March 4, 2024

For quickly evaluating sectors through an initial lens, scoring equity sectors based on well-known factors that have demonstrated robustness in academic consensus can be an effective method to gain insights rapidly. Similar to equity scoring models, we can score sectors by ranking aggregate metrics for each main factor. While it's not the definitive solution, it significantly reduces the workload. Instead of poring over dozens of charts for each sector, a concise scoring board can provide a solid understanding of where sectors stand in relation to a given factor.

Strategists can utilize a ranking model to swiftly garner insights and remain up to date before conducting a more in-depth analysis of each sector. Systematic investors might employ their ranking model to create a rule-driven algorithm based on these scores. For fundamental equity investors, a ranking model offers a rapid overview of where their sector of interest currently stands in comparison to others.

In our sector scoring model, we work with the 11 known GICS sectors (The Global Industry Classification Standard developed by S&P and MSCI). However, this model can also be applied to GICS industry groups and even sub-industries. In the model, metrics and averages of metrics per factor are first calculated for each sector in the background. Then, all the factor metrics are ranked against their peers. It's a simple ranking from 1 to 11, with 1 being the best score. The total rank is an equally weighted average (weights can be calibrated according to preferences) of three main domains:

1. Price Rank: A rank based on metrics that consider price momentum and the breadth of the sector.

2. Shorter Term Rank: A rank based on factors we consider more short-term oriented for investors with a horizon of one month to one year.

3. Longer Term Value Rank: A rank based on factors we consider more long-term oriented for investors with a horizon exceeding a year.

Based on these four rankings alone, investors can already quickly gauge potentially interesting trade setups:

- Shorter-term setups: sectors with the best total rank.

- Shorter-term trade setups: sectors with the best price rank and short-term rank.

- Longer-term trade setups: sectors with the best value rank and perhaps a reasonable price rank.

2. EQUITY FACTOR SCORES EXPLAINED

**The price rank consists of two factor rankings:**

- *Price momentum rank:* An average ranking of simple momentum indicators such as the rate of change over the past 1, 6, and 12 months, and moving average oscillators.

- *Price breadth rank:* An average ranking of breadth indicators, such as the percentage of stocks within the sector index trading above their 50-day and 200-day moving averages.

**The short-term rank consists of an average weighting of five factor ranks:**

- *Macro momentum rank:* Based on the rankings of the beta of equity indices to our cyclical macroeconomic index. If our cyclical index signals a positive environment for cyclical economic growth, the equity sector indices are ranked from highest to lowest beta. For instance, currently, the cyclical signal is positive, and sectors with high beta to cyclical economic growth (like Discretionary, Tech (mainly semiconductors), Materials, and Industrials) get higher scores. Conversely, more defensive sectors such as staples and utilities would rank higher if cyclical growth became negative.

- *Analyst momentum:* Also known as earnings momentum, this is based on academic findings that analyst revisions (changes in earnings per share estimates), changes in analyst price targets, and earnings surprises can lead to further positive momentum in stocks. This also captures a part of the sentiment in quarterly management guidance. Instead of sifting through dozens of earnings call transcripts, one can look at earnings revisions. Very positive management guidance often leads to upward revisions, which can drive price momentum as investors herd towards stocks with the best guidance and prospects in the short term.

- *Fundamental momentum: *This involves looking at the second derivative of growth, defined as acceleration or deceleration in the percentage growth of trailing 12-month sales, EPS, and return on equity measured quarterly. Acceleration and deceleration are especially important for growth stocks in sectors such as Technology and Health Care. Investors often react quickly to changes in growth rates for these types of stocks.

- *Quality: *Quality is a debated factor, with academics often disagreeing on its definition. In our equity scoring models, quality consists of various subfactors like free cash flow margins, gross profitability to assets, the economic value-added spread (return on capital minus cost of capital), earnings quality accruals, a fundamental score similar to Piotroski, and a stability score of the above metrics measuring their consistency over time. For equity indices, we use simpler metrics like gross margins, return on equity, and return on capital.

- *Expected growth: *While growth is not traditionally considered a factor, we still find it relevant for short-term purposes if the growth style is in positive momentum versus benchmarks. If the value style becomes more prominent, the weight of the expected growth factor can be adjusted accordingly.

The long-term value rank is a simple weighted average (weights can be calibrated) of three subfactors:

- *The consensus analyst rank: *Analysts set price targets based on combinations of multiples with expected earnings estimates and sometimes use DCF. We incorporate intrinsic discounted cash flow estimates, which may indicate more long-term intrinsic value.

- *Free cash flow yield:* We emphasize free cash flow yield as a valuation multiple that has been effective in ranking equities across sectors.

- *Relative multiple z-score rank:* We focus on how sectors trade relative to a benchmark (like a World index) by calculating time series of individual multiples (price to earnings, price to forward earnings, enterprise value to sales, price to cash flow, etc.). We then calculate relative multiples versus the benchmark, normalize each relative multiple by calculating z-scores, and rank these z-scores to quickly identify relative deviations.

In our next blog, we will explore a similar equity screener for individual stocks.

We will highlight the industrial sector. Recently, leading manufacturing indices have been improving (chart 1 below), and momentum for the sector has been picking up (chart 2 below). Although the valuation score appears less appealing, a deeper examination reveals (it pays to dig deeper after using quantamental tools) that the industrial sector's valuation multiples are not excessively high on an absolute or relative basis (chart 3 below)compared to the world index. The sector receives a lower score because other sectors appear even cheaper. Only the technology sector is notably expensive,if we dig deeper, both on a relative and absolute basis.

Thanks for reading our work and stay tuned for the next update!

Cheers

Hans & Thomas

Stratsy