What's the value of Elon Musk's stock option pay package?
How $3 billion six years ago becomes $50 billion today
Executive Summary: Although accounting requires fair valuation of ESOs at grant date, any option pricing model (e.g., BSM) can give a wide range of outputs. My own ex ante value of Elon’s mega grant would—based on a superficial information set—have been $550 million to $3.3 billion. Due to (i) an audaciously leveraged (↑risk/reward) but fair package and (ii) extraordinary multi-year outperformance, the intrinsic value of the options is now ~ $50 billion. Ex-post $50 B ⊬ ex ante $3 B. The post-trial opinion is well-written but only persuaded me that the court decision to rescind was terrible.
TSLA stock greatly overperformed any reasonable expectation over the period
Employee stock options are dilutive but costing them is tricky
Accounting requires an up-front fair value of an instrument (if ATM) with zero intrinsic value
The performance vesting requirements are superhero hurdles: they greatly reduce the ex ante value of the grant relative to its time-vested equivalent.
Due to these valuation challenges, it’s no surprise that some investors just look at Equity Run Rate and/or Equity Overhang
I get to a similar ex ante outcome with a totally intuitive growth model
Summary
I’ve never owned Tesla shares (TSLA), but I did notice the headlines about Elon Musk’s pay package reportedly worth a whopping ~ $50 billion1. In a former life as a management consultant, I designed incentive pay packages for technology and finance companies, so I was curious about the details behind such a large number. As an investor, stock-based compensation (SBC) fascinates me because most technology investors definitely do understand conceptually that SBC is a significant financial factor—often a source of sizeable dilution—but many institutional investors (and most retail investors) do not know how to incorporate SBC into a valuation framework. It’s not because they aren’t aware that SBC is dilutive. They know. And institutional investors, in my experience, are not lazy2. Rather, as I hope to introduce here, incorporation of SBC into a valuation framework is an inherently tricky, pseduo-circular math problem.
For this post, I will take a quick look at his package. I did take not time (this morning) to read the majority of the many SEC filings related to this package; my analysis is based on three TSLA SEC filings: the 2018 Proxy, the 2018 10K, and the recent 2024 Proxy. There are a lot of filings and documents, maybe I missed something important this morning.
TSLA stock greatly overperformed any reasonable expectation over the period
First, let’s look at the timeline. According to the 2018 Proxy (DEF 14A):
“In January 2018, following more than six months of careful analysis and development led by the Compensation Committee, with participation by every independent Board member and the help of Compensia3, the Board granted the 2018 CEO Performance Award to Mr. Musk, subject to approval by a majority of the total votes of Tesla common stock not owned by Mr. Musk or Kimbal Musk cast at a meeting of the stockholders to approve the 2018 CEO Performance Award. On March 21, 2018, such approval was obtained, with approximately 73% of the votes cast by such disinterested shares voting in favor of the 2018 CEO Performance Award.” — 2018 Def 14A
The 2024 Proxy clarifies that the exercise price of Elon’s grant was the “Fair Market Value (FMV) of Tesla common stock on the grant date of January 21, 2018, which was $350.02 per share of our common stock.” In my ggplot below, the vertical red lines indicate that grant date and the two subsequent stock splits; i.e., 5-for-1 split followed by 3-for-1 split. The splits mean that “to go back in time” we need to use a factor of 5*3 = 15. At the time of grant (Jan 2018):
He was granted 20.3 million FMV (aka, at the money, ATM) options, which splits twice into 20.3 * 3 * 5 = 304.0 million options,
At a strike price of $350.02 per share, which splits twice into $350.02 ÷ 5 ÷ 3 = $23.33 per share.
That’s an incredible run! As of yesterday close, TSLA’s price is $184.86 which implies a +38.1% CAGR. The price is down from $248.42 at the beginning of the year; alternatively, measured from grant date to January 2nd, 2024, the price appreciation was a stunning +48.8% per annum.
If we ignore the performance vesting, the grant’s mechanics are super simple: it is a front-loaded at-the-money (ATM; aka, FMV) grant of non-qualified stock options (NQSOs) with the typical 10 year term4. The unique features of this front-loaded grant include:
It was large (i.e., 12% of total shares outstanding) but restricted by super ambitious, shareholder-friendly performance conditions. We cannot separate the huge reward potential from the epic risk5. Both the size and the performance requirements here are outliers. Quid pro quo. This unique risk/reward dynamic exacerbates a valuation problem that is already non-trivial for vanilla employee stock options (ESOs).
Any ex ante valuation of the package is going to be much lower than the realized (ex post) value of ~$50 billion due to the highly unexpected outperformance shown above. To be specific about the ex post value:
As of yesterday, the (pretax) intrinsic value is ($184.86 - $23.33 strike) * 303,960,630 options = $49.10 billion
As of Jan 2, 2024, the intrinsic value was ($248.42 - $23.33 strike) * 303,960,630 options = $68.42 billion.
In a legal drama that I do not profess to understand, somehow a shareholder plaintiff convinced a Delaware court after a five day trial to agree that the 2018 pay package was unfair to shareholders and should be rescinded. This was decided in January 2024, six years after the grant. In the meantime, Elon Must was paid no compensation. Don’t even get me started6.
Employee stock options are dilutive but costing them is tricky
Most employee stock options (ESOs) vest over time, but Elon’s mega option grant is also performance-based. In fact, it is extremely performance-based. Therefore, I’m going to take two steps. First, I’ll ignore the performance requirement and treat the option “as-if” it were a vanilla option at grant. That will give us a range. Second, I’ll briefly show that the performance requirements necessarily discount the grant’s value; i.e., if the range is plausible for unrestricted (except time) options, the performance requirements can only reduce that range.
But let’s start with the valuation dilemma. ESOs7 are derivatives. Like Elon’s mega option grant, most ESOs are FMV grants (i.e., strike price equal to stock price) with zero intrinsic value at grant. Without going deep, I’ll just assert the following points about this extremely popular “zero intrinsic value” compensation vehicle we call an FMV ESO:
It’s a relatively efficient method of compensation—if not used excessively—because unexercised options will have no direct impact on the company’s cash flow. If the stock tumbles after grant, the options ultimately cost the company nothing. A lot of academic stuff has been written about the theoretical substitution of cash for the option, but this is a risky, illiquid asymmetric compensation component. It’s wonderful to receive option grants, but you can’t pay bills with them for literally years; and most stocks do not go to the moon. There is a very real possibility they will ultimately be worth nothing (especially if the company is not prone to repricing ESOs).
Yet it’s completely untrue that ESOs are free to the company. At grant, they have zero intrinsic value but they do have positive time value. ESOs are definitely dilutive, it’s that their actual dilution is deferred. I’ve read so many different characterizations, including false claims that overstate their cheapness. I think the best way to think about ESOs is that they represent deferred and potential, but likely, dilution. The reason the dilution is likely is that the strike price is fixed, but we reasonably expect the stock price to drift up, say, at the cost of capital. This fixed strike price is the primary reason that executive options are something of a “gift:” they can be worth a lot even if the stock underperforms in relative terms.8
The core math problem is nicely illustrated by Elon’s mega grant. He was granted ATM options with a strike price of $23.33. If the stock had increased only a little bit, actual dilution would be small. For example, if the he stock had eked up only +2.75% per annum, then over six years, that’s 1.0275^6 -1 = +17.6% and options exercised at that point in time would be similar to modestly discounted (ie, -15%) ESPP shares. However, if the stock increases a lot (as it did here), the dilution is much greater. In extremis, imagine an option granted with a strike price of one penny ($0.01). Well, that’s really giving away an entire share. That’s a lot of dilution. This circularity is the valuation problem: the actual realized dilution depends on a future stock price that, in turn—in an efficient market—ought to be reduced by the expected dilution of the grant itself. Notice—careful reader—how this circularity leads us right up the steps to the governance question in the case of Elon Must (or any key executive at a public company): the more important that this person is to the achievement of the highly dilutive scenario (aka, stock price outperformance), the less we care about the high dilution! On the other hand, if the outperformance would have been achieved without him, the high dilution is just a corporate giveaway by existing shareholders.
From the company and shareholder perspective, there is a difference between book accounting, tax accounting and cash flow (aka, economic) impacts. At a minimum, there will be timing differences.
Accounting requires an up-front fair value of an instrument (if ATM) with zero intrinsic value
If we travel back in time to 2018, we can see how Tesla was expensing its other ESOs. I’d like to plug those assumptions into Elon’s grant, “as if” his grant did not have performance requirements (or more accurately, before any discount for performance vesting). My true motive is to show you that it’s all just a twitchy model. Sorry! My grandpa had a Cadillac that seemed to swerve all over the road. His ride was not a tight German car ride. We teased about it, referring to it as his boat. He’d move the steering wheel just a little and, yikes, we’re headed into the curb. Option pricing models are twitchy like that.
Like many others, Tesla uses the Black-Scholes (BSM) option pricing model to estimate the fair value of granted stock options. Here are the assumptions used for the other (non-Elon) employee stock option grants in 2018:
Expensing the options is an accounting requirement. I personally love the principles behind accounting; they enable consistent financial statements that aspire to recognize expenses as they are incurred. However: for the sake of these noble principles, the value of these zero intrinsic value options is determined at the time of grant and never subsequently re-valued. We are saved from unduly volatile income statements, but the price (in this case) is that the initial fair value never gets updated.
In the worksheet below9, I used these assumptions to value Elon’s mega grant. Because my point is to illustrate the model’s sensitivity to volatility and term assumptions, I’ve shown a matrix of those two inputs. For example, I highlighted $9.02 because that’s the BSM’s option value for an option with a 5-year term if the expected volatility, σ, is 40%. This corresponds, in the lower panel, to ~39% of the $23.33 stock (or strike) price. It’s often the case that ESO values are deemed to be about 1/3rd the underlying share’s value; a rough rule-of-thumb is a 1:3 ratio of value of option to restricted share (or RSU). So, this result feels about right. TSLA did assume 42% volatility (a bit higher than 40%) and 4.7 years (a bit lower than 5.0 years), but those assumptions imply an option value of $9.09.
Again, if I use their contemporaneous assumptions (σ = 42% and T = 4.7 years), I get $9.09 per option. If I round to the displayed σ = 40% and T = 5.0 years, I get a nearby $9.02. You may notice their “$121.92 Grant date fair value per share” is equal to $121.92/15 = $8.13 in today’s terms. The difference between my $9.09 and their $8.13 is mostly due different grant dates.
The above matrix is why I’ll never obsess with fine precision in the case of ESO valuation. We are able justify a wide range of grant date values, as you can see. The green region reflect my personal, highly subjective view that a credible range—in this scenario—would have been 31% to 62%. About this analysis, I’d like to say the following things:
If we time travel back to 2018 when the grants were made, we can ask ourselves: what’s a reasonable estimate of their fair value at grant? It’s way easier to answer “as if” they were typical FMV option grants restricted only by time but not performance. Then we can debate discounts or workarounds to reduce their value per additional performance restrictions. If I were to convince you that the fair value at grant was $2.742 billion before restrictions, then what effect do performance restrictions have? In this case (more below), they serve to reduce the value because they represent the very real possibility (or probability) that some fraction of these 303.9 million options will never vest. It’s hardly the only way to think about incorporating performance vesting, but it’s the easiest: if 300 million options are granted that would otherwise vest over time, performance restrictions are tantamount to an expectation that p*300 MMoptions will eventually vest (where p*300 < 300 and p is the probability-weighted expected percentage of the grant that will vest).
Even in this easy first step, it’s ridiculous to pretend that zero intrinsic value derivative are worthy of a single point estimate! If we time travelled back to 2018 and you asked me for the unadjusted BSM option value, my answer might have been: the unrestricted grant might have a fair value of $2.7 billion but the honest (aka, highly confident) range is something like $2.2 billion to $4.4 billion.
Why is my model so twitchy? Look at the matrix. The correct volatility is the expected volatility. Even after estimating it, we should contend with issues related to the very long horizon that is a bit unnatural to the model; e.g., are the returns really i.i.d.? Sure, 60% is really high volatility input but consider that 60% volatility, in this case, would have still massively underestimated the ultimately realized value of the option grant. Just saying. What about the option term assumption? Ah, here is where the “BSM for ESO” exercise crumbles like a stale oatmeal cookie.
The ESOs do actually have a 10-year term so that is the correct input into a BSM option pricing model if these were European style options. But these are American style options that are, further, restricted by time vesting and also not especially liquid. Consequently, the widely accepted practice is to use the expected life of the option (4.7 years, in TSLA’s case). As John Hull writes about this practice, “It should be emphasized that using the Black-Scholes-Merton formula in this way has no theoretical validity.”10 If you are just learning this here, I’m sorry to inform you that the BSM model isn’t even the correct model for this job.
What’s really going on? Lowering the expected life is the easiest way to reduce the option expense but the actual justification for a reduction are the unrelated—at least model-wise—vesting restrictions and illiquidity. The kludges are compounding in a confusing way, so let me recap: The BSM is meant for European options (under restrictive assumptions). The ESOs are American style, which itself makes them more valuable ceteris paribus. But that’s outweighed by their illiquidity and vesting restrictions, which greatly reduce the option’s value. To approximate that reduction, we use an expected life instead of the option’s actual term.
If you want to debate the assumptions and the model, I respect you. Maybe you’d like to switch out BSM for binomial or an advanced BSM variant (solve one problem, create another). On the other hand, if you want to ignore the model because you realize the recognized expense doesn’t help you understand the actual dilution threat, which is a range that probably contains some circularity, I also respect you. We’re just playing with a model, and if you want me to get a higher or lower value, I can do it. However, the precision and elegance does not mean that I’ve yet given you any great insight into the actual dilutive impact of the grant. I love the BSM a lot, I really do. But, if I were analyzing the package as an investor, most of this so far would be, um what’s the word, unhelpful to me.
The performance vesting requirements are superhero hurdles: they greatly reduce the ex ante value of the grant relative to its time-vested equivalent.
So far I’ve argued that my own at-grant fair value using Tesla’s own assumptions into a kludgy BSM option pricing model would have ranged from $2.2 billion to $4.4 billion where the in-between $2.7 billion is a direct match to their two key assumptions (volatility and expected life). However, that pretends these were typical time-vested options. To say these options attached with performance restrictions is an comical understatement.
TSLA’s market cap at the time of grant was ~ $59 billion. The 20.3 million options vest in 12 tranches; each trance vests an additional 20.3/12 = 1.7 million options. The first tranche (of options on 1.7 million shares) required increasing the market cap to $100 billion. Each additional tranche required another +$50 billion added to market cap. The final tranche requires reaching $100 + (50*11) = $650 billion in market cap. Importantly, these market cap milestones are not flimsy (aka, instantaneous) triggers: each milestone ($100 B, $150 B, $200 B, …) must be the function of both 30-day and six-month trailing averages11.
Further, there are 16 “operational milestones”: eight escalating revenue and eight escalating EBITDA thresholds that ought to be achieved, if the market cap targets are reached, because they were derived as reasonable multiples.
To me—if I lazily continue to implement the kludge (i.e., BSM option pricing model) approach in order to attempt an ex ante valuation—the easiest (but probably not best) way to handle this is to make an assumption about the reasonable fraction of the grant that could have been expected to vest.
In the exhibit below, I modify the previous exhibit (first deleting the second panel that represented the values as a percentage of share price) by adding three “Expected to vest” assumptions: 25%, 50%, and 75%. So, if we mirror TSLA’s own BSM input assumptions (that valued the options at $9.02) we’d get discounted values of $690 million (if 25% vest), $1.37 billion (if 50% vest) and $2.06 billion (if 75% vest). The within-green reasonable range becomes $550 million (if 25% are expected to vest under a conservation assumption of {σ = 30%, T = 5 years}) to $3.32 billion (if 75% are expected to vest under a less conservation assumption of {σ = 50%, T = 10 years}).
Ergo, my best, quick guess of the confident range I would have given back then (i.e., the ex ante number) is $550 million to $3.3 billion. It’s a wide range, but ranges are more honest than point estimates. Please note: Here is the key piece of information that I do not have (but would have obtained if I were the consultant at the time). At the time of grant, which of the early tranches were likely (aka, probable) to vest? It would have been critical to ascertain how many tranches, if any, were effectively going to vest eventually over time.
Additional “Post-Exercise Holding Period”: if you think a 75%/50%/25% discount for the high performance hurdles is too much, I’d mention that these options have an additional and unusual illiquidity feature. Musk is required to hold the shares for five years after exercise.
Due to these valuation challenges, it’s no surprise that some investors just look at Equity Run Rate and/or Equity Overhang
I’m sorry not sorry to walk you through an exercise which, alas, does not inform an investor’s view on dilution. We need to understand models before we insult them. I haven’t even discussed the accounting and cash flow implications of these (or any) option grants, but hopefully you can see why many investors simply resort to side glancing the run-rate and equity overhang implied by the grant.
Run-rate refers to the equity incentive grants as a percentage of shares outstanding. For example, maybe a tech company grants options on 2% to 4% of shares outstanding per year. Compensation consultants routine benchmark this number. The analytical challenge is that an performance-vested option is less dilutive than a time-vested option is less dilutive than a restricted share (or restricted share unit). Whereas run-rate is a flow measure (e.g., 3% granted during fiscal 2023), equity incentive overhang is its stock equivalent: at the end of the fiscal year, what is the potential (including outstanding options) that might be granted going forward?
This mega grant was sized, by design, as 12.0% of the total shares outstanding: 2.53 billion shares outstanding * 12% = 304 million options. That is a humongous number but:
It clearly was a front-loaded grant that was next-in-sequence to cover a period of 5+ years. If we assume 6 years, then the annualized run-rate is ~2% per year. Still a large number for one person, but actually not out of bounds for an executive tech team.
The performance hurdles were, and are, so high that they probably defy comparison. Apparently the compensation consultant did not perform benchmarking. Benchmarking executive compensation is the first job of the comp consultant. It’s a stunning omission. The only two reasons I can think of for not doing it are: they weren’t given the time, or because these performance hurdles are as unique as Elon Musk is once-in-a-generation. (Actually, here’s a third reason: maybe they figured that any benchmarking would show this package was an outlier. The reason I’m not convinced by that political motive, you can see, is that I’m not confident this grant was unreasonable on a risk-adjusted basis).
How did Tesla actually (ex ante) value these grants
They used Monte Carlo simulation. I know because the post-trial opinion—which riveting and well-written—explains in a passage that makes me smile:
On December 22, [the consultant] provided a valuation letter based on the December 13 Term Sheet. [The consultant] used Monte Carlo simulations to estimate the probability of hitting the market capitalization milestones, which is a “generally accepted statistical technique” that “simulate[s] a range of possible future” outcomes over a given timeframe using constantly repeating, random potential scenarios.”
[He] determined that the first market capitalization goal—described as $100 billion, or $50 billion of growth—would occur 45.55% of the time, after which the likelihood of achieving subsequent milestones rapidly declined to below 10% from milestone six onward. The Monte Carlo valuation did not account for the probability of hitting the operational milestones, nor did it incorporate Tesla’s internal projections.
Based on these estimates, [he] reached an initial grant date fair value for the 2018 Grant of $2,656,430,639. He then applied a 10.52% illiquidity discount based on the Five-Year Hold Period, arriving at a final value of $2,377,077,626.398. [His team] continued to refine this valuation in the following weeks by tweaking assumptions, including the holding period and dilution rate.”
I’m smiling because I wonder how many customers (aka, Committee members) fully understood the simulation output and model’s fragility. Even as I adore Monte Carlo: it’s really the only way to do it right, in my opinion. After discounts, this number is probably not too far from where I would have gotten. As I wrote at the top, it’s the nature of the derivative beast that we don’t have a simple way.
I get to a similar outcome with a totally intuitive growth model
Still, a far more intuitive approach to ex ante valuation is a simple growth model. Below is another exhibit. Over various horizons, I’ve assume a range of reasonable per annum stock price growth targets, {8%, 9%, 10%, 11%, 12%}. The table’s interior cells contain the present value (PV) of a grant if the stock grows at the Price CAGR and the resultant future intrinsic value is discounted back at 5.0%. For example, I happen to think 11.0% CAGR is a reasonable target growth rate if sustained over 7.5 years. In that scenario, $23.33 grows to $23.33*1.11^7.5 = $51.04. The future intrinsic value, therefore, is $27.71 which discounts to $27.71/1.05^7.5 = $19.22. That implies a grant PV of $19.22 * 303.4 MM options = $5.841 billion. If 50% is a reasonable vesting expectation, then $5.841 * 50% = $2.92 billion. We find ourselves back in the same neighborhood!
Summary
Geez, I meant this to be a quick analysis (on a holiday morning) and I’ve already written too much. I hope I’ve achieved two things. First, I hope I’ve shown why ex ante valuation of this performance-based ESO package is very tricky with a wide range of plausible values. Second, I hope I’ve answered the question at the top:
How does $3 billion six years ago become $50 billion today?
My answer: the package was very high risk/reward, but ex ante grant values should be based on expected and/or target outcomes. You do not calibrate the award size by assuming super-heroic outperformance. You’ve got to analytically parse (i) the potential high payout implied by extraordinary outperformance from (i) the calibration of the award size under an assumption of expected performance.
As my naïve growth model illustrates, the company can award a grant with a fair value of ~ $3 billion because it’s reasonable—if not stretch—to expect +11% price appreciation over a 7.5-year period, and yet extraordinary outperformance renders the realized value to be ~$50 billion. Because you didn’t expect +38% or +48%, obviously. Six or seven years is both a long discounting window and a shareholder-friendly horizon.
At first glance, ARK’s open-source model looks like fine artisanship https://github.com/ARKInvest/ARK-Invest-Tesla-Valuation-Model
It is interesting that the Proxy says (emphasis mine) “We used Compensia …to help us develop the 2018 CEO Performance Award and understand how our executive compensation compares to that of our competitors” but they apparently did not benchmark the package. I don’t know anybody at Compensia but I used to work for one of the consultancies who was also considered (“FW Cook, Pearl Meyer, Semler Brossy, and Radford”). As I’ve written many times, the best in the business (and best boss I’ve ever had) is Robin Ferracone at Farient Advisors. She’d be perfect for this because the situation is political with Musk’s influence over the Board and you need somebody in the role with total integrity who can also withstand pressure. The consultant wants the business and everybody wants to make Elon happy. In my opinion, there are very few people with the people (and technical) skills to navigate this situation. Personally I would not be able to do it, I’d get pushed around and I get starry-eyed.
The majority of ESOs are granted with 10-year terms, but among those that are exercised, the majority are exercised much sooner and they are exercised in a cashless exercise. For example: say Mary was granted 1,000 NQSOs that strike at $30.00 and the stock is now $38.00, such that she’s sitting on ($38 - 30)*1,000 = +$8,000 profit; aka, intrinsic value. The liquidity problem is that exercise requires $30,000 plus taxes; she’s taxed on the $30,000 gain at ordinary income rates. With the broker’s help, a cashless exercise enables the immediate use of the shares to cover to cover; aka, sell-to-cover. In this case, if we assume the combined tax rate is 35.0%, she needs $30,000 (to buy the shares) plus $2,800 (35% taxes on the gain), or $32,800. Rather than pay cash and own 1,000 shares, she immediately sells $32,800 ÷ $38.00 ≈ 864 shares to cover the exercise. Without using any cash, she holds 1,000 - 864 = 136 shares after the cashless exercise; this is value of 136 * $38.00 = $5,168.00, which is the same as her after-tax gain, as given by ($38.00 - 30.00) * 1,000 * (1 - 35%).
In case the inseparability of risk/reward is not obvious, here is an illustration. Say the fair value of ATM options given {S = $23.33, K = $23.33, T = 7 years, σ = 30%, Rf = 4%, q = 0%} is $9.54. If you want to grant a target value of $100,000 to an executive, then you grant $100,000 ÷ 9.54 = 10,487 options. Now change the strike price to K = 23.33 * 1.06^7 = $35.09; i.e., the same options switch to OTM with a higher strike price indexed at +6% per annum over the term. The BSM per option value drops (from $9.54) to $6.19. If you still want to grant a target value of $100,000 you need to grant $100,000 ÷ 6.19 = 16,147 options; i.e., you need to increase the size of the grant by 54%. The OTM options are riskier than the ATM options: you cannot maintain the grant size and pretend the value at-target is the same. The design risk, especially if they use Monte Carlo simulation, is to use outperformance scenarios to inform target value grants.
Well, just one thing about the ruling. As I mentioned, the post-trial opinion is riveting and it’s really well-written. I could not stop reading it!
However, it only served to persuade me that that the court’s decision was terrible. Even before the contents of the agreement: the court rescinded an agreement reached in a defensible process by typical actors (e.g., Board, Committee, Consultant) within the legal bounds of their right to do so.
Among the arguments made include this nugget: “Why did Tesla have to ‘give’ anything in these circumstances? Musk owned 21.9% of Tesla at the time of the Grant.841 If the goals were retention, engagement, and alignment, then Musk’s pre-existing equity stake provided a powerful incentive for Musk to stay and grow Tesla’s market capitalization .” Am I missing something because I feel like I’ve taken crazy pills when I read this. They appear to be saying that because Musk pre-owned 21.9%, he maybe doesn’t need to be paid anything from 2018 to 2024. We appreciate you being a maniacal workaholic and thank you for the current free work. Um, no, I’m not aware of a universe where that logic applies. The pre-owned 21.9% is largely irrelevant to the go-forward package because he keeps it, if he stops. He can quit and then you’d have to renegotiate the new package, right? Nevermind the whole thing is an embarrassing attempt to retroactively undo an agreement made in good faith.
True, the process was not perfect, but I want to make one more note about the process: there was plenty of time for major players to step in and exert influence for almost six months, if they wanted to exert more influence. By 2017 “Tesla was already nearing completion of the 2012 Grant milestones”. The “first mention of what would become the 2018 Grant” occurred on 2017 and “Little progress was made on Musk’s new compensation plan through May 2017”. “The Board first discussed the prospect of a new compensation plan for Musk during a June 6, 2017 Board meeting”. Initially, the timeline was “reckless”: On June 23rd, the Committee discussed the plan for the first time, “[a]lthough the committee had no idea what the terms of the plan might be, they were told to be prepared to approve it in July. Brown thought the timeline was unwise.” By late June the broad contours of the play were on the table, by my read of the transcript. But then the process decelerated and “slowed to a halt” from August to September. More meetings and a “surge of activity” into December.
ESO refers to employee stock options including executive stock options. Elon’s 2018 mega grant ESOs were non-qualified stock options (NQSOs or NSOs) as opposed to the less common—but tax better—incentive stock options (ISOs)
The problem of the gift of a fixed strike price is why Warren Buffett and others, at various points, have argued for indexed stock options. For example, the strike price increases over time by its cost of equity. This would, in theory, eliminate windfall gains to executives due to price appreciation due to beta (or even just time passage via the risk free rate). This gets to a key weakness of stock options: a company’s stock can go up due to several factors that have little do to with the company. A company can benefit, or be penalized, from market/sector/industry association for longer than we’d expect. When I consulted to Amazon a long time ago, indexed options were considered. But, for reasons beyond my scope, they invariable run into multiple practical implementation issues.
Message me if you want the Excel. BTW, I’m super excited that I used Excel’s LAMBDA function for the first time! The LAMBDA function made it easy for me to enter the BSM formula into a single draggable cell because I self-defined d1 and d2; e.g., NORM.S.DIST(d1_($L$10,$L$11,$O$11,$O$10,$K17,N$14),TRUE)
Hull, John. OFOD 11th Edition.
It is very easy to gloss over this feature but it makes the milestone more robust. A stock like TLSA can spike or drop fast. Market capitalization, of course, is the function of a volatile stock price. Myself, I think I would have thought to propose the 30-day trailing average, but not the the 6-month trailing average that is decisively shareholder-friendly.