DLOM: The marketability discount in (company) valuation

The Discount for Lack of Marketability (DLOM) refers to the amount deducted from the value of a non-publicly traded company share to reflect its limited marketability. 

Marketability should be distinguished from liquidity. While liquidity only considers whether a company share can be sold quickly, marketability also includes that the sale of the company share occurs at low costs and at a predictable price with high probability.

In addition to the DLOM, a discount for lack of control (DLOC) is also possible, where the existing or missing control, according to scientific studies, can also influence the DLOM.

The DLOM originated in the Anglo-American region. Empirical studies proving its existence were already carried out in the 1970s. With the consideration of the DLOM by US tax authorities and courts, its significance in Anglo-American valuation practice quickly increased. Over time, various approaches to determining the DLOM were developed. Selected approaches with high practical relevance are discussed below.

Since valuation methods typically determine market values, it is recognised, especially in Anglo-American valuation literature, that investors demand a discount on the market price for non-marketable shares due to the higher risk. According to the Expert Committee for Business Valuation and Business Administration (FAUB) of the Institute of Public Auditors in Germany (IDW), the leading German standard-setter in business valuation, company share discounts depend on the respective shareholder (i.e., subjective). As a result of subjectivity, discounts are not to be considered in an objective share value determination. Since German tax authorities and courts strongly adhere to the IDW standards, the application field in German valuation practice appears limited at first glance. Upon closer examination, it becomes evident that DLOMs can be relevant, especially in valuations for purchase price negotiations.

Other applications arise in the valuation of employee stock option programs under the international accounting standard IFRS 2 or the valuation of financial instruments under IFRS 13. German companies may also require a so-called 409A valuation in the USA, where DLOMs are often applied, for example, when US employees are incentivised through an employee stock option program.

In recent decades, various approaches to determining the DLOM have been developed. Benchmark studies and option pricing model-based methods are particularly relevant in practice.

In these studies, DLOMs are determined based on either restricted stock or pre-IPO transactions.

In the Anglo-American region, restricted stocks (i.e., shares with a time-limited trading restriction) are common. These are particularly issued by publicly traded companies to employees as stock-based compensation. To determine the DLOM, the transaction prices of restricted stocks are compared with the stock price valid at the transaction time. It must be ensured that the restricted stocks differ from regular stocks only in terms of limited tradability. Otherwise, the lower price could also be explained by other factors (e.g., lack of dividend en­title­ment or voting rights).

Since the first studies in the 1970s, which were based on data from the late 1960s, numerous other restricted stock studies have been conducted in the USA. The most recent well-known studies are based on transactions from the 1990s. Earlier studies often determined DLOMs of 30-35 per cent in the median, while later studies determined DLOMs of 20-27 per cent. The outdated data is particularly criticised in the literature. Furthermore, the legislation on which the restricted stocks are based has changed significantly over the decades. The man­da­to­ry holding period in particular has significantly decreased. This partly explains why DLOMs in restricted stock studies are declining. It is also debated in the literature whether the risk profile of publicly traded com­pa­nies, which form the basis of restricted stock studies, is comparable to the risk profile of smaller, non-publicly traded companies to which the DLOM is applied.

Another approach in benchmark studies is comparing pre-IPO transactions with the IPO price. According to these studies, the price difference is explained by the lack of marketability in the period before the IPO. Pre-IPO studies have sometimes determined significantly higher DLOMs than those based on restricted stocks. It is questionable whether the transactions were conducted at arm’s length. The observation period of the studies is also of great importance. During the times of the new market, significant distortions in the basic data may exist. Furthermore, transaction prices from different dates are compared. The company’s earnings situation can change significantly during this time, so the price difference could be explained by other reasons. It is possible to correct a changed earnings situation (e.g., multiple-based). However, the reliability remains questionable.

The frequently used studies in practice are also several decades old, raising the question of data currency and relevance to the valuation date in this form of benchmark study.

Based on benchmark studies, a DLOM of approximately 20-35 per cent has long been established as a “rule of thumb”. However, due to the existing weaknesses of the studies, this is now viewed very critically. General approaches based on average study results are often rejected by US tax authorities and courts.

If studies are used to determine the DLOM, it is advisable to select individual comparable transactions and determine a DLOM based on the individual peer group. However, the problem of data currency remains.

For a better understanding of option pricing-based methods, it is necessary to realise that the marketability risk is pronounced in two directions (difficult loss limitation and profit realisation). On the one hand, the acquirer bears the risk that they cannot quickly sell the shares in the event of a declining value and thus cannot limit their loss. After all, a fire sale usually involves a further value discount. On the other hand, the acquirer also bears the risk that they cannot immediately sell the shares at the current value in the event of a value increase.

Numerous models now exist, usually named after their inventor. The most well-known models include:

Although the models are based on different approaches, the same input factors are often used: particularly the term, volatility, and dividend yield.

Although deriving the input factors can be challenging, it is possible to tailor the option pricing models to the specific valuation challenge. The problem of data currency does not exist in any of these approaches. Re­cog­nised approaches can be used to determine volatility. Typically, for non-publicly traded companies, volatility is determined using a peer group. It is conceivable to use historical or implied volatilities. Volatility acts as a measure of uncertainty. Higher volatility means that the future price development is more uncertain. In the context of the DLOM, this means that the probability of a price change within the disposal period is higher for companies with higher uncertainty (volatility). The DLOM for these companies is correspondingly higher. The term is also freely selectable in option pricing model-based methods and can be adapted to the valuation object or industry specifics and is not implicitly predetermined based on study data. The term (i.e., the time required for a sale (no fire sale)) is of great importance, as the probability of a price change increases with time. Considering the individual distribution situation provides significant added value, as distributions are a form of partial liquidation and thus reduce the risk for the company owner.

The strengths and weaknesses of the models are intensively discussed in the literature. The individual profile of the models determines the application area. For example, the Chaffe model is based on a European put option. With a European option, the option holder secures the right to sell their share at a predetermined price. This form of option protects the option holder against a declining price, but it can only be exercised at the end of the term. The representation using a European put option technically leads to higher discounts being de­ter­mined for companies with higher distributions. Given the risk reduction through distributions, this result is logically inexplicable. Therefore, the Chaffe model is not suitable for companies with high distributions. In the Longstaff model, DLOMs of >100 per cent can also be determined for longer terms and higher volatilities. These results are also logically inexplicable and thus limit the model’s application area. The Finnerty model, on the other hand, has an upper limit of approxi­ma­​​tely 32 per cent. This means that using this model, DLOMs of > approxi­ma­tely 32 per cent cannot be determined. In practice, this is occasionally seen as an advantage, as the maxi­mum DLOM is in line with the average results of benchmark studies and thus difficult to challenge. How­ever, situations may justify a significantly higher DLOM. The brief explanations show that the model choice depends on the individual case.

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Regardless of the chosen approach (benchmark study or option pricing-based method), it is advisable to consider qualitative factors in the considerations. Important factors are:

Many factors can be implicitly considered in the approaches. In benchmark studies, for example, transactions of comparable companies with similar business activities or shareholder structures can be used. Volatility implicitly reflects the company’s revenue security and should be determined based on companies with com­pa­ra­​ble business activities. The distribution capability, for example, is reflected in the dividend yield as an input factor.

The presentation of different approaches clearly highlights the added value of option pricing-based models due to the higher degree of individualisation and the given data currency. For an overall assessment and plausibility check of the results, a plurality of methods with reference to benchmark studies is still recommended due to the existing weaknesses. The choice of methods depends on the individual case, depending on the valuation object and context. Due to the different strengths and weaknesses, this requires access to extensive financial information and a detailed understanding of the different approaches.

It remains to be seen whether new option pricing-based methods will lead to a gradual improvement of the existing weaknesses in the future and whether the practical relevance of benchmark studies will continue to decline.