VALUATION OF CONTINGENT CONSIDERATION

1. INTRODUCTION TO CONTINGENT CONSIDERATION

Company A intends to acquire Company B. Company B has just introduced a new product line that is expected to generate significant sales. Company B’s owners have projected a significant amount of sales from the proposed product line and are considering the same to influence the deal size. Company A, on the other hand, believes that there is a risk of uncertainty in the achievement of targets contemplated by the seller and hence there is a disagreement on the deal valuation. By incorporating a contingent consideration clause in the purchase agreement, the seller accepts part of the business risk along with the buyer and also participates in any upside post-transaction.

Contingent consideration may be contingent on different events, for example, on the launch of a product, on receiving regulatory approval, or reaching a certain revenue or income milestone. The achievement of such events often spans over more than a year. Thus, it is necessary to understand the acquisition date as well as the post-acquisition treatment of such contingent consideration.

2. CLASSIFICATION AND MEASUREMENT OF CONTINGENT CONSIDERATION

Figure 2.1.1: Classification of contingent consideration

Example: A fixed monetary amount to be settled in a variable number of shares would be classified as a liability.

Contingent consideration classified as a liability is required to be re-measured at its fair value at each reporting period. For example, a consideration depending on revenue achieved over the next three years from acquisition will need to be fair-valued at the end of each year / quarter. Whereas, a consideration classified as equity is not required to be fair-valued post the initial recognition since the consideration has already been determined and locked as at the acquisition date.

3. VALUATION OF CONTINGENT CONSIDERATION / EARN-OUTS

Mostly, contingent consideration is paid on achievement of certain revenue or profit targets. Additionally, such payments may be spread over more than just one year. The pay-outs can either be linear pay-outs or non-linear pay-outs.

3.1 Linear pay-outs
Pay-outs which are dependent on a single metric and are expressed in terms of a fixed percentage or the product of a financial or some non-financial parameters, are referred to as linear pay-outs. Considerations that vary based on different levels of revenue or other parameters are non-linear pay-outs. For example:

Target will receive a payment at some future date as follows:

•  If EBIT < $1 million, the payoff is zero;

•  If EBIT = $1 million, the payoff is a 10x multiple of EBIT.

The valuation method will be driven by the structure of the contingent consideration pay-outs. There are two broad valuation approaches used to value a contingent consideration.
i) Probably weighted expected return method, more commonly referred to as ‘PWERM’, or scenario-based method (‘SBM’); and
ii) Option pricing method, also referred to as the ‘OPM’.

3.1.1 Probably weighted expected return method (PWERM)
The PWERM assesses the distribution of the underlying matrices based on estimates of the forecasts, scenarios and probabilities. The pay-out computed is then discounted to present value using a discount rate corresponding to the risk inherent in the inputs considered while computing the compensation. The following are the steps followed:
i) Estimate scenarios of outcomes and associated probabilities.
ii) Compute the expected payoffs using the scenario probabilities.
iii) Discount expected payoffs to present value using risk-adjusted discount rates.

Illustration 3.1.1.1

• INR 100 crores payment contingent upon obtaining FDA approval.
• Approval expected in one year.

Solution:

Advantages:
i)    Management controls scenarios and probabilities: The scenarios and probabilities are generally prepared by the management because they would be the best source for such data points.
ii)    Understandable: The computation and the flow are understandable to a reader with basic financial knowledge.
iii)    Flexible: The model can be structured to fit most pay-out scenarios.

Disadvantages:
i)    Management controls scenarios and probabilities: While this has been discussed under advantages, management control over these inputs is also counter-intuitive since management tends to be overly optimistic or pessimistic in its assumptions.
ii)    Lots of subjective assumptions: Most of the methods / inputs are subjective and involve judgement, which at times is not the most ideal approach to value such pay-outs.
iii)    Discount rate: Since the methods involve multiple scenarios, it is challenging to estimate the appropriate discount rate.
iv)    Path dependencies: Pay-out scenarios which are path dependent, i.e., the result of one scenario is related to one or more dependent scenarios, are difficult to model in the PWERM. It can lead to multiple nodes and is prone to errors.

3.2 Non-linear pay-outs
Non-linear contingent considerations are either not strictly linear, or they pay a fixed amount based on a milestone correlated with the broader economy; thus, they require an OPM as their complexity and discounting cannot be adequately captured in a PWERM; for example, if the buyer pays INR 50 crores if EBITDA is at least INR 75 crores in the first three years, or if the buyer pays 40% of revenues above INR 50 crores in year two, subject to a maximum of INR 40 crores. Another, more complicated, example: The buyer pays 40% of revenues in years one to three, subject to a minimum of INR 10 crores and a cap of INR 40 crores. In such an arrangement, a PWERM will not work since it’s impossible to adjust the discount rate to align with the risk of such a complex pay-out structure. An option-pricing model is generally used to value such arrangements.

3.2.1 Option-pricing methods
The payoff structures for contingent consideration arrangements that have a non-linear structure are similar to those of options in that payments are triggered when certain thresholds are met. Accordingly, some option-pricing methods may be appropriate for valuing contingent consideration that have a non-linear payoff structure and are based on metrics that are financial in nature (or, more generally, for which the underlying risk is systematic or non-diversifiable). The OPM is implemented by modelling the underlying metrics based on a log-normal distribution that requires two parameters:

* The expected value: The management expectation of the matrices over the term of the arrangement. This is generally provided by the management.

* The volatility (standard deviation) of the metric: The volatility of the metric measures the potential variability from the expected value. This is generally determined by using market-based data. However, volatility for financial metrics like revenue and EBITDA cannot simply be computed using the movement in stock prices of the comparable companies. It needs to be appropriately levered and unlevered to capture the variability in achievement of the metrics.

There are two widely used option-pricing methods, viz., the Black-Scholes Model (‘BSM’) and the Monte Carlo simulation model.

3.2.1.1 Option-pricing method – Black-Scholes Model
BSM treats a pay-out arrangement just like an ordinary option which enables use of the standardised Black Scholes – Merton formula. This approach can work for simpler pay-out structures, for example, if the selling shareholder earns the pay-out only if the target metric hits a threshold, or for linear pay-outs with caps or floors. The consideration is assumed to represent a call option on the future performance of the seller.

Illustration for BSM
Earn-outs are contingent upon the target of achieving a benchmark EBIT of INR 11,25,000 within three years. The EBIT is currently INR 10,00,000. At the end, the acquirer will pay additional consideration equal to the excess EBIT over the benchmark.

The discount rate is 10% and the risk-free rate is 3%. Volatility of earnings is 14% based on historical EBIT.

The inputs to the Black-Scholes Model for this example are:

i)    The current INR 10,00,000 level of earnings is the value of the underlying,
ii)    the benchmark of INR 11,25,000 serves as the exercise price,
iii)    the term is three years,
iv)    the volatility is 14%,
v)    the risk-free rate is 3%, and
vi)    the dividend rate is 0%.

Based on the above inputs, calculations for the Black-Scholes Model can be incorporated into an Excel spreadsheet. The resulting call option value of INR 84,413 will be the value of the contingent consideration.

3.2.1.2 Option-pricing method – Monte Carlo Simulation Model
For more complex structures, a Monte Carlo simulation is preferred. Arrangements that pay over multiple periods or multiple metrics are subject to combined caps or a floor. A Monte Carlo simulation considers the correlation between matrices and pay-outs over multiple periods. The Monte Carlo simulation repeats a process many times attempting to predict all the possible future outcomes. At the end of the simulation, several random trials produce a distribution of outcomes that can be analysed. Random numbers are used to measure possible outcomes and the likelihood of their occurrence. Generally, simulation software are used to generate random numbers. These random numbers are generated based on the applicable distribution driven by the metric triggering the pay-outs.

The following are the important considerations of key inputs for valuing contingent considerations using an option-pricing model:

Discount rate applied based on risk of target metric
For earn-outs that require this kind of discount rate, either the top-down or bottom-up approach may be used to develop the rate. These approaches are well known in the valuation field. They rely on the concept of beta (ß), which reflects the level of market risk reflected in an instrument.

In the top-down approach, ß is based on the deal’s rate of return adjusted for the difference in market risk between the target metric and the overall enterprise value. Adjustments can reflect many relevant factors, such as the general risk in the target metric, leverage, term, size premium and entity-specific risk. In the bottom-up approach, ß is the target metric adjusted for term, size, entity-specific risk and other relevant valuation factors. The bottom-up approach may rely on statistical analysis of the target metric from the entity or its peers.

Volatility
Valuation techniques that rely on options modelling or Monte Carlo simulation require a volatility of the target metric. There are four ways in which such volatility can be computed:

i)    Historical changes in the target metric for the acquired entity and public comparable companies,
ii)    Entity volatility based on the relationship between the target metric and the enterprise value,
iii)    The difference between analyst forecasts and actual results for peer companies, and
iv)    Fitting a distribution to management’s estimates.

With any of these methods, a discussion with management is recommended since a derived volatility may fail to accurately incorporate the economics of the entity’s situation.

Both option-pricing models can get complex and difficult to comprehend for a lot of professionals and they have their share of advantages and disadvantages.

Advantages:
i)    Manage complex payoff structures: Can accommodate a wide range of complex payoff structures.
ii)    Objective assumptions: Most inputs are governed by market-related inputs making it less subjective than the PWERM.
iii)    Discount rate: Since the computations are made using random numbers and volatility, generally risk-adjusted discount rates are used, reducing the need of subjectivity inherent in building discount rates for financial matrices.

Disadvantages:

Valuation of contingent consideration and selection of the appropriate methods for doing so can be quite challenging. Such valuations are continuously evolving as new literature on methods and approaches is published around the world. The selection of methods to value these arrangements is driven by the complexity of the pay-outs and the experience and the qualifications of the valuer to be able to appropriately apply these methods.

The complexity of contingent consideration is not limited to its valuation but has several accounting and taxation implications which need to be considered and analysed. The accounting and tax aspects vary, based on the accounting standard being followed as well as the structure of the transactions. A discussion on these aspects would warrant an independent article, which we intend to cover over the next few issues.