Once your organization decides that it’s going to grant performance shares contingent on Relative Total Shareholder Return (“RTSR”), one of the first and most impactful decisions is how you’re going to determine the “target” grant size. Generally, there are three (3) broad methodologies for doing so:
Methodology 1: Share Price – The current share price (with or without a preceding averaging period for smoothing purposes). The great benefit of this methodology is the simplicity, in that it is very easy for a participant to understand the value of the awards they just received. The following example will be used throughout all 3 methodologies.
Example 1: Company ABC wants to grant an executive $1M of value of RTSR performance shares on April 1, 2019, when the 10-day average stock price of Company ABC is $10. The performance shares may earn payouts ranging from 0% – 200% of target, depending on the ultimate TSR ranking compared against peers during the period of 1/1/2019 – 12/31/2022. The participant would receive 100,000 target shares, calculated by simply dividing $1M by $10.
Methodology 2: Accounting Value – The accounting rules (see Accounting for Performance Shares) under ASC 718 require a rigorous calculation of fair value using Monte Carlo simulation, which captures all the of the terms and economic conditions as of the grant date. This value is also required to be disclosed in the Summary Compensation Table of the Proxy, so there is great alignment between what the investors see and what is used for participants.
Example 2: On the accounting grant date of 4/1/2019, a Monte Carlo simulation yields a fair value of $15.00 per target award granted, or 150% of face value. Note that the performance period began on 1/1/2019, and Company ABC has outperformed their peers during the period of 1/1/2019 – 4/1/2019 (the “stub period”), which has been reflected in the fair value. The participant would receive 66,667 shares., calculated by dividing $1M by $15.
Methodology 3: Economic Value – Similar to the accounting value (Methodology 2), the economic value captures all of the terms and conditions of the award; however, it ignores any effect of actual performance during the stub period (January 1 to April 1) that has already been completed. This methodology will also use Monte Carlo simulation.
Example 3: On the accounting grant date of 4/1/2019, a Monte Carlo simulation yields an economic fair value of $13.00 per target award granted, or 130% of face value. Note that the performance period began on 1/1/2019, yet all companies are considered to have the same TSR as of the beginning of the performance period. The participant would receive 76,923 shares, calculated by dividing $1M by $13.
For compensation planning and grant sizing, there are no regulatory or audit rules requiring one methodology or another. Of the three methodologies summarized above, there is no perfect solution, as each has their pros and cons. However, we believe there is some merit in minimizing the difference in fair value between the 3 alternatives, such that the accounting value, economic value, and the stock price are reasonably close to each other (see Design Levers to Reduce the Fair Value of your RTSR Shares).
Methodology | Pros | Cons |
---|---|---|
# 1: Stock Price | • Easiest for participant to understand • Easiest to calculate for regulatory filings | • Least accurate to the actual value of the performance share • Summary Comp Table will not match the value communicated to participants • Depending on the stock price (and presuming it is less than the accounting and economic valuations), it can be more dilutive to shareholders |
# 2: Accounting Value | • Summary Comp Table will match the value communicated to participants | • Complicated for participants to understand • Requires a Monte Carlo simulation on quick turnaround for filing purposes • Has a perverse dynamic where good performance during stub period punishes the participant with fewer shares, while bad performance during stub period is rewarded with more shares • Can be volatile year-over-year depending on stub period performance |
# 3: Economic Value | • Most accurate representation of the fair value of the instrument • Is quite stable as a percentage of stock price year over year | • Complicated for participants to understand • Summary Comp Table will not match the value communicated to participants • Requires a Monte Carlo simulation but can be performed well in advance of the grant date |
Please contact the authors at Infinite Equity if you would like to discuss these alternatives in greater detail.