Restricted stock awards and RSUs continue to grow in popularity. To both achieve deductibility under Code Section 162(m) and avoid the stigma of “pay for pulse,” many companies cause these awards to vest based on performance criteria. I recently spotted an interesting article by a couple of PhD.s http://www.grgeta.com/edi/GT_SFEA2011.pdf on a methodology they call: “self-funded equity awards” (SFEA). SFEA is a way for companies to structure their restricted stock awards so that they are explicitly linked to performance metrics only, while containing an implicit link to stock performance. CFOs generally prefer that because they can reverse the accounting expense incurred if the awards do not eventually vest. Permit me to quote at length from the article.
The fundamental theory behind performance-based long-term incentive awards is that they are “cost neutral” to shareholders, such that the awards will only pay out if shareholders receive a commensurate return. However, few companies empirically test this theory when selecting performance metrics. Grant Thornton’s compensation and benefits consultants and financial economists have developed a quantitative tool, the Self-Funding Equity Awards (SFEA) methodology. This tool can empirically relate future values of a company’s financial and operational metrics such as EPS, EBITDA or ROE to future expected stock performance. With that knowledge, grant designers can create vesting schedules for equity awards that depend entirely on financial and operational metrics but also have an indirect relationship to stock performance. Such awards are designed to be “self-funding” because the payout to management is indirectly linked to shareholder gains. Unlike awards directly linked to stock price performance, these awards qualify as performance shares for financial reporting purposes. Since stock price movements are not directly attributed to manager actions, utilizing a performance-based ward results in compensation more directly tied to management action.
I am not smart enough (or good enough at math) to know whether this actually works, but it sounds like an intriguing concept.