Generating Qualitative Insights for Company Valuation
Author: Carlo Alberto Zucca
Estimated reading time: 10 min
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Valuation is more of an art rather than a science. This is the general conception hovering over the field of investment research and analysis. Professionals rely intensively on quantitative models, such as DCF, rNPV, Real and Financial Option approach, Venture Capital framework through which they arrive at investment recommendations or opinions to generate alpha. These models are fairly straightforward to develop and can be fine-tuned through extremely complicated add-on analysis. Regardless of their complexity, the keystone to all these models is the underlying assumptions which need to be derived both quantitatively and qualitatively from the company financials and its competitive environment.
While quantitative aspects are extensively discussed, there is not as much spotlight on qualitative elements. It is essential to understand that qualitative analysis has the same (if not even higher) importance over company valuation practices. Moreover, a lot of analysts use a bottom-up approach trying to come up with useful information to apply to the models instead of focusing on a broader macro level to derive a strategic view of the market. A thorough qualitative review especially of the sector in which the company operates is of the utmost importance, then followed by company-specific assessments.
An overview of the main qualitative frameworks
Generally speaking, we have different analysis that might be useful to conduct on a sector level:
1) Capacity, Demand & Pricing Analysis
2) Financial metrics analysis
3) Stock performance analysis against a benchmark
4) Stakeholders Analysis
Demand, Supply and Price: the fundamentals of every market
This section is dedicated to understanding what factors might affect the overall sector valuation and consequently companies’ valuation. We can start from a simple reasoning about how the inflows of a company are generated. Companies’ gains are a function of volume and pricing. Volume and pricing are a result of the interaction between supply and demand in the sector. The ideal process would be to collect historical data on demand and supply and at the same time keep track of price behaviors. The challenge here would be to define what proxies can be used to define capacity and demand. Every sector has its own drivers, which are up to the analyst to understand and track. For example, in the telecommunication sector we can find different metrics such as access lines, fiber lines, population, subscribers, call success rate, area coverage and many others. Part of this analysis can be simplified or delivered more rapidly by looking at works completed by industry associations, trade journals or consulting firms.
In case everything fails, we would need to rely on comparable companies. It would be comprehensive to also include companies that have failed over the years in order to have a somewhat complete view of these factors. Extremely important in this section would also be to understand if revenue forecasts of the companies in that sector is in line with the growth rate of the sector overall. It can happen that the comparable companies considered have an overall growth rate higher or lower than the sector they are trying to represent therefore further adjustments need to be made to the model.
Is the sector financially sound and stable ?
This section is dedicated to addressing the sector’s financial health. These data usually need to be gathered manually from individual companies since it is quite rare for associations to provide breakdown or financial information. The most helpful metrics can be summarized as follows: revenue, average selling price for major products or services, EBIT, pre-tax income, free cash flow, dividends, CAPEX, ROIC, ROE and cost of capital. For every data previously mentioned, we need to look at historical fluctuations, peaks and troughs. The essential documents that need to be present in our checklist are: annual and quarterly report, consensus estimates, earnings call transcription, MD&A statements and proxy statements. All these documents can be found in company proprietary websites or stock exchange databases. As an example, we can look for comparable companies in the NASDAQ and NYSE that count more than 6.000 companies combined. SEC (Securities and Exchange Commission) filings can be obtained through different sources but one of the most used websites is EDGAR.
The browser can provide us with 10-K (annual statement) or 10-Q (quarterly statement) filings, Initial public offering documentation (where we can find a section dedicated to market analysis), proxy statements, 8-K and much more. 10-k is the annual report and provides a detailed view of all the most relevant aspects of the company: business, risk factors, financial data, market view and other matters. 10-Q has the same function of a 10-K but also provides MD&A (management discussion and analysis) and information on options and warrants (in case of need for the quantitative sections). 8-K reports the occurrence of material events or triggering events. Proxy statements call shareholders to vote on specific matters; they might be useful to understand critical factors (defined and described in later sections). Another important document that we will need in the stock performance analysis section is the Consensus Estimate. However, this information is usually provided by Bloomberg, Reuters, FactSet and other financial data providers.
Call earnings can also be downloaded from this database and it is used to collect information on the doubts and questions that investors raise during the publication of the financial results and thus can help to gather extra information on current relevant topics.
The second part of this analysis consists of gathering macro-economic data and checking for their peak and trough. There are hundreds of possible metrics provided by governments or public institutions worldwide: nominal and real GDP, labor productivity, employment, household savings, national savings, short and long term interest rate, import, export et cetera. The main proposition in this section is to compare the fluctuations of macro-data and financial metrics and try to figure out correlations between the two areas.
Connecting the dot: creating a first strategic look of the sector
This section is dedicated to the analysis on how the above-mentioned factors affect the sector’s valuation. In order to understand how the valuation changes we need to compile a reliable universe of comparable and track their share prices over the past 15/20 years at least. During this screening it is important to avoid survival biases and adjust for possible outliers. For example, sectors with high competition but few leaders might end up warping the analysis and shifting the results towards those leaders’ performances. At this point, we need to derive insightful valuation multiples that can allow us to derive proper conclusions on the sector’s valuation fluctuations. The most used multiples are EPS and cash flow multiples. We need to remember stocks trade on expectations rather than actual financial performance (today more than in any other period in history), therefore we will focus our analysis on the consensus that our universe bears. We are trying to assess sector-level valuation, we don’t need to get too company specific. Since it is quite hard to find sector-level consensus that is specific for our target, it is likely we will have to build one from the universe we created previously. The main outcomes from this analysis should provide us insights about:
a) Period of out/underperformance.
b) Changes in relative performance due to valuation multiples fluctuations or consensus earnings alterations.
c) Delay between sector performance changes and adjustments in sector fundamentals.
As a last step for this part, we will need to compare the results of our home-made sector index with a suitable benchmark and check when our index outperforms or underperforms the benchmark. Ideally, we want to understand whether the different results are due to changes in valuation multiples, financial metrics, expectations or results. This part provides us with hints about inflection points, time of reactions and general trends.
Sectors are not watertight compartments
Stakeholders analysis has been created for company-specific purposes and with time has evolved into a great tool to incorporate economics, political science, game theory, decision-making and environmental sciences. It is also an interesting tool that allows us to develop our knowledge on the vertical stream of our sector. Through this analysis, we can better understand who the suppliers, vendors and final clients of our sector are. This is essential to estimate how downstream or upstream events might impact our sector.
This analysis usually ends up with a matrix that allows a company to identify the most relevant people, organizations, companies or associations, their level of participation, their interest and influence in the project in order to determine how to involve them and communicate with them in an efficient manner. On a sector level, this entails listing and assessing the influence of different stakeholders on the sector performance.
This process can be divided into 3 steps:
- Identify the products or services that make the major inputs to your sector.
- Identify the sectors that purchase products or services from your universe of comparable.
- Run reality checks with industry professionals or colleagues that have previously worked on the same area.
Further narrow down of the analysis
Once we have completed the sector level analysis, we can start looking at recurring trends over single companies that are part of our comparable universe. These companies will need to be compared among each other in order to gather insights on possible factors for price and financial fluctuations over the years. This screening would create, together with the previous sector assessment, a list of criteria that can aid our forecasts.
Materiality & Monitoring: two important aspects of our critical factors
Once we have understood critical factors that might influence our sector or individual comparable, we need to define the materiality of these factors. We can define materiality as a consistent change in the underlying financials of a sector or stock, a change in players expectations or a change in the resource allocation process. Moreover, these factors need to have a relevant likelihood of occurrence over the typical investment time horizon to be considered material.
The next step is to look at current financial and valuation metrics or proxies, in order to derive any slight change and identify possible new critical factors. Historical events work better for companies with a long trading history, while current analysis is more suited for companies that are highly influenced by current market condition and expectations on their growth rate. As we have mentioned previously, stocks trade on their forward multiples which are derived from business inflows capability in the future and their opportunity cost of capital. It becomes clearer, if we consider two companies being appraised using a perpetuity framework (respecting the on-going concern assumption).
If we assume a Beta of 0.97, a FCFE of 100 in a risk free rate of 1%, expected market return of 8% and expected market return equal to the actual risk-free rate (1%) and two different growth rates: growth rate (a) of 1% and growth rate (b) 1.5% and we calculate the value of this stream of cash flow we would have:
- Case growth rate (a): In this case we use a growth rate of 1%
re =0.01 + 0.97*(0.08-0.01) =7.79%
Equity Value = (100*1.01)/(7.79% – 1%) = 1487.48
- Case growth rate (b): In this case we use a growth rate of 1.5%
re =0.01 + 0.97*(0.08-0.01) =7.79%
Equity Value = (100*1.015)/(7.79% – 1.5%) = 1613.67
We can notice that case B delivers a valuation 8.48% higher than case A with only a difference of 50 bps in growth rate. The result would be exponentially different considering companies with 10 or 15% expected CAGR.
Once historical and current criteria of stocks and sector’s fluctuations has been assessed and shortlisted, we need to develop a monitoring tool in order to keep track of the criteria and deliver accurate forecasts for our company to be analyzed. Criteria are not set in stone; it is likely for the 4/5 material and critical factors that we spent weeks studying to become less material due to company market strategy to hedge against those factors. For example, we can think of the price of commodities such as oil, copper or cotton. During the XVII and XVIII century the price of commodities was a critical factor that might have had a huge impact on entire countries and economies but the advent of derivative products made commodity price fluctuations a factor less challenging. Today most of the companies or even countries (see how Mexico didn’t suffer from the oil price collapse during Covid epidemic) have already eliminated the risk of price fluctuations through forward, future or other derivative contracts.
Scouting for new factors can be time consuming, however the benefit comes in the shape of white noise reduction. The factors listed as non-material or non-relevant will allow us to ignore them and focus on the most important ones. News are close to infinite and will come in quick; we will need to be able to immediately assess the need or not of that information.
Team effort: build your own winning squad
Last but not least, investment analysis is not a single-player quest. The most successful researchers ask for clarifications and explanations to colleagues, industry professionals, company managers, associations or any other resource that is deemed to be reliable for this task. Whether you are more on the quantitative or qualitative side, don’t forsake the other half. Build your own research style and good luck with your investments!
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