV ), whose largest holdings are used to calculate these metrics.

Shortcut

The next two paragraphs in italic describe the dashboard methodology. They're necessary for new readers to understand the metrics. If you're used to this series or if you are short of time, you can skip them and go to the charts.

Base Metrics

I calculate the median value of five fundamental ratios for each industry: Earnings Yield ("EY"), Sales Yield ("SY"), Free Cash Flow Yield ("FY"), Return on Equity ("ROE"), Gross Margin ("GM"). The reference universe includes large companies in the U.S. stock market. The five base metrics are calculated on trailing 12 months. For all of them, higher is better. EY, SY and FY are medians of the inverse of Price/Earnings, Price/Sales and Price/Free Cash Flow. They are better for statistical studies than price-to-something ratios, which are unusable or non available when the "something" is close to zero or negative (for example, companies with negative earnings). I also look at two momentum metrics for each group: the median monthly return (RetM) and the median annual return (RetY).

I prefer medians to averages because a median splits a set in a good half and a bad half. A capital-weighted average is skewed by extreme values and the largest companies. My metrics are designed for stock-picking rather than index investing.

Value and Quality Scores

I calculate historical baselines for all metrics. They are noted respectively EYh, SYh, FYh, ROEh, GMh, and they are calculated as the averages on a look-back period of 11 years. For example, the value of EYh for healthcare providers in the table below is the 11-year average of the median Earnings Yield in this industry .

The Value Score ("VS") is defined as the average difference in % between the three valuation ratios (EY, SY, FY) and their baselines (EYh, SYh, FYh). The same way, the Quality Score ("QS") is the average difference between the two quality ratios (ROE, GM) and their baselines (ROEh, GMh).

The scores are in percentage points. VS may be interpreted as the percentage of undervaluation or overvaluation relative to the baseline (positive is good, negative is bad). This interpretation must be taken with caution: the baseline is an arbitrary reference, not a supposed fair value. The formula assumes that the three valuation metrics are of equal importance.

Current Data

The next table shows the metrics and scores as of last week's closing. Columns stand for all the data named and defined above.

Value and Quality Chart

The next chart plots the Value and Quality Scores by industry (higher is better).

Evolution Since Last Month

The most notable moves are an improvement in value score for healthcare equipment and a deterioration in quality for pharmaceuticals/biotechnology.

Momentum

The next chart plots median returns by industry.

Interpretation

Healthcare providers, pharmaceuticals/biotechnology and life science tools are close above their valuation baseline based on 11-year averages. Pharma/biotech and life science tools are also close below their quality baseline. Healthcare providers look less attractive in this regard. Healthcare equipment is the most overvalued subsector and also shows the lowest quality score.

Dashboard List

I use the first table to calculate value and quality scores. It also may be used in a stock-picking process to check how companies stand among their peers. For example, the EY column tells us that a large pharma/biotech company with an earnings yield above 0.0358 (or price/earnings below 27.93) is in the better half of the industry regarding this metric. A Dashboard List is sent every month to Quantitative Risk & Value subscribers with the most profitable companies standing in the better half among their peers regarding the three valuation metrics at the same time. The list below was sent to subscribers several weeks ago based on data available at this time.

It's a rotational model with a statistical bias toward excess returns on the long-term, not the result of an analysis of each stock.

Is CURE a Safe ETF to Bet on Healthcare?

Direxion Daily Healthcare Bull 3X Shares ETF ( CURE ) is a leveraged ETF tracking 3x the daily return of the S&P Healthcare Select Sector Index, which is the underlying index of XLV. It was launched on 6/15/2011 and has a net expense ratio of 0.99%. To reach its objective, it holds the stocks of the underlying index along with swap contracts on this index.

Leveraged ETFs often underperform their underlying index leveraged by the same factor. Beta-slippage is the main reason of decay in equity leveraged ETFs. To understand it, imagine a very volatile asset going up 25% one day and down 20% the day after. A perfect double leveraged ETF goes up 50% the first day and down 40% the second day. On the close of the second day, the underlying asset is back to its initial price:

(1 + 0.25) x (1 - 0.2) = 1

…whereas the perfect leveraged has lost 10%:

(1 + 0.5) x (1 - 0.4) = 0.9

In a trending market, beta-slippage can be positive. If the underlying index goes up 10% two days in a row, on the second day, it is up 21%:

(1 + 0.1) x (1 + 0.1) = 1.21

…whereas the perfect 2x leveraged ETF is up 44%:

(1 + 0.2) x (1 + 0.2) = 1.44

Since inception in 2011, CURE has outperformed XLV, as reported in the next table. It also shows a much higher risk in drawdown and volatility (measured as standard deviation of monthly returns), resulting in a lower risk-adjusted performance than the non-leveraged index (measured by Sharpe ratio).

I define the normalized drift of a leveraged ETF as follows:

Drift = (Return - (IndexReturn x Ñ))/ Abs(Ñ)

Where:

• "Return" is the return of the leveraged ETF in a given time interval, including dividends.
• "IndexReturn" is the return of a non-leveraged ETF on the same underlying asset in the same time interval, including dividends.
• "Abs" is the absolute value operator.
• " Ñ" is the leverage factor.

The next chart plots the 12-month drift since one year after inception (June 2013). The historical average is negative (meaning a decay): -2.08%.

Positive drift follows a steady trend in the underlying asset, whatever the trend direction. It means positive drift may come with a gain or a loss for the ETF. Negative drift comes with daily return volatility ("whipsaw").

CURE is an efficient swing trading instrument in a bull market. However, it may suffer a large decay when the underlying index oscillates between positive and negative daily returns. Leveraged ETFs with a 3x factor like CURE are significantly more risky than 2x ETFs because the drift is amplified. They have been designed for seasoned traders with a good understanding of their behavior behind the advertised leveraging factor. In doubt, don't touch them.

For further details see: