Triggered Disclosures: Escaping the Disclosure Dilemma

In a post a few weeks ago, I argued that the disclosure process had lost its moorings, as corporate disclosures (annual filings, prospectuses for IPOs) have become more bulky, while also become less informative. I argued that some of this disclosure complexity could be attributed to the law of unintended consequences, with good intentions driving bad disclosure rules, and that some of it is deliberate, as companies use disclosures to confuse and confound, rather than to inform. For those of you who agreed with my thesis, the end game looks depressing, as new interest groups push for even more disclosures on their preferred fronts, with the strongest pressure coming from the environmental, social and governance (ESG) contingent. In this post, I propose one way out of the disclosure dilemma, albeit one with little chance of being adopted by the SEC or any other regulatory group, where you can have your cake (more disclosure on relevant items) and eat it too (without drowning in disclosure). 

The Disclosure Dilemma: Disease and Diagnosis

    For those of you who did not read my first post on disclosures, let me summarize its key points. The first is that company disclosures have become more bulky over time, whether it be in the form on required filings (like annual reports or 10K/10Q filings in the US) or prospectuses for initial public offerings.  The second is that these disclosures have become less readable and more difficult to navigate, partly because they are so bulky, and partly because disclosures with big consequences are mingled with disclosure with small or even no consequences, often leaving it up to investors to determine which ones matter. The net effect is that investors feel more confused now, when investing in companies, than ever before, even though the push towards more disclosures has ostensibly been for their benefit.

    As we look at the explosion of disclosures around the world, there are many obvious culprits. The first is that technology has made it possible to collect more granular data, and on more dimensions of business, than ever before in history, and to report that data. The second is that interest groups have become much more savvy about lobbying regulatory groups and accounting rule writers to get their required data items on the required list. The third is that companies have learned that converting disclosures into data dumps has the perverse effect of making it less likely that they will held accountable, rather than more. That said, there are three other reasons for the disclosure bloat: 

• The first is the prevailing orthodoxy in disclosure is tilted towards "one size fits all", where all companies are covered by disclosure requirements, even if they are only tangentially exposed. Though that practice is defended as fair and even handed, it is adding to the bloat, since disclosures that are useful for assessing some firms will be required even for firms where they have little informative value. 
• The second is the notion of materiality, a key component of how accountants and regulators think about what needs to be disclosed.  Using the words of IFRS (1.7), ‘Information is material if omitting, misstating or obscuring it could reasonably be expected to influence decisions that the primary users of general purpose financial statements make on the basis of those financial statements, which provide financial information about a specific reporting entity’. As we will argue in the next section, this definition of materiality may be leading to too much disclosure for backward looking items and too little for forward looking items.
• The third is that the disclosure rule writers happen to be in the disclosure business, and since more disclosure is good for business, the conflict of interest will always tilt toward more rather than less disclosure. No matter how many complaints you hear from accountants and data services about disclosure bloat, it has been undeniable that it has created more work for accountants, appraisers and others in the disclosure ecosystem.

It is quite clear, though, that unless we break this cycle, where each corporate shortcoming or market upheaval is followed by a fresh round of new disclosures, we are destined to make this disclosure problem worse. In fact, there may come a point where only computers can read disclosures, because they are so voluminous and complicated, perhaps opening the door for artificial intelligence or matching learning into investing, but for all the wrong reasons.

Escaping the Disclosure Trap

    There is a way out of this disclosure trap, but it will require a rethink of the status quo in disclosures. It starts first by moving away from "one size fits all" disclosure rules to disclosures tailored to companies, a "triggered" disclosure process, where a company's value story (big market, lots of subscribers) triggers disclosures on the parameters of that story. It extends into materiality, by reframing that concept in terms of value, rather than profits, and connecting it to disclosure, with disclosure requirements increasing proportionately with the value effect. Finally, it requires creating a separation between those who write the disclosure rules and those who make money from the disclosure business.

One size (does not) fit all!

When disclosure laws were first written in the aftermath of the great depression, they were focused on the publicly traded firms of the time, a mix of utilities, manufacturing and retail firms. At the time, the view that disclosure requirements should be general, and apply to all companies, was rooted in the idea of fairness. In the decades since, there have been exceptions to this general rule, but they have been narrowly carved out for segments of firms. For instance, oil companies are required to disclose their ownership of "proven undeveloped reserves", in addition to details about quantity, new investments and progress made during the year in converting those reserves. The disclosure rules for banks and insurance companies require them to reveal the credit standing of their loan portfolios and their regulatory capital levels to investors and the public. These exceptions notwithstanding, disclosure laws written to cover concerns in one sector (such as the use of management options at technology firm or lease commitments at retail and restaurant companies) have been applied broadly to all companies. It is time to rethink this principle and allow for a more variegated disclosure policy, with some disclosures required only fir subsets of companies. Since the next big bout of disclosures that are coming down the pike will be related to ESG, this discussion will play out in a wide range of ESG data items. For instance, while it makes sense to require that fossil fuel and airline companies report on their carbon footprints and greenhouse gas emissions, it may just be a time consuming and wasteful exercise to require it of technology companies.

From earnings-based to value-based materiality

I do not think that you will find many who disagree with the premise that any information that has a material effect should be disclosed, but there is disagreement on what comprises materiality. I believe that the "materiality principle", as defined by accountants, is diluted by measuring it in terms of impact on net income and the fact that accountants tend to be naturally conservative in measuring that impact. Simply put, it is safer for an accounting or audit firm to assume that a disclosure is material, and include it in reports, even if it turns out to be immaterial, than it is to assume that it is immaterial, and be found wrong subsequently.  One solution to this problem is to redefine materiality in terms of effects on value, rather than earnings, thus accomplishing two objectives. First, it will reduce the number of noise disclosures, i.e., those that pass the materiality threshold for earnings, but don't have a significant impact on value. Second, since value is driven by expected cash flows in the future and not in the past, it will shift the focus on disclosures to items that will have an impact on future earnings and cash flows, rather than on past earnings or book value.

Triggered Disclosures

At first sight, the requirements to make disclosures slimmer and more informative may seem at war with each other, since disclosure bloat has largely come from well-intentioned attempts to make companies reveal more about themselves. Triggered disclosures, where disclosures are tailored to a company's make-up and stories, are one solution, where contentions made by a company trigger additional disclosures related to that contention. Thus, a company that claims that brand name is its supreme competitive advantage would then have to provide information to not only back up that claim, but also to allow others to value that brand name. 

Disclosure Illustration: Initial Public Offerings

    

It is difficult to grapple with disclosure questions in the abstract, and to illustrate how my proposed solutions will play out in practice, I will focus on initial public offerings, where there is a sense that the disclosure rules are not having their desired effect. In my last post, I noted that prospectuses, the primary disclosure documents for a companies going public, have bulked up, contrasting the Microsoft and Apple prospectuses that came in at less than a 100 pages in the 1980s to the 400+ page prospectuses that we have seen with Airbnb and Doordash in more recent years. At the same time, applying a disclosure template largely designed for mature public companies to young companies, often with big losses and unformed business models, has resulted in prospectuses that are focused in large parts on details that are of little consequence to value, while ignoring the details that matter.  Since companies going public often do so on the basis of stories that they tell about their futures, and these stories vary widely across companies, this segment lends itself well to the triggered disclosure approach. To do so, I will draw on a paper that I co-wrote with Dan McCarthy and Maxime Cohen, to provide details. In that paper, we argue that a going-public company that wants to build its story around certain dimensions (a large total addressable market or a large user base) will trigger disclosure of a more systematic, business type-specific, collection of “base disclosures” that are required to understand the economics of businesses of that type, whatever type that might be.

Total Addressable Market (TAM)

Companies going public have increasingly supported high valuations by pointing to market potential, using large TAMs as one of the justifications. These TAMs are often not only aspirational, but also come with very little justification and no timeline for how long it will take for the existing market sizes to grow into those TAMs. For instance, the graph below shows the TAMs that Uber and Airbnb claimed in their prospectuses at the time of their initial public offerings.

Uber and Airbnb Prospectuses

Is Uber’s total addressable market really $5.2 trillion? I don’t think so, but you can see why the company was tempted to go with that inflated number to push a “big market” narrative. To prevent the misuse of TAM as little more than a marketing ploy, companies that specify a TAM should also have to provide the following:

a. TAM, SAM and bridges: Companies that specify a TAM should also specify the existing market size (i.e., the serviceable addressable market or SAM), as well as additional “bridges” so that investors can understand the evolution from SAM to TAM (e.g., an estimate of how many individuals would be interested in the company’s product before considering price). Investors who may be skeptical of a lofty TAM could still look to SAM as a more achievable intermediate metric.

b. Market share estimates: As long as companies do not have to twin TAM with expectations of market share, there is little incentive for them to restrain themselves when estimating TAM. We would recommend requiring that companies that disclose TAM figures couple them with forecasts of their market share of those TAM figures. For companies that are tempted to significantly inflate their TAMs, the worry that they will be held accountable if their revenues do not measure up to their promises, will act as a check.

c. Ongoing metrics or measures: Companies usually provide TAM, SAM, and variants thereof on a one-shot basis, disclosing these figures in their pre-IPO prospectuses and then never again. We believe that investors should be given these measures on an ongoing basis. This will help on two levels. First, it will allow investors to see how well the company is adhering to its prior disclosures and forecasts and provide investors with updates if conditions have changed. Second, companies that know they will be held accountable to their IPO disclosures after they go public will be more incentivized to make those disclosures realistic and achievable. 

To the extent that investors will continue to assess premiums for companies that have bigger markets, the bias on the part of companies will still be to overestimate TAM. That said, these recommendations should help rein in some of those biases.

Subscription-Based Companies

A subscription-based company derives its value from a combination of its subscriber base (and additions to it) and the subscription fees its charges these subscribers.  Consequently, the value of an existing subscriber can be written as the present value of the expected marginal profit (subscription fee net of the costs of servicing that subscription) from the subscription each year, over the expected life of the subscriber (based upon renewal/churn rates in subscribers), and the value of a new subscriber will be driven all of the same factors, net of the cost of acquiring that subscriber. The overall value of the company can be written in terms of its existing and new subscribers:

Companies that sell a “subscriber” story have the obligation, then, to provide the information needed to derive this value:

1. Existing subscriber count: Observing the total number of subscribers in each period (e.g., month or quarter) allows us to track overall growth trends in the number of subscribers, and to understand how revenue per subscriber evolves over time, because revenue is disclosed.
2. Subscriber churn: To value a subscriber, a key input is the renewal rate or its converse, the churn rate. Holding all else constant, a subscription business with a higher renewal rate should have more valuable subscribers than one with a lower renewal rate. It would stand to reason that any subscription-based company should report this number, but it is striking just how many do not disclose these measures or disclose them opaquely. For example, while the telecom industry regularly discloses churn figures, Netflix has not disclosed its churn rate in recent years. 
3. Contribution profitability: For subscribers to be valuable, they need to generate incremental profits, and to estimate these profits, you need to know not just the subscription fees that they pay, but also the cost of servicing a subscription; the net figure (subscription fee minus cost of service) is called the contribution margin. Many subscription companies explicitly disclose contribution profits (e.g., Blue Apron, HelloFresh, and Rent the Runway), but many others do not (e.g., StitchFix). In the absence of explicit contribution profit data, investors often resort to simple proxies for it, such as gross profit, but these proxies are imperfect and noisy.
4. Subscriber acquisitions & drop offs: To move from the value of a single subscriber to the value of the entire subscriber base, we must also know how many subscribers are acquired over time, not just the net subscriber count. Put differently, if a company grew the overall size of its subscriber base from 10 million to 12 million subscribers in a year, it is quite different if that net growth came about because the company acquired 10 million customers that year but then lost 8 million of them, versus if the company acquired 2 million customers and lost none of them. Acquisition (or equivalently, churn) disclosures are what allow us to piece this apart.
5. Cost of acquiring subscribers (CAC): Subscription-based companies attract new subscribers by offering special deals or discounts, or through paid advertising. While the cost of acquiring subscribers can sometimes be backed out of other disclosures at subscription-based companies (such as subscribers numbers, churn and marketing costs), it would make sense to require that it be explicitly estimated and reported by the company.
6. Cohort data: While many subscriber companies are quick to report total numbers, only a provide a breakdown of subscribers, based upon subscription age. This breakdown, called a cohort table, can be informative to observe retention and/or monetization patterns across cohorts, as noted by Fader and McCarthy in their 2020 paper on the topic. Many subscription-based firms, including Slack, Dropbox, and Atlassian, now disclose cohort data, and the figure below shows one such chart for Slack Technologies:

   

   Source: Slack Technologies Form S1

By breaking down cohort-specific retention and monetization trends, a cohort chart offers investors visibility into retention and development patterns as a function of subscriber tenure (e.g., does the retention rate get better or worse as subscribers get older), and trends across time, as subscribers stay on the platform. 

Transaction-Based Companies

The guiding principles driving our disclosure recommendations for subscription-based businesses largely extend to transaction-based businesses, with the primary difference being that subscription revenues are replaced with transaction revenues, a number that is not only more difficult to estimate, but one that can vary more widely across customers. The value of the customer base at transaction-based businesses is driven off the activity of these customers, translating into transaction revenues and profits. 

As with subscriber-based businesses, this framework can only be used if the company provides sufficient data from which one can estimate the inputs. Deconstructing this picture, many of the key disclosures track those listed for subscription based companies, including contribution profitability, customer acquisition costs and cohort data. In addition, there are three key additional pieces of information that can be useful in valuing these companies:

1. Active customer count: We replace the notion of a subscriber with that of an “active” customer, which is more suitable for transaction-based businesses. After all, a customer in your platform who never transacts is not affecting value, and one issue that transaction-based companies have struggled with is defining "activity". Wayfair, Amazon, and Airbnb, for example, define an active customer to be one who has placed at least one order over the past 12 months. In contrast, Lyft, Overstock, and many other companies define a customer as active if they placed an order in the past 3 months. 
2. Total orders: In transaction-based companies, the average purchase frequency of active customers can change, often significantly, over time. We need to know the total orders because this further allows us to decompose changes in revenue per active customer into changes in order frequency per active customer and changes in average order value. While some transaction-based businesses disclose this information, including Wayfair, Overstock, Airbnb, and Lyft, this data is notably absent for many others, such as Amazon.
3. Promotional activity: It can be easy to significantly increase purchase activity through enticing targeted promotions, creating the illusion of rapid growth that may not be sustainable over the long run, due to their substantial cost. Since these promotions are often reported as revenue reductions, rather than expenses, the cost of these campaigns are often opaque, to investors. For example, DoorDash did not disclose their total promotional expense during the most recent 6 months in their IPO prospectus, creating substantial uncertainty for investors as to how this may have influenced gross food sales). 

Fintech Companies

In the last decade, we have seen banks, insurance companies and investment firms face disruption from firms in the "fin-tech" space, covering a diverse array of companies in the space. With all of these companies, though, there is (or should be) a lingering concern that part of their value proposition comes from "regulatory arbitrage", i.e., that these disruptions can operate as financial service companies, without the regulatory overlay that constrains these companies, at least in their nascent years. Since this regulatory arbitrage is a mirage, that will be exposed and closed as these fin-tech companies scale up, investors in these companies need more information on:

• Quality/Risk metrics on operating activity: In the aftermath of the 2008 crisis, banks, insurance companies and investment banks have all seen their disclosure requirements increase, but ironically, the young, technology-based companies that have entered this space seem to have escaped this scrutiny. In fact, the absence of a regulatory overlay at these companies makes this oversight even more dangerous, since an online lender that uses a growing loan base as its basis for a higher valuation, but does not report on the default risk in that loan base, is a problem waiting to blow up. It is highly informative for investors to observe the evolution of these measures in the years and quarters leading up to the IPO. Indeed, lenders can be tempted to strategically lower their credit standards to issue more loans (and hence significantly increase revenue through loan-related fees, which are often assessed upfront) to create the illusion of growth at the expense of long-term profitability and trust (since many of these risky loans are likely to default in the future).
• Capital Buffer: It is worth remembering that banks existed prior to the Basel accords, and that the more prudent and long-standing ones learned early on that they needed to set aside a capital buffer to cover unexpected loan losses or other financial shortfalls. In the last century, regulators have replaced these voluntary capital set asides, at banks and insurance companies, with regulatory capital needs, tied (sometimes imperfectly) to the risk in their business portfolios. Many fintech companies have been able to avoid that regulatory burden, largely because they are too small for regulatory concern, but since they are not immune from shocks, they too should be building capital buffers and reporting on the magnitude of these buffers to investors. 

Conclusion

As data becomes easier to collect and access, the demands for data disclosure from different interest groups will only increase over time, as investors, regulators, environmentalists and others continue to add to the list of items that they want disclosed. That will make already bulky disclosures even bulkier, and in our view, less informative. There are three ways to have your cake and eat it too. The first is to allow for increasing customization of disclosure requirements to the firms in question, since requiring all firms to report everything not only results in disclosures becoming data dumps, but also in the obscuring of the disclosures that truly matter. The second is to shift the materiality definition from impact on earnings to impact on value, thus moving the focus from the past to the future. Finally, tying disclosures to a company's characteristics and value stories will limit those stories and create more accountability.

YouTube Video

Papers

1. Going to Pieces: Valuing Users, Subscribers and Customers
2. Initial Public Offerings: Dealing with the Disclosure Dilemma (with Dan McCarthy and Maxime Cohen)

Blog Posts

1. User and Subscriber Businesses: The Good, the Bad and the Ugly!
2. Disclosure Dilemma: When more (data) leads to less (information)

Disclosure Dilemma: When more (data) leads to less (information)!

In the last few decades, as disclosure requirements for publicly traded firms have increased, annual reports and regulatory filings have become heftier. Some of this surge can be attributed to companies becoming more complex and geographically diversified, but much of it can be traced to increased disclosure requirements from accounting rule writers and market regulators. Driven by the belief that more disclosure is always better for investors, each market meltdown and corporate scandal has given rise to new reporting additions. In this post, I look at trends in corporate reporting and filings over time, and why well-meaning attempts to help investors have had the perverse effect of leaving them more confused and lost than ever before.

Time Trends in Reporting

   Publicly traded firms have always had to report their results to their shareholders, but over time, the requirements on what they need to report, and how accessible those reports are to the public (including non-shareholders) has shifted. Until the early 1900s, reporting by public companies was meager, varied widely across firms, and depended largely on the whims of managers, with smaller, closely held firms among the most secretive. Between 1897 and 1905, for instance, Westinghouse Electric & Manufacturing neither published an annual report, not held a shareholder meeting. In the years before the First World War, the demands for more disclosure came from critics of big business, concerned about their market power, but few companies responded. It took the Great Depression for the New York Stock Exchange to wake up to the need for improved and standardized disclosure requirements, and for the government to create a regulatory body, the Securities and Exchange Commission (SEC). The SEC was created by the Securities Act of 1933, which was characterized as "an act to provide full and fair disclosure of the character of the securities sold in interstate and foreign commerce", and augmented by the Securities Exchange Act of 1934, covering secondary trading of securities. Almost in parallel, accounting as a profession found its footing and worked on creating rules that would apply to reporting, at least at publicly traded companies, with GAAP (Generally Accepted Accounting Principles) making its appearance in 1933. In the years since, disclosure requirements have changed and expanded, with companies in foreign markets creating their own rules in IFRS (International Financial Reporting Standards), with many commonalities and a few differences from GAAP. To get a measure of how disclosures have changed over time, I will focus on two filings that companies have been required to make with the SEC for decades. The first is the 10-K, an annual filing that all publicly traded companies have to make, in the United States. The second is the S-1, a prospectus that private companies planning to go public have to file, as a prelude to offering shares to public market investors.

The 10-K (Annual Filing)

    The Securities Exchange Act of 1934 initiated the rule that companies of a certain size and number of shareholders have to file company information with the SEC both annually and quarterly. The threshold levels of company size and shareholder count have changed over time (it currently stands at $10 million in  assets and 2000 shareholders), as have the information requirements for the filing. In the early years, the SEC summarized the company filings in reports to Congress, but the general public and investors had little access to the filings, relying instead on annual reports from the companies, for their information. It was the SEC's institution of an electronic filing system (EDGAR) in 1994 that has made both annual (10-K) and quarterly (10-Q) filings easily and more freely accessible to investors, leveling the playing field.

    I valued my first company in 1981, using an annual report as the basis for financial data, but my usage of 10-Ks did not begin until the 1990s. I have always struggled with both the language and the length of these filings, but I must confess that these struggles have become worse over time. Put simply, there is less and less that I find useful in a 10-K filing, and more verbiage that seems more intended to confuse rather than inform. Let me start with how this filing has evolved at one company, Coca Cola, between 1994 and 2020, using the most simplistic metric that I can think of, i.e., the number of pages in the filing:

Coca Cola Investor Relations

This is clearly anecdotal evidence, and may reflect company-specific factors, but there is evidence to indicate that Coca Cola is not alone in bulking up its SEC filings. In a research paper focused almost entirely on how 10-K disclosures have evolved over time, Dyers, Lang and Stice-Lawrence count not just the words in 10-K filings (one advantage of having electronic filings is that this gets easier), but also what they term redundant, boilerplate and sticky words (see descriptions below chart):

Dyers, Lang and Stice-Lawrence

Redundant words: Number of words in sentence repeated verbatim in other portions of report

Boilerplate words: Words in sentences with 4-word phrases used in at least 75% of all firms' 10Ks

Sticky words: Words in sentences with 8-word phrase used in prior year's 10K

While this paper goes only through 2013, a more updated study suggests that the word count has continued to climb in recent years:

Lesmy, Muchnik & Mugerman

Both studies referenced to above also point to another troubling trend in the 10-K filings, which is that they have become less readable over time. Lesmy, Muchnik and Mugerman use two popular measures of readability, the Gunning-Fog Index and the Flesch-Kincaid readability test on 10-Ks, and find that not only are 10-Ks much less readable than most texts (they use the Corpus of Contemporary English or COCA Academic texts) and the newspapers (they use the financial and general section of The Daily Telegraph, a UK paper), but that the gap is also getting wider:

Lesmy, Muchnik & Mugerman

To be honest, I think that the authors are being charitable in their assessment of 10-Ks, by linking their reading to higher education. The complexity in the filings does not come from using bigger words or advanced language, but from using a mix of legalese, double-talk and buzzwords to leave readers, no matter how educated they are, in a complete fog. Why have 10-Ks become longer and less readable? Dyers, Lang and Stice-Lawrence make a creative attempt to answer this question, by first breaking down the filing information into thirteen topic categories and graphing how 

Dyers, Lang and Stice-Lawrence

After placing the lion’s share of the blame for bloat on the SEC and rule writers,  Dyers et al, also note three topics account not just for much of the verbosity, but also the redundancy, stickiness and lack of readability: risk factors, internal control and fair value/impairment. 

Dyers, Lang and Stice-Lawrence

While the risk factor section may provide employment for lawyers, internal control for auditors and fair value/impairment for accountants, I have always found these sections to be, for the most part, useless, as an investor. The risk factors are legalese that state the obvious, the internal controls section (a special thanks to Sarbanes-Oxley for this add-on) is a self-assessment of management that they are "in control", and the fair value/impairment by accountants happens too late to be helpful to investors; by the time accountants get around to impairing or fairly valuing assets, the rest of the world has moved on. 

The S-1 (Prospectus)

The S-1 is a prospectus filing that companies that plan to go public in the US have to make, and it plays multiple roles, a recording of the company’s financial history, a descriptor of its business models and risks and a planner for its offerings and proceeds. As with the 10-K, the requirements for the prospectus go back to the Securities Exchange Act of 1934, but the disclosure requirements have become more expansive over time. To provide a measure of how much the S-1 has bulked up over time, consider the table below, where I compare the number of pages in the prospectus filings of two high profile companies from each decade, from the 1980s to today:

SEC Filings

Consider two high profile offerings from the 1980s, Apple and Microsoft, and contrast them with the filings from IPOs in more recent years. Apple’s prospectus from 1980 was considered long, running 73 pages, and Microsoft’s prospectus in 1986 was 69 pages long, with the appendices containing the financials. In contrast, Uber’s prospectus in 2019 was 285 pages long, with a separate section of 94 pages for the financial statements and other disclosures, itself an increase on the Facebook prospectus from 2012, which was 150 pages, with 36 pages added on for financial statements and other add-ons. Along the way, prospectuses have become more complex and less readable, and there are three forces that have caused these changes. 

• The first is that the added verbiage on key inputs has made them more difficult to understand, rather than provide clarity. Consider, for instance, the disclosure requirements for share count, which have not changed substantially since the 1980s, but share structures have become more complex at companies, creating more confusion about shares outstanding. Airbnb, in its final prospectus, before its initial public offering asserted that there would 47.36 million class A and 490.89 million class B shares, after its offering, but then added that this share count excluded not only 30.87 million options on class A shares and 13.79 million options on class B shares, but also 37.51 million restricted stock units, subject to service and vesting requirements. While this is technically "disclosure", note that the key question of why restricted stock units are being ignored in share count is unanswered.
• The second is that companies have used the SEC's restrictions on making projections to their advantage, to tell big stories about value, while holding back details. For some companies, a key metric that is emphasized is the total addressable market (TAM), a critical number in determining value, but one that can be stretched to mean whatever you want it to, with little accountability built in. In 2019, Uber claimed that its TAM was $5.2 trillion, counting in all car sales and mass transit in that number, and Airbnb contended that its TAM was $3.4 trillion, five times larger than the entire hotel market's revenues in that year.
• Finally, while most companies, that are on the verge of going public, lose money and burn through cash, they have found creative ways of recomputing or adjusting earnings to make it look like they are making money. Thus, adding back stock-based compensation, capitalizing expenses that are designed to generate growth (like customer acquisition costs) and treating operating expenses as one-time or extraordinary, when they are neither, have become accepted practice.

In sum, prospectuses like 10-Ks have become bigger, more complex and less readable over time, and as with 10-Ks, investors find themselves more adrift than ever before, when trying to price initial public offerings.

The Investor Perspective

As companies disclose more and more, investors should be becoming more informed and valuing/pricing companies should be getting easier, right? In my view, the answer is no, and I think that investors are being hurt by the relentless urge to add more disclosures. I am not the first, nor will I be the last one, arguing that the disclosure demon is out of control, but many of the arguments are framed in terms of the disclosure costs exceeding benefits, but these arguments cede the high ground to disclosure advocates, by accepting their premise that more disclosure is always good for investors and markets. On the contrary, I believe that the push for more disclosure is hurting investors and creating perverse consequences, for many reasons:

1. Information Overload: Is more disclosure always better than less? There are some who believe so, arguing that you always have the option of ignoring the disclosures that you don't want to use, and focusing on the disclosures that you do. Not surprisingly, their views on disclosure tend to be expansive, since as long as someone, somewhere, can find a use for disclosed data, it should be. The research accumulating on information overload suggests that they wrong, and that more data can lead to less rational and reasoned decision for three reasons. First, the human mind is easily distracted and as filings get longer and more rambling, it is easy to lose sight of the mission on hand and get lost on tangents. Second, as disclosures mount up on multiple dimensions, it is worth remembering that not all details matter equally. Put simply, sifting though the details that matter from the many data points that do not becomes more difficult, when you have 250 pages in a 10-K or S-1 filing. Third, behavioral research indicates that as people are inundated with more data, their minds often shut down and they revert back to "mental short cuts", simplistic decision making tools that throw out much or all of the data designed to help them on that decision. Is it any surprise that potential investors in an IPO price it based upon a user count or the size of the total accessible markets, choosing to ignore the tens of pages spent describing the risk profile or business structures of a company? 
2. Feedback loop: As companies are increasingly required to disclose details about corporate governance and environmental practices in their filings, some of them have decided to use this as an excuse for adopting unfair rules and practices, and then disclosing them, operating on the precept that sins, once confessed, are forgiven.. This trend has been particularly true in corporate governance, where we have seen a surge in companies with shares with different voting rights and captive boards, since the advent of rules mandating corporate governance disclosure. For a particularly egregious example of overreach, with full disclosure, take a look at WeWork's prospectus and especially the rules that it explicitly laid out for CEO succession.
3. Cater to your audience: Company disclose data to multiple groups, to governments to meet regulatory requirements and for taxes, to consumers about the goods and services they they sell, to their bankers about loan obligations due and to shareholders about their overeat financial performance. Rule writers on disclosure sometimes seem to forget that each of these groups need different information, and trying to meet all their needs in one disclosure is a disservice to all of them.  It is worth remembering that the reason that we have 10-Ks and S-1s at companies is for shareholders, interested in investing in the company, not regulators, consumers, accountants or lawyers. That said, it is also worth remembering that not everyone investing in a  company is an investor and that many are traders. Drawing on a contrast that I have used many times before, investors are interested in the value of a stock, which, in turn, is determined by cash flows, growth and risk, and buying stocks that they believe trade at a price less than the value. Traders, on the other hand, have little interested in fundamentals, focusing  instead on mood and momentum, and how those forces can lead to prices increase.
   
   Much of the regulatory disclosure has been focused on what investors need to value companies, albeit often with an accounting bias. However, there are for more traders than investors in the market, and their information needs are often simpler and more basic than investors. Put simply, they want metrics that are uniformly estimated across companies and can be used in pricing, whether it be on revenues or earnings. With young companies, they may even prefer to use user or subscriber counts over any numbers on the financial statements. 
4. Make it about the future, not just the past: While I don't think that anyone would dispute the contention that investing is always about the future, not the past, the regulatory disclosure rules in the US and elsewhere seem to ignore it. In fact, much of regulatory rule making is about forcing companies to reveal what has happened in their past, and while I would not take issue with that, I do take issue with the restrictions that disclosure laws put on forecasting the future. With the prospectus, for instance, I find it odd that companies are tightly constrained on what they can say about their future, but that they can wax eloquently about what has happened in the past. Given that much or all of the value of these companies comes from their future growth, what is the harm in allowing companies to be more explicit about their beliefs for the future? Is it possible that they will exaggerate their strengths and minimize their weaknesses? Of course, but investors know that already and can make their own corrections to these forecasts. More importantly, stopping companies from making these forecasts does not block others (analysts, market experts, sales people), often less scrupulous and less informed than the companies, from making their own forecasts.
5. Mission Confusion: Should disclosures be primarily directed at informing investors or protecting them? While it is easy to argue that you should do both, regulators have to decide which mission takes primacy, and from my perspective, it looks like protection is often given the lead position. Not surprisingly, it follows that disclosures become risk averse and lawyerly, and that companies follow templates that are designed to keep them on the straight and narrow, rather than ones that are more creative and focused on telling their business stories to investors.

Disclosure Fixes

The nature of dysfunctional processes is that they create vested interests that benefit from the dysfunction, and the disclosure process is no exception. I am under no illusions that what I am suggesting as guiding principles on disclosure will be quickly dismissed by the rule writers, but I am okay with that. 

1. Less is more: I do think that most regulators and investors are aware that we are well past the point of diminishing returns on more disclosure, and that disclosures need slimming down. That is easier said than done, since it is far more difficult to pull back disclosure requirements than it is to add them. There are three suggestions that I would make, though there will be interest groups that will push back on each one. First, the risk profile, internal control and fair value/impairment sections need to be drastically reduced, and one way to prune is to ask investors (not accountants or lawyers) whether they find these disclosures useful. A more objective test of the value to investors of these disclosures is to look at the market price reaction to them, and if there is none, to assume that investors are not helped. (If you apply that test on goodwill impairment, you would not only save dozens of pages in disclosures, but also millions of dollars that are wasted every year on this absolutely useless exercise) Second, I would use a rule that has stood me in good stead, when trying to keep my clothes from overflowing my limited closet space, in the disclosure space. When a new disclosure is added, an old one of equivalent length has to be eliminated, which of course will set up a contest between competing needs, but that is healthy. Third, any disclosures that draw disproportionately on boilerplate language (risk sections are notorious for this) need to be shrunk or even eliminated.
2. Don't forget traders: Almost all of the disclosure, as written today, is focused on investor needs for information. Thus, there is almost no attention paid to the pricing metric being used in a sector, and to peer group comparisons. Rather than adopt a laissez fare approach, and let companies choose to provide these numbers, often on their own terms and with little oversight, it may make more sense that disclosure requirements on pricing and peer groups be more specific, allowing for different metrics in different sectors. Just to provide one illustration, I believe that the prospectus for a company aspiring to go public should include details of all past venture capital rounds, with imputed pricing in each round. While investors may not care much about this data, it is central for traders who are interested in pricing the company. 
3. Let companies tell stories and make projections: The idea that allowing companies to make projections and fill in details about what they see in their future will lead to misleading and even fraudulent claims does not give potential buyers of its shares enough credit for being able to make their own judgments.With the S-1, the disclosure status quo is letting young companies off the hook, since they can provide the outlines of a story (TAM, multitude of users, growth in subscribers) without filling in the details that matter (market share, subscriber renewal and pricing).
4. With triggered disclosures: To the extent that some companies want to tell stories built around non-financial metrics like users, subscribers, customers or download, let them. That said, rather than requiring all companies to reveal unit economics data, given the misgivings we have about disclosures becoming denser and longer, we would argue for triggered disclosure, where any company that wants to build its story around its user or subscriber numbers (Uber, Netflix and Airbnb) will have to then provide full information about these users and subscribers (user acquisition costs, churn/renewal rates, cohort tables etc.)

I hope that we can keep these principles in mind, as we embark on what is now almost certain to become the next big disclosure debate, which is what companies should be required to report on environmental, social and governance (ESG) issues. You are probably aware of my dyspeptic views of the entire ESG phenomenon, and I am wary about the disclosure aspects as well. If we let ESG measurement services and consultants become the arbiters of what aspects of goodness and badness need to be measured and how, we are going to see disclosures become even more complex and lengthy than they already are. If you truly want companies to be good corporate citizens, you should fight to keep these disclosures in financial filings limited to only those ESG dimensions that are material, written in plain language (rather than in ESG buzzwords) and focused on specifics, rather than generalities. Speaking from the perspective of a teacher, put a word limit on these disclosures, take points off for obfuscation and then think of what existing disclosures should be removed to make room for it!

YouTube Video

Company Filings

1. EDGAR Company Filings (US companies)
2. Companies House (UK company filings)

Research

1. The Evolution of 10-K Textual Disclosure: Evidence from Latent Dirichlet Allocation (Dyers, Lang & Stice-Lawrence)
2. Doyoureadme? (Lesmy, Muchnik and Mugerman)

The disclosure dilemma: Why more disclosure has led to less information

The last three decades have been the golden age of disclosure, as both accounting rule writers and regulators have pushed companies to reveal more and more about their prospects to investors, both in the US and internationally. Some of this push can be attributed to more activist investors, demanding more information from companies, but much of it can be traced to accounting fraud/malfeasance, where companies held back key information from investors, who paid a price as a consequence. In response, legislators, the watchdog agencies (SEC and its equivalents) and the accounting rule-writers (GAAP, IFRS) have all responded by increasing the amount of information that has to be disclosed by firms. That should be good news for investors, but here are the contradictions that I see:

• If the objective of “disclosure” laws is to prevent the next Enron, Parmalat or Worldcom accounting scandal, it clearly has not worked, since we seem just as exposed as we have always been to these problems. If anything, companies seem to have become more creative in hiding “bad” stuff, in response to disclosure laws, making it more difficult to detect problems. 
•  If the objective is to help investors value companies better, it has not worked either. To me financial disclosures are raw data, when I do valuation, and I must confess that I find financial statements more difficult to work with today than I did thirty years ago, when disclosure laws were less onerous.

So, what gives here? Why have these increased disclosure requirements not worked the magic that they were supposed to? While we can point to lots of reasons, including imperfections in the disclosure requirements, I think that the biggest problem is that the disclosure rules have turned financial disclosures into data dumps. To see my point, take a look at the 10K for a publicly traded company, even a small one, and you will see a document that runs into tens or even hundreds of pages. For instance, Procter & Gamble’s most recent 10K runs 239 pages and it is slim next to Citigroup’s most recent 10K which runs more than 300 pages.  If you are interested in valuing Procter & Gamble or Citigroup, you have to work your way through these pages, separating the wheat from the chaff, or more specifically, information from data. Faced with information overload, it is easy to get distracted by the legal boilerplate (you might as well throw out the entire section that discusses risk) and the trivial details that clutter modern disclosures. In my estimate, less than 10% (and that is being generous) of a modern financial disclosure has any value to an investor and to find this information, here are some things to keep in mind: 

1. Read with focus: Know what information you are looking for, before you start looking for it.  In other words, reading a 10K, just looking for useful information, is equivalent to digging up your backyard, looking for interesting stuff. Your most likely outcome is that you will end up with a mountain of dirt and little to show for your work.
2. Don’t sweat the small stuff: If you are valuing a $ 60 billion dollar company, you can afford to skip over that section that describes in excruciating detail a $25 million real estate lease that the company has entered into or the $50 million lawsuit filed against the company. 
3. Don’t cater to your inner accountant: We know that accounting has its fixations and that financial disclosure often cater to these fixations. Thus, there are large chunks of these documents that are dedicated to how intangible assets have been “fair valued” or goodwill has been “impaired” (a mythical asset that exists only in the accounting world). Since I don’t trust accounting fair value judgments to begin with and goodwill has but a peripheral role (if that) in cash flow based valuation models, I can afford to skip these sections. 

As some of you already know, I do teach a valuation course at Stern and my invite to anyone who is interested in sitting in still holds. Since a key part of doing valuation is learning how to work with financial disclosures, I recently put together a webcast on disclosures, where I used P&G’s most recent 10K to value the company. If you are interested, you can find the webcast with the supporting material (the 10K, my slides and my valuation of P&G). In fact, they are part of set of webcasts I am doing on the nuts and bolts of valuation:
http://people.stern.nyu.edu/adamodar/New_Home_Page/valuationtools.html

I am afraid that things will only get worse for investors. The push towards more disclosure, well intentioned though it might be, is unstoppable and  will create more bulk in annual reports and company filings, and more distractions for investors.

While I am sure that I will be ignored, here are my suggestions to the regulatory and accounting disclosure czars if they truly want to help investors:

1. Focus on principles, not rules: The principles that govern valuation are simple and robust, but they seem to take a back seat to rules when it comes to disclosure requirements. To provide a simple example, capital expenditures should measure what a company invests in its long term assets, whether those assets are tangible (land, building, equipment) or intangible (human capital, brand name, intellectual property). Not only are the accounting rules governing capital expenditures unnecessarily complex but they are internally inconsistent, with different rules governing tangible and intangible investments. (Prime exhibit: the treatment of R&D expenditures). 
2. Less is more: My wife, who is the "organizer' in our house, has a very simple rule for everyone in the family. For every new item that any of us buys, one item has to be removed (given away or abandoned) from our closets. It is an excellent rule, since in its absence, we would undoubtedly hoard what we already have, on the off chance that we might need it in the future. I would propose a similar rule in disclosure. When companies are required to disclose something new, an old disclosure requirement of equal length has to be eliminated, thus preventing disclosure bloat.
3. Target investors, not lawyers: As I browse through financial disclosures, I am struck by how much of the content is written by lawyers, and for lawyers, with the specific intent of shielding companies from lawsuits and/or regulatory backlash. While I understand that companies are gun shy about being sued, and that this protection is necessary,  it may be time to allow companies to file two disclosures, one for lawyers and one for investors. Using P&G as my example, I could construct an investors' 10K, about 20 pages in length, stripped off all the legalese that the full 10K includes.
4. Let accountants do accounting (and not valuation): I know that "fair value" accounting is here to stay, but  I believe that the push is misguided. By requiring accountants to play the role of appraisers, it asks them to play conflicting roles: provide a faithful recording of what has happened in the past (traditional accounting) while also forecasting the future (a key component of making valuation judgments). In the process, I think that we will end up with financial statements that do neither accounting nor valuation well and that investors will pay the price.

Looking forward, investors will increasingly be tested on their capacity to separate the data that matters (information) from the data that does not (noise or distraction). There is an interesting twist (and I thank Bill, who commented on this post for this insight). The increasing complexity of financial disclosure does open up the possibility that investors who can navigate their way through these disclosures and separate information from data will have a competitive advantage over other investors, who give up in frustration.

Earnings surprises, price reaction and value

The earnings season is upon us and each company’s earnings announcement is eagerly awaited, traded upon and talked about. For widely followed companies like Apple, the obsession with what the next earnings report will deliver overwhelms any sensible assessment of what it means for the company. But is this obsession merited? Do earnings announcements have significant effects on value? If so, why? More importantly, can you make money off earnings announcements? 

The “Announcement” Process
To understand how and why earnings reports matter, we should start by looking at the process. Publicly traded companies are required to report on their performance at “regular” intervals. In the US, the reports have to come every quarter, with full financial statements filed with the SEC. The degree of disclosure varies across markets, both on timing (quarterly, semi-annual and annual) and on information (partial reports of performance in some regimes).

The reporting ritual is highly scripted, at least in the US, in terms of timing (companies report earnings on about the same date every year, give or take weekends, and in the same format to allow for year to year comparisons). The initial report provides the bare bone details (revenue growth, earnings per share and a breakdown of a few extraordinary items) and is followed a few weeks later by the full filing of the quarterly report (10Q) with the SEC.

Since earnings reports contain information that can affect prices, the SEC does regulate trading and disclosure around the reports. Insiders are restricted from trading before earnings announcements and Regulation FD bars firms from providing information about upcoming earnings reports to subsets of investors (analysts). In theory, at least, the information in an earnings report should be “news” to markets.

Companies may be restricted from providing information selectively to analysts following them, but this does not prevent analysts from forming and propagating their expectations about what the earnings report will contain to their clients and, by extension, the public. In fact, a substantial portion of a typical equity research analyst’s time is spent on the “earnings forecasting” exercise, and there are services that assess analyst quality by looking at how close the forecast comes to actual numbers. In the US, services such as Zacks and I/B/E/S that track and report analyst forecasts of earnings and you can find them in the public domain (Yahoo! Finance or similar sites)

The Expectation Game
When a company does report its earnings, markets will react to the “news” in the report but the way we measure the news has to be relative to expectations. Thus, a company that reports that its earnings went up by 30% may be seen as delivering bad news, if investors were expecting an increase of 40%, and a firm that announces an earnings decline of 30% may be providing positive information, if the expectation was that earnings would decline by 40%. Thus, it is not the magnitude of the earnings change that matter but the “surprise” in the earnings, measured as the earnings change relative to expectations.

But how do you measure expectations? One obvious answer is to use the analyst estimates of the earnings and news reports like this one generally compare the earnings change to the “consensus” estimate of earnings change to frame the report. A second is to use the “past” earnings growth for the company as a measure of expected earnings growth. With either measure, then, a positive (negative) earnings surprise then becomes an earnings report where the actual earnings per share exceeds (falls below) the expected value (using consensus earnings estimates or historical earnings growth).

While you can use analysts or history as the basis for estimating expected earnings, the market expectations process is a more nuanced one and more difficult to model. In the last two decades, firms have become more attuned to playing the earnings game, and have become increasingly adept at beating earnings expectations by playing both sides of the game. First, they work on analyst expectations, using selective leaks to bring expectations down, prior to earnings reports. Second, they work to mold the actual earnings, using both accounting choices (earnings management) and operating discretion (timing of R&D expenses, for instance) to deliver results that beat expectations. The problem with this game is that markets catch on and adjust expectations accordingly.

The Announcement Effect
If you can measure earnings expectations, an earnings surprise should have an effect on stock prices, with positive (negative) surprises evoking positive (negative) responses. The earliest studies of earnings surprises used historical earnings to estimate expected earnings and found backing for this hypothesis. In more recent studies, consensus estimates of earnings have been used to measure expected earnings. The following graph captures the announcement effect of earnings surprises, categorized from most positive to most negative, with expectations measured as consensus estimate from analysts:

There are three interesting findings embedded in this graph. 

1. Pre-announcement drift: There is a mild drift in stock prices before earnings reports that is consistent with the eventual surprise: prices move up before positive surprises and down before negative surprises. I will let you make the judgment on whether this is evidence of insider trading, investor prescience or some combination of the two. 
2. Announcement effect: The announcement still contains news. On the announcement, the price effect reflects the magnitude and the direction of the surprise, with stock prices going up about 3%, on average, in reaction to the most positive surprises.
3. Post-announcement drift: The most surprising finding is that stock prices continue to drift after the announcement in response to the surprise. The graph below looks at the price drift in the 30 days after the announcement:

Differences across firms
There are studies that indicate that the returns associated with earnings surprises are more pronounced with some types of stocks than with others. For instance,

1. A study of value and growth stocks found, instance, that the returns in the three days around earnings announcements were much more positive for value stocks (defined as low PE and PBV stocks) than for growth stocks across all earnings announcements – positive as well as negative. This suggests that you are much more likely to get a positive surprise with a value stock than with a growth stock, indicating perhaps that markets tend to be overly optimistic in their expectations for growth companies. 
2. Earnings announcements made by smaller firms seem to have a larger impact on stock prices on the announcement date and prices are more likely to drift after the announcement. 
3. As with analyst reports, there seems to be evidence that the market reaction to earnings reports is a function not only of the earnings number reported but also the accompanying management commentary.
4. There is some evidence that the market reaction to earnings reports is greater at firms with high institutional ownership, with one rationale being offered that institutional investors tend to be more short term in their focus and thus more likely to respond to quarterly earnings reports.

There is one final aspect of the earnings game that may be affecting stock market reactions. As firms become adept at playing the game, managing expectations and tweaking earnings to beat expectations, investors have adapted. Firms that consistently beat consensus estimates now have to beat them by a "margin" (based upon their past history) to register a positive surprise. This is of course the phenomenon of "whispered earnings". With the Apple announcement due later today (July 24, 2012), the consensus earnings estimate is for earnings per share of $10.35 and the whispered earnings estimate is 67 cents higher at $11.02. The only problem is that Apple has beaten whispered earnings 42 out of the last 56 quarters. It is only a matter of time, I guess, before you have whispers on top of whispered earnings. My head hurts just thinking about the possibilities.

Playing the Earnings Game
So, how can investors play the earnings game? Using the earnings surprise graph as the basis for the discussion, here are some of the possible paths.
a. Predict the surprise: You can try to devise ways of forecasting positive or negative surprises before they occur. I know it is easier said than done, but to the extent that you can stay on the right side of the insider trading law and find advance indicators of upcoming surprises (trading volume changes, price patterns etc.) you can profit.
b. Trade on the news: To take advantage of the drift after the news, you could buy stocks after exceptionally positive earnings announcements and sell short on stocks after terrible earnings reports. Given that the drift is about 2-3%, don't expect this to do much more than augment returns at the margin. You could of course load up and use options to leverage the profits, but...

c. Play the earnings momentum game: While the first two strategies are short term, there is a longer term strategy that can be built around earnings reports. Studies indicate that companies that have consistently beat earnings reports over the last few quarters deliver higher returns in subsequent periods. Thus, in addition to screening for high quality growth and low risk, you can also screen for earnings momentum.
d. Intrinsic value assessment: As a believer in intrinsic valuation, I look for ways to tie the information in earnings reports to intrinsic value. To do that, though, you need to look past the top line news (earnings per share) and at the underlying details (revenue growth, operating margins and return on capital). If you do so, you may very well find  a report that looks positive on the surface (because the actual earnings exceed expectations) but contains enough negative news (lower revenue growth, declining margins and return on capitals) to cause intrinsic value to decrease. If the market misreads the report as "good" news and the stock price jumps up, you have the makings for a contrarian play.

So, here is the challenge. By the time you read this post, the Apple earnings report will have been made public. Evaluate it and make your judgment on how (if at all) you will incorporate it into your investment strategy for Apple. I have attached my intrinsic valuation of Apple (made before the earnings report came out) with suggestions on how to incorporate the information in the earnings report into value. Take your best shot!