Valuation of companies and investments is one of the most complex tasks in business economics as a large number of factors that influence value have to be analysed as precisely as possible. This is made more difficult by the fact that they predominantly involve the future and therefore uncertain data that the valuer can (at best) only directly influence and shape to a limited extent. For example, who today can predict what influence digitalisation, artificial intelligence or other disruptive developments will have on established and (currently still) successful business models.
We spoke to Prof. Sascha H. Mölls, professor of business studies and financial reporting at Philipps University in Marburg, about the latest developments, methods and regulation in the field of company valuation.
A provocative question to start with – is company valuation more of a science or is it simply looking into a crystal ball?
Sascha H. Mölls: You've got right to the key problem of making predictions in any forward-looking valuation. At first glance I admit that it definitely gives the impression of being like looking into a crystal ball. Even though this problem, which results from uncertainty, can never be completely resolved, the vast majority of academic discussions address the issues in the context of valuation parameters that are far more structured.
Of course, this structure still provides plenty of scope for discretion, but everything can then be investigated in detail using specific questions as part of theoretical and also empirical analyses, and thus contribute to proposing sound solutions.
At this point, let me come back to the "crystal ball" accusation which – as I previously explained – is raised whenever we talk about the problem of making predictions. For some years, (real) option based valuation approaches have been providing methods for modelling and measuring possible cashflow trends using stochastic processes. Models like this, which have not yet become well established in business practice – probably due to their complexity – do require certain assumptions regarding developments but, at the same time, allow valuation of complex decision situations at a company and/or project level. Very similar approaches to the valuation problem can be found in many other areas of science, for example climate research. There is unlikely to still be anyone today who would seriously contend that the extrapolated predictions are the result of looking into a crystal ball.
How can capital market based methods predict what influence digitalisation, artificial intelligence or other disruptive developments will have on established and (currently still) successful business models?
Sascha H. Mölls: As I understand it, the question relates not so much to the concept of the capital market based methods themselves as primarily to the forecasting problem, in other words the problem of how to define the valuation parameters in particular decision situations. There is no doubt that in current standard methods, this is at the discretion of the valuer who has to identify and verify the plausibility of both the denominator and the numerator for the cash-based formula in a specific situation, so that this variable can be consolidated to give an expected value or a decision value. However, when it comes to sound analyses, the (real) option based valuation methods that I already mentioned could be useful for the developments you have outlined, as they are conceptually able to model different levels and sources of uncertainty and measure them using a complex valuation formula. I think there's a very good reason why these kinds of methods are so popular in literature relating to finance and the capital market when it comes to valuation of research and development (innovations), risk capital, long-term infrastructure projects, industry-specific valuation problems and more general business strategy issues. There is a great deal of methodological knowledge and potential out there, but unfortunately those involved in making real-world valuations are not yet tapping into it.
In a few sentences, could you please summarise the key academic and professional developments in the field of capital market based valuation in recent years?
Sascha H. Mölls: At a theoretical and conceptual level, I think that discussions of company valuation in Germany in the "classic" literature have primarily addressed detailed technical valuation issues, for example relating to valuation of tax advantages with different assumptions, determination of multi-period capital costs or the incorporation of business growth into valuation formulae.
In my opinion, this theoretical work on valuation may not always have had much of a direct benefit for real-world business.
Thankfully, however, alongside the conceptual discussions there has been an increasing trend towards putting existing valuation models on a more solid empirical footing. In many cases, this has directly revealed the possible practical applications and limitations of existing concepts, delivering valuable insights for real-world valuations. In the age of big data, the increasing availability of business data is likely to add even more weight to this empirical underpinning in the future. In view of the developments discussed in the previous question, this could also be true for (real) option based valuation models, which to date have lacked comprehensive empirical validation.
Future opportunities and risks play a large part in determining the current and future value of a company. However a look at the world of company valuation shows that risk is frequently reduced to a single variable, known as the beta factor. Does this not massively trivialise the complexity of valuing companies?
Sascha H. Mölls: It's definitely true that reverting to capital market models such as the CAPM or the beta factor represents a significant simplification based on narrow and arbitrary assumptions. But I wouldn't go so far as to call it trivialisation. To a certain extent I think that the situation here is more like a kind of trade off. On the one hand, company valuation is accused of being like using a crystal ball, that everything is arbitrary and not substantiated. On the other hand, intuitive valuation structures nonetheless based on "hard" assumptions are criticised as being too simple or too highly aggregated.
I see the return equation in CAPM or using the beta factor as a market-related risk measure as nothing more than tools to give some structure to the relevant problem. In practice, they have to be used and interpreted with careful consideration and sound judgement and thus represent a framework for the final determination of risk-adjusted equity capital costs and the fundamental relationships. However, it actually becomes dangerous when determination of capital costs degenerates into taking figures from a newspaper or similar source of information. This is definitely not appropriate for these problems and therefore is not desirable. Users need to be very aware of the limitations and scope of their methods.
In practice, the beta from a peer group is frequently used, even though it can be shown that identical or similar betas adjusted for the capital structure cannot be attributed to the same "operational risk". Why are peer group betas used in spite of these weaknesses?
Sascha H. Mölls: First of all, I want to make it clear that I'm no fan of current peer group analyses and I fully appreciate the weaknesses of the method. But please let me attempt to explain the relative popularity of this approach in practice. Starting from a strictly subjective value concept in company valuation, which has typically been expressed using the classic earnings value applied to the valuer's decision-making area, for well over 20 years now valuation with a much greater capital market focus has enjoyed considerable popularity and – because it utilises fair data – is linked to greater objectivity and more general applicability. If this kind of valuation approach is pursued and implemented in a country like Germany that is not so dependent on the capital market, it is hardly surprising that a peer group analysis is no use at all without the use of (rough) conclusions by analogy.
In reality, the approximately 1,000 stock market listed companies in Germany represent the valuation framework for all other non-capital market companies, which are then valued based on a comparison group defined in some way or another. It should therefore be immediately apparent that this kind of method may be able to provide a rough classification but does not release the valuer from carrying out their actual task. Ultimately, however, for whatever reason these kinds of comparative figures often play a role in legal disputes.
Is it plausible that when using the CAPM the calculation of expected return and thus the beta factor will only include systematic risks? These are derived from historic price trends on the stock market. This assumes that the capital market is at least as well informed of a company's risk situation as the company itself.
Sascha H. Mölls: In your question you used a term that is frequently used but I think is imprecise and therefore can be confusing. The two components of systematic and unsystematic risk are not detached from one another – they are linked together. This is because the covariance that is crucial for calculating the beta factor incorporates the company's individual risk. A (substantial) part of the systematic risk is therefore unsystematic risk. There would be no other way to explain why the CAPM or beta factor would theoretically be suitable for determining a company's risk-adjusted equity capital costs. As a consequence of the assumption of diversification that a broad-based investor – not implausibly – makes, unsystematic risk is irrelevant to the valuation (as it can be eliminated) and all that remains to determine the risk premium is the systematic risk component. For practical valuations, the usual problem of referencing the past certainly comes up, but ultimately only represents one aspect of the general forecasting problem.
You're also right to criticise the far-reaching yet simplifying assumptions due to the supply and distribution of information. The premise of perfect competition is a hard assumption that allows all the desired transformations and therefore delivers simple solutions.
Which valuation methods would you suggest for SMEs, for which no capital market information is available?
Sascha H. Mölls: My probably rather critical comments on the possible uses and limitations of peer group analysis definitely make it clear that I take a very critical stance on adopting (minimal) capital market data as a reference framework for valuing the wide range of non-capital market companies. This view is directly applicable to valuation of SMEs too. Companies like these are normally subject to very different legal requirements (for example in terms of the role of the owner) and as a result are exposed to very specific risk situations. By consequence, recent literature has proposed a move away from the mantra of conclusions by analogy based on (apparently) objectivised capital market data, suggesting the use of different risk analysis methods instead as part of a multidimensional approach. Compared to current standard valuation practices, I would rate this kind of method as very promising. It is essentially consistent with the (real) option based valuation I discussed previously, which attributes huge significance to understanding the decision situation and the valuation in the analysis of different aspects of uncertainty.
Why is more attention not paid to internal risk information when it comes to company valuation, for example using a risk coverage based capital cost calculation or simulation based methods (see article by Gleißner/Wolfrum in Handbook of Capital Market Based Company Valuation)? Do the tools of risk management not provide established instruments, even though they have not achieved acceptance in the world of company valuation?
Sascha H. Mölls: As I'm sure you would expect from my previous answers, this is something I unreservedly agree with. Understanding the risk situation and the interactions between individual sources of risk plays a key role in any valuation. Purely focusing on capital market data, reflecting the risk only at a highly aggregated level, will not generally be sufficient to obtain an appropriate valuation for the given situation. This is even more true when viewed against the backdrop of the mega trends we touched on at the beginning of the interview (digitalisation, artificial intelligence etc.) and rapidly changing global economic structures. Therefore, risk management methods and tools are definitely a good link when it comes to ongoing development and improvement of current company valuation practices.
How do you rate the company valuation methods in a financial reporting context?
Sascha H. Mölls: As financial reporting has become more international, valuation issues have gained in importance in terms of company disclosure in recent years. The specific cause of this is the tendency towards fair value, which – if no market prices are available – is calculated either by analogy or using capital market based valuations based on cash value formulae.
Thus, financial reporting is now – to a greater extent than before – directly connected to the central methods of company valuation. However, I don't think this connection is without its problems. On the one hand, efforts to establish future value methods are definitely to be welcomed, in terms of the information benefits and thus the relevance of financial reporting for decisions. Fair value may in principle be more informative than historic purchase or manufacturing costs. On the other hand, company disclosure shares the inherent problem of every future valuation: the valuation methods adopted are subjective, in other words they can essentially be determined by the valuer. The basis for the valuation becomes blurred and is no longer comprehensible to outsiders. As a result, in case of doubt the target group for financial reporting does not hugely benefit in terms of the information value of the published figures. Last but not least, the tendency towards capital market based valuation methods in financial reporting was also a central factor in the emergence of the last global financial and capital market crisis. Supposedly "fair values" can quickly become unfair if future estimates turn out to be incorrect and the recognised profit becomes cyclic as a result of time valuation. This shows that the discrepancy between the claims and the reality of capital market based valuation can entail severe economic consequences.
Finally, we'd like you to gaze into your crystal ball. What developments do you foresee in the area of capital market based company valuation in the coming years and how do you intend to help shape these developments?
Sascha H. Mölls: In my view, the developments have already been outlined very clearly in previous questions. On the one hand, there will be continuing empirical underpinning of current or slightly more developed valuation methods intended to back up the classical form of capital market based valuation.
At the same time, both for valuation of capital marked based and non-capital market companies, differentiated risk analyses relating to different risk factors as well as their interactions are gaining in significance. This applies to the valuation itself and also in relation to deriving differentiated decision-making rules. The methods and procedures required for this purpose are theoretically already available, but need to be addressed much more intensively both by academics and, especially, by those involved in real-world valuations. In the future, I personally want to continue to pick up on current issues arising from the two trends outlined and address them through both empirical and conceptual analyses.
[The questions were asked by Frank Romeike, Editor-in-Chief RiskNET]
Prof. Sascha H. Mölls has been Professor of business studies and financial reporting in the economics faculty at Philipps University in Marburg since 2011. After graduating in business studies from Philipps University in Marburg, he went on to achieve his doctorate (2003) and post-doctoral qualifications (2008), also in Marburg. Between 2008 and 2010 Mr Mölls then held the professorship in business studies, specialising in financial reporting and auditing, in the faculty of economics and social science at Christian-Albrechts University in Kiel. As well as the different aspects of financial company valuation, his teaching and research fields include empirical (comparative) corporate governance and financial reporting research, as well as auditors' decision-making behaviour.