Bloomberg Professional Services
This article was written by Steve Hou, PhD, Quantitative Researcher at Bloomberg.
Analyst ratings are one of the most widely followed metrics for equity investors with ANR<GO> being one of most frequently visited functions on the Bloomberg Terminal. Analysts are closely followed because they usually possess deep knowledge about the industries they cover and regularly uncover new fundamental information about individual companies. The fact that analyst upgrade and downgrade recommendations instantaneously move stock prices reflects the weight that investors place on their knowledge and analyses.
Analyst recommendations are also often questioned. Specifically, analysts are commonly perceived as exhibiting a bullish bias. This is documented in the academic finance literature and in the linked whitepaper. It turns out analysts often are not wrong, but may be late. By the time analysts collectively come to love a stock, it may be too late to buy as most of the upside has already been priced in.
So how can investors extract useful information from analyst recommendations of stocks? An obvious thing to do is to invest in stocks with the highest analyst ratings. Indeed, a rich finance academic literature has shown that the most highly rated stocks tend to outperform the least highly rated stocks. Figure 1 shows that equity indices comprising 50 US stocks with the highest consensus analyst ratings, whether it’s equal-weighted or market-cap weighted, have at various times kept up or outperformed the broader US stock market index.
Can investors take a different approach than investing in stocks that are most beloved by analysts? Indeed. By defining an “improvement score” that follows (similar as a typical stock price momentum signal), a contrarian ANR improvers strategy intentionally avoids the buy-rated stocks and invests instead in those stocks, whose consensus ratings have seen the most increase recently. Figure 1 shows that such a strategy has earned significantly higher returns than both the broader market and the most highly rated stocks. Further, the excess returns are highly orthogonal to traditional sources of equity factor risk premiums.
Why have the ANR improvers performed strongly over the long run? While the linked whitepaper dives into greater details on the construction and factor characters of the above-mentioned indices, it is worth touching on the core intuition: ANR improvers represent a bet on the asymmetric opportunities in turnaround companies.
The intuition of the ANR improvement signal may be demonstrated by an example: how the ANR Improvers Index has traded the stock Oracle Corp (Ticker: ORCL). Since 2020, the BANR Index has held Oracle three separate times. The transactions are tabulated in Table 1. Fortuitously, all three transactions were profitable and in fact the returns exceeded the those of the benchmark index Bloomberg US Large & Mid-Cap Index.
As can be seen in Figure 2, all three times the BANR Index buys Oracle when the ANR improvement score rises (its consensus analyst rating increases over the past 6 to 12 months) and sells when the improvement score falls. In one of those instances (“2020-10-05 – 2021-06-10”), the stock price continues its previous uptrend. In the other two instances (“2022-06-09-2023-09-04” and “2023-12-14 – 2024-06-13”), Oracle’s stock prices staged reversals of their prior downtrends.
The Oracle trades show an example that the analyst rating momentum does not simply follow stock prices. Rather the improvement score anticipates a turnaround of the stock. This point is further demonstrated systematically in the white paper. Oracle is dropped as of the rebalance on Jun 14, 2024, as its consensus analyst rating has climbed above 4 or a “buy”, hence ineligible for ANR improvers.
The Oracle example also illustrates the nature of the ANR improvers signal that when it picks up a turnaround stock, it often captures “idiosyncratic” risks surrounding the company. In the case of Oracle, which had been going through a sectoral recession post the COVID Work-from-Home demand, the turnaround came at the heel of the generative AI revolution and a surge in demand for high performance computing servers for training foundational AI models.
Back on the aggregate level, the analyst ratings of individual stocks have experienced significant inflation globally over the last twenty years. As Figure 3 shows, the median US large and mid-cap universe stock saw its consensus ANR score increase steadily from under 3.7 to almost 4 (half the stocks in the universe are “buys” or “strong buys”). In contrast, the ANR improvement score of the median stock fluctuates symmetrically around 0. The ANR improvement scores may be arguably unaffected by the ratings inflation.
Since 2023, the strong performance of the broader stock market has represented the momentum strength of the most beloved mega cap stocks while the rest of the index has generally languished. There is a wide discussion of a shrinkage of “market breadth”. This can also be seen through the soaring returns of the market cap weighted version of the ANR Leaders Index since 2023. Should such a trend either reverse itself or the returns broaden out, ANR improvers represent a strong candidate for providing strong orthogonal returns.
- Invesco Ltd has launched the Invesco Pricing Power ETF based on the BANR Index under the ticker UPGD.
This article provides a summary of key concepts from our latest whitepaper, “When Analysts Change Their Minds.”
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