Volatility is one of the most important parameters in the valuation of share-based payment programs under IFRS 2. As a measure of share price fluctuation, it significantly influences - along with other factors such as term, risk-free interest rate, and exercise price - the value of stock options and similar instruments. This article demonstrates the practical significance of volatility determination and its impact on company valuation.
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Volatility describes the intensity of price fluctuations of a security within a specific period. As a statistical measure, it is typically expressed as the standard deviation of logarithmic returns and usually annualized on a yearly basis. The higher the volatility, the more the price fluctuates around its mean value.
Volatility plays a central role in the valuation of options and other derivative financial instruments. A fundamental understanding of this parameter is essential, as increasing volatility also increases the value of an option. This is because stronger price fluctuations increase the probability that the option will be "in the money" during its term.
The mathematical representation of volatility is given by the formula:
where σ represents volatility, ri represents individual returns, and rˉ represents the average return.
The significance of volatility extends far beyond mere numerical calculation. It is an essential indicator of investment risk and directly influences the price formation of options and option-like instruments.
While the basic calculation of volatility appears relatively straightforward, its specific determination in the context of IFRS 2 presents companies with particular challenges.
IFRS 2 "Share-based Payment" sets specific requirements for determining volatility. The standard requires consideration of expected volatility over the entire option term. This does not mean mechanically extrapolating historical volatility; rather, a forward-looking estimate must be made.
According to IFRS 2.B25, several factors must be considered when estimating expected volatility:
The standard places special emphasis on the use of historical volatility. This should cover a period corresponding to the expected option term. However, it should be noted that the more recent past is generally more meaningful for the future than periods further back.
The standard acknowledges that determining volatility for non-listed companies presents a particular challenge. In such cases, the company must estimate expected volatility considering all available information, particularly by using the volatilities of comparable listed companies.
The determination of volatility for share-based payments can be done through three different approaches, which are used depending on the availability of market data and whether the company is listed.
Implied Volatility from Market Prices
Implied volatility is derived from current market prices of traded options. This forward-looking method reflects market expectations and considers current developments. It is considered particularly meaningful as it aggregates the assessments of all market participants and is based on actual transactions.
Historical Volatility for Listed Companies
For listed companies, historical volatility can be calculated from past share price fluctuations. The standard deviation of logarithmic returns is determined over a period that ideally corresponds to the expected option term. This method offers the advantage of an objective data basis but must be critically questioned regarding its future relevance.
Peer Group Analysis for Non-listed Companies
For non-listed companies, volatility estimation is performed using comparable listed companies (peer group). This involves using companies of similar size, business model, and industry affiliation. The determined average volatility of the peer group serves as an approximation, though company-specific adjustments may be necessary to account for particularities of the company being valued.
The valuation of share-based payments requires a systematic approach that considers both theoretical foundations and practical circumstances. A central aspect is the selection of the appropriate valuation date.
The initial volatility estimation occurs at the grant date and should generally be maintained in subsequent periods, even if actual volatility develops differently.
The quality of volatility estimation significantly depends on the availability and reliability of input data. While established listed companies usually have sufficient data available, valuation becomes considerably more complex for young companies or during volatile market phases. This requires careful consideration between different data sources and time periods.
Another critical point is the consideration of extraordinary events: company acquisitions, restructurings, or significant changes in the business model can distort historical volatility and limit its predictive power for the future. In such cases, adjusted valuation approaches are necessary to appropriately account for these special effects.
The choice of the observation period also presents a particular challenge. On one hand, the period should be long enough to ensure statistical significance. On the other hand, it should be short enough to reflect the current market situation.
Practice shows that a compromise must be found between these conflicting requirements, which should be oriented towards the expected option term.
The valuation of share-based payments requires the use of appropriate option pricing models, which vary depending on the complexity and design of the programs. Three models, each with specific advantages and disadvantages, have become particularly established in practice:
Black-Scholes Formula
The Black-Scholes formula is the standard model for valuing simple stock options under IFRS 2. It is particularly suitable for plain vanilla options with European-style exercise. The model is based on the assumption of a lognormal distribution of stock prices and considers, in addition to volatility, the risk-free interest rate, dividend yield, and the remaining term of the option.
Binomial Model
For more complex compensation programs with special exercise conditions or vesting periods, the binomial model is used. It offers more flexibility than the Black-Scholes formula as it can model various scenarios of price development. The model divides the term into discrete time intervals and models possible upward and downward movements of the stock price at each point in time.
Monte Carlo Simulation
For index-linked compensation or compensation tied to relative performance targets, Monte Carlo simulation is the method of choice. This method simulates thousands of possible price developments and considers:
The choice of the appropriate option pricing model depends significantly on the complexity of the compensation program and the specific exercise conditions. While simple programs can be efficiently valued using the Black-Scholes formula, more complex structures require more sophisticated models such as the binomial model or Monte Carlo simulation.
The practical implementation of volatility valuation under IFRS 2 presents companies with various challenges that require careful consideration:
Missing Market Data for Start-ups
For young, non-listed companies, determining volatility is particularly challenging. The lack of price history and often innovative business model make it difficult to identify comparable companies. Additionally, rapid growth and changing business models can limit the significance of historical data from peer group companies. In such cases, a combination of different valuation approaches is required, considering both industry-specific and company-specific factors.
Complexity of Valuation Models
The increasing complexity of modern compensation programs places high demands on valuation models. Performance conditions, market conditions, and various exercise hurdles must be precisely modeled. The parameterization of the models requires solid mathematical knowledge and a deep understanding of the underlying assumptions. Particularly with Monte Carlo simulation, even small changes in input parameters can lead to significant valuation differences.
Documentation Requirements for Auditors
The chosen valuation approaches must be documented in a transparent and audit-proof manner. This includes:
Mastering these challenges requires a systematic approach and the implementation of robust processes that ensure consistent and traceable valuation.
IFRS 2 sets extensive requirements for the valuation and documentation of share-based payment programs. The standard setters place particular emphasis on transparent and traceable determination of volatilities, as these have a significant impact on valuation results.
Requirements for Volatility Determination
The regulations of IFRS 2 require a forward-looking estimate of expected volatility over the entire option term. Both historical data and forward-looking information must be considered. The standard explicitly requires documentation of the methodology used and the assumptions made.
Audit-Relevant Aspects
For auditors, several aspects are in focus when examining volatility determination. The chosen valuation methodology must be coherently justified and consistently applied. Special attention is paid to the traceability of volatility calculation and the appropriateness of the data basis used. Auditors also ensure the correct allocation of volatilities to the respective cash generating units.
Disclosure Requirements
Detailed information about the volatilities used must be provided in the notes to the IFRS financial statements. These include:
Compliance with these regulatory requirements is not only important from a compliance perspective but also contributes to the comparability and transparency of financial reporting.
The challenges in determining volatility under IFRS 2 can be efficiently managed with a specialized software solution like Valuation Pro. The platform offers a comprehensive approach for the professional valuation of share-based payments.
Current Volatility Data at the Push of a Button
Valuation Pro enables direct access to an extensive pool of current volatility data. The database provides high-quality capital market data and is characterized by its large data scope. Auditors and accounting experts can quickly and efficiently determine the required volatilities.
Standardized Valuation Models
The software integrates all relevant valuation models - from the Black-Scholes formula to the binomial model and Monte Carlo simulation. The standardized procedures ensure consistent and traceable valuation that meets IFRS 2 requirements. The platform's intuitive usability enables professional valuation even for less experienced users.
Audit-Proof Documentation
A particular advantage lies in the automated, audit-proof documentation. The software creates complete valuation documentation that transparently demonstrates all relevant parameters, assumptions, and calculation steps. This not only meets the documentation requirements for auditors but also facilitates communication with stakeholders and supervisory authorities.
The solution is specifically tailored to the needs of auditors, tax consultants, and accounting managers, and significantly simplifies the complex process of volatility valuation.
We support you in researching the data — e.g. putting together the peer group — with a short training session on how to use the platform. We are happy to do this based on your specific project.
