2 Reasons Multiday Averages Make Sense for Grant Sizing

When granting equity awards, close to 90% of companies use a value-based approach to determine grant sizes [1]. Rather than starting with a number of shares, they first determine the amount of value they want to deliver to employees. This helps companies evaluate and size equity awards in the context of employees’ overall compensation (e.g., employees might receive equity awards equal to 20% of base salary).

Ultimately, however, grants must be expressed as a number of shares. Thus, companies that use this approach must decide on a per share value that will be divided into the aggregate value to determine the total shares granted. Currently, over 70% of companies use a spot price—i.e., the FMV on or around the date of grant—for this purpose[1]. I think this is a mistake. I’d like to see more companies use a multiday average price to determine grant sizes.

What Is a Multiday Average?

A multiday average is just that: rather than use the FMV from a single date, you would average the FMVs for a specified period (e.g., 30 days) and use the average value to determine grant sizes.

Reason #1: It’s More Equitable

Using a multiday average evens out grant sizes, which helps ensure that employees aren't unfairly penalized because they have the bad luck to be granted an award when the price is high and also don’t receive a windfall because they have the good luck to be granted an award when the price is low. The recent volatility in the stock market provides a great example of how helpful this can be.

For my example, I’ve created a fictitious company that trades at 1/100th the value of the S&P 500. (I’m using 1/100th of the S&P price because the S&P trades at around $3,000 per share and that high of a value makes the example clunky. The aggregate values would work out the same regardless of the per share price. Also, I’m rounding to the nearest dollar because decimals are confusing and distracting in examples. Otherwise, this is a historically accurate example.)

Let’s assume that my fictitious company is granting RSUs to two employees, both of whom are relatively equal in terms of rank, tenure, and performance. Each employee is to receive an RSU worth $10,000. Employee A’s RSU is granted on February 20, when the stock price is $34 per share. Employee B’s RSU is granted one month later, on March 20, when the stock price has dropped to $23 per share.

I did not pick these days by chance. February 20 is the day before the market started to slide and March 20 is just a couple of days before the market hit its low point for the year. This example mirrors what many companies have experienced with their stock prices from February 20 through today.

If we use the FMV on the grant date to determine the number of shares in each grant, employee A will receive a grant for 294 shares ($10,000 divided by $34 per share) and employee B receives a grant for 434 shares ($10,000 divided by $23 per share). Employee B’s grant is almost 1.5 times the size of employee A’s grant. Not because employee B deserves more shares but merely because employee B’s grant was timed fortuitously.

As of yesterday, our fictitious company’s stock had fully recovered, to $34 per share.  At this price, Employee A’s grant is worth about $10,000 (slightly lower because of rounding). Employee B’s grant, however, is worth $14,756. Over the long term, Employee B could end up realizing significantly more compensation from his/her RSU than Employee A. This would be fine if it is our intention, but this isn’t the case—we intended them both to receive grants that were relatively equal in value.

Using even just a 30-day average would have smoothed out the differences between the two grants considerably.  The 30-day average for Employee A’s grant is $33 per share. The S&P 500 was fairly stable for the 30 days leading up to February 20, so the 30-day average doesn’t have a big impact on Employee A’s grant. It would be for 303 shares instead of 294 shares.

But using a 30-day average has a significant impact on Employee B’s grant. The 30-day average on March 20 is $30. This reduces the size of Employee B’s grant to 333 shares, which is more comparable to the grant that Employee A received just a month before.  The current value of both grants is also more comparable. At yesterday’s stock price of $34 per share, the value of employee A’s grant is worth a little over $10,000 and Employee B’s grant is worth a little over $11,000. From a compensation standpoint, this seems like a better result than using the spot price on the date of grant to determine the grant size.

Reason #2: Share Usage Is More Predictable

As demonstrated in my example, using spot prices to determine grant sizes results in a large variation in grant sizes. Wildly different sized grants make it harder to forecast share usage and, when the company’s stock price declines, it can cause the company to burn through its plan reserve faster than expected.

When the company in my example uses a spot price to size the grants to employees A and B, it uses up significantly more shares than it was planning to. But when the 30-day average price is used, the company’s share usage aligns with about what it was planning on at the start of the year.

The Cons

Using a multiday average introduces complexities beyond having to calculate the average FMV. The expense recorded for accounting purposes will differ from the value communicated to employees. In my example, the expense for Employee A’s grant will be $10,302 (303 shares multiplied by the $34 grant date FMV) and the expense for Employee B’s grant will be $7,659 (333 shares multiplied by the $23 grant date FMV). But unless the employees are executives (or work in finance or accounting), there’s no reason for them to know the expense recorded for their grants.

For named executive officers, the grant value reported in the Summary Compensation Table and Grants of Plan-Based Awards Table is tied to the value of the grant for accounting purposes. Thus, this reported value will also differ from the value communicated to these executives.

While these considerations should not be underestimated, I think the advantages in terms of fairness to employees and forecasting outweigh the disadvantages. 

1 Data source: 2019 NASPP/Deloitte Consulting Stock Plan Design Survey