"The penalties for financial ignorance have never been so stiff." — NYT
In order to succeed as an investor, one must understand the language of business. Wall Street professionals exploit the complexity of financial statements—what observers have called the "obfuscatory verbiage" of finance—to widen the gap between the informed and the uninitiated. Rather than depending on others to oversee your stock investments, self-reliance is essential for achieving success.
Our Excel-based spreadsheet tool—Historical Analysis v2.3 (HAv2.3)—provides an organized and credible means to work through the somewhat indecipherable information in financial statements. It is designed to short-cut the learning process for investors at every level of experience.
"Even after disclosure, the numbers that some companies report are based on accounting methodologies so complex that it can't easily be determined precisely how they were arrived at. Some companies take advantage of often-loose accounting rules to massage their numbers to make their results look better… companies have an incentive to use aggressive—but, under the rules, acceptable—accounting to boost their reported earnings and prop up their stock price." — WSJ, "Week in Ideas"
Financial advisors often find it easier to project confidence than to possess genuine expertise. Research from the Shanghai Advanced Institute of Finance found that more attractive mutual fund managers drew more investment capital and earned more promotions despite their funds performing less well than their peers—suggesting that investors too readily conflate personal charisma with financial acumen. The question every investor should ask: does an advisor's wealth derive from personal investing returns, or from selling advice to people like you?
Successful stock market investing requires a strong foundation in financial knowledge, a comprehension of collective behavior, and a disciplined mindset. As investing authority Peter L. Bernstein counseled in 1970, investors should take big risks with small amounts of money rather than small risks with large amounts.
"Investing isn't about mastering the markets; it's about mastering yourself… To be an intelligent investor doesn't require a stratospheric IQ. It does require discipline and the ability to think for yourself… individual investors are 'scarcely ever' forced to sell stocks or funds and—unlike professional portfolio managers who are continually measured against the market—are never compelled to care what other investors are doing. That independence is your single most valuable asset, a luxury most professional investors can only dream of possessing." — WSJ, "You're Not Paranoid. The Market Is Out to Get You." (11/17/24)
Studies have shown that when investors discover peers disagree with their choices, their decisions become up to three times more likely to mirror the crowd—without any conscious awareness of being influenced. Instead of investing based on the whims of the crowd, follow policies and procedures. Use a checklist focused on the stability of the underlying business rather than share-price movements:
As one leading investment manager noted: "It all starts with a well-defined process that is executed with a high degree of discipline… not many [successful investors] have a truly well-defined process and are truly disciplined in executing it." Data compensates for overconfident intuitions.
"Biases are hard-wired into our brains and personalities: Some of us are overconfident, taking excessive risks; others too meek, seeking to avoid losses at the first sign of trouble… Some mistakes arise from the tendency to feel pain from a loss more acutely than pleasure from a gain. Investors sell too quickly when holdings take a few hits, and hesitate to build big positions in stocks they like." — WSJ
Mental discipline is as critical as analytical skill. CFA Howard Marks has noted that patience is among the most important attributes in investing, and that the most consequential market movements are "primarily attributable to changes in psychology, not fundamentals—and psychology cannot be predicted and certainly cannot be timed." HAv2.3 helps investors achieve the kind of disciplined, data-driven investing that leads to durable financial success.
In aging bull markets, investors face mounting temptation. As one analyst observed, companies need to report ever-larger earnings to generate the same investor excitement as time passes. Analysts and companies dance expectations downward in tandem: analysts deliberately lowball estimates, helping companies beat them and, over time, boosting the stock price. The WSJ has noted this pattern: "To call such predictably engineered numbers 'surprises' is almost absurd… In today's market, that red flag is redder than ever."
Bull markets also breed fraudulent behavior. Trustify, Inc. and countless Silicon Valley startups illustrate how the rush to invest in a "hot funding round" leads sophisticated investors to forgo basic financial due diligence. As the counsel at law firm Anderson Kill advised: "If you feel like you need verification of something and are afraid of asking for it because it will throw you out of the deal… maybe it's not the right deal for you."
Bear markets test investor psychology in the opposite direction. The WSJ has reported on the "Hail Mary" phenomenon: investors, fixated on prior losses, make desperate, high-risk bets in hope of recovery. Neuroscience experiments confirm that choosing to stop chasing losses activates the same brain circuits that register pain and disgust—"no wonder it can be hard to stop this behavior, even if you realize your persistent bad bets are putting you deeper in the hole."
"The dangers lurking in the market can be hidden or delayed, but never eliminated. For investors, slumps are a chance for introspection—and, sometimes, new opportunity." — WSJ, "We Can't Prevent Market Panics. We Can Control How We React." (3/28/20)
The best way to recover is by gritting your teeth and grinding out gains one slow, deliberate step at a time. Recovery is a process, not an event. As Bernard Baruch famously noted: "I made my money by selling too soon."
Historical Analysis v2.3 (HAv2.3) and Projection v2.3 (Pv2.3) are software tools specifically designed for conducting financial statement and quality-of-earnings analyses and forecasts. The insights generated by these tools are valuable for a broad range of professionals.
The initial concept behind HAv2.3 and Pv2.3 originated in the Special Credits Department of a prominent West Coast bank in the late 1960s. The department focused on retailing and manufacturing companies, and the bank's objective was to develop computer software that would aid in training Credit Analysts and prevent the approval of risky loans—as well as to support customer development efforts. Throughout the subsequent decades, these tools underwent significant updates and refinements, incorporating numerous additional analytical features.
Historical Analysis v2.3 allows a user to input annual historical financial data to produce many reports, including:
HAv2.3 efficiently organizes and analyzes large volumes of financial statement data. In order to input data correctly, one must consider the accounting policies used by the company under analysis, as well as the underlying assumptions and financial statement footnotes. It can be beneficial to search for certain words and phrases in Form 10-K reports—such as "substantial doubt," "significant deficiencies," "control weakness," "disclosure failure," "irregularities," "adverse material weakness," "negative impact," "subpoena," "search warrant," "defects," "penalty," or "resigned"—though we have observed that such language often appears after our Predictor of Financial Distress and Quality of Reported Earnings sections have already indicated concerns based solely on numerical information.
HAv2.3 enables users to analyze patterns in important operational metrics such as gross-profit margins, return on investment, and corporate solvency. This analysis informs investment decisions—whether selecting, exiting, or avoiding an investment altogether.
HAv2.3 generates cell color shading to highlight financial "red flags," including questionable accounting practices and indicators of financial distress. As noted by leading analysts: "Distorting one section of the financial statements throws the numbers out of whack in some other section… analysts must be disciplined enough to disbelieve the innocent explanations that companies routinely provide for ratios that in reality reveal trouble down the road." (Financial Statement Analysis, Fridson & Alvarez)
HAv2.3 incorporates the Altman Z-Score, described as "a measure of how closely a firm resembles other firms that have filed for bankruptcy… the most widely used measure of corporate financial distress." (Stockopedia, 4/13/11) This tool complements other analytical approaches; seldom should any Z-Score measure serve as the sole basis for analysis.
HAv2.3 has been back-tested against examples cited in the U.S. General Accounting Office Report to the Senate Banking Committee (October 2002): “Financial Statement Restatements—Trends, Market Impacts, Regulatory Responses, and Remaining Challenges.” In those cases—where the outcome of financial distress or restatement was already known—HAv2.3’s analytical framework successfully identified numerical patterns consistent with those outcomes at a point in time before the distress became publicly known. Additionally, HAv2.3 analyses of Enron and Satyam Computer Services identified patterns of concern while those companies’ shares were still rising, and years before the frauds became public, respectively. View the GAO report →
It is important to note what back-testing proves and what it does not. Back-testing applies an analytical framework to cases where the outcome of fraud or financial distress was already known before the analysis was conducted. It demonstrates that the methodology is capable of surfacing the right patterns in the right historical data—a necessary condition for a sound analytical tool, but not a sufficient one. A more demanding test is whether the methodology proves useful under real-world conditions, with unknown outcomes and actual capital at risk.
The operator of this Service has used HAv2.3 and Pv2.3 as the analytical foundation of a personal stock investment process over many years, making actual investment decisions in live markets based in substantial part on the outputs of these tools. That experience has produced successful investment outcomes across that extended period—through varying market conditions including bull markets, bear markets, and periods of significant market stress.
A tool that works only in hindsight, on known cases of improper reporting, has limited value. A tool that an experienced analyst has found useful and profitable in prospective, real-world application over many years has demonstrated something more meaningful: that the analytical patterns it surfaces are not artifacts of historical data alone, but carry forward into live market conditions with sufficient reliability to support sound investment decision-making.
Taken together, back-testing against documented cases of improper financial reporting and prospective validation through extended real-world investment experience provide a more complete evidentiary basis for confidence in the methodology than either form of evidence could provide alone.
Standard caveat: The operator’s individual experience reflects one person’s application of the tools, informed by their own analytical judgment, investment philosophy, data discipline, and portfolio decisions. It does not guarantee that any other User will achieve similar results. Past performance—including the operator’s own—is not indicative of future results. Users should not invest based on any analytical tool alone without independent judgment and professional advice.
Projection v2.3 (Pv2.3) provides the ability for a user with a higher level of expertise to enter a company's financial data for the most recent year-end and input various forecasting assumptions—such as growth rates, fixed charges, and turn-days. A significant portion of this data can be obtained from the analyses generated by HAv2.3. Once entered, Pv2.3 generates annual financial statements and analyses, enabling the user to test multiple scenarios.
A major feature of Pv2.3 is that the user may pre-specify desired constraint ratios and/or amounts—including Worth-to-Debt, Times-Interest-Earned, Fixed-Charge-Coverage, and Current ratios, along with amounts of Working Capital. Using these assumptions and constraints, Pv2.3 allocates funds needed to balance the forecasted Balance Sheet among Short-Term Debt, Long-Term Debt, and/or Equity. The user is not required to engage in the seemingly endless task of manually allocating anticipated funds, checking the impact on desired ratios, then re-allocating and re-checking until reaching multiple targets. The one-step, non-iterative logic in Pv2.3 is more accurate and efficient than an iterative approach, and cell color shading highlights when the funds-needed-allocation logic has been invoked. Pv2.3 can reveal the amount, timing, and nature of a company's future funding needs.
We invite you to try the CCS Financial Statement Analysis service on a complimentary basis. Request the HAv2.3 Input Form Spreadsheet, complete it with data for the company you wish to analyze, and return it to us. We will conduct a full analysis and deliver your report — free of charge for your first submission.
There is no obligation and no credit card required.
The primary attraction of investment books, as the WSJ has noted, "isn't beautiful prose or a compelling plot. Our relationship with such titles is more transactional. We spend the time and money in hopes of learning something that will help us make better investors." (WSJ, 9/8/22) The concepts of financial statement analysis and related red-flag tests used in HAv2.3 and Pv2.3 have been derived from the following works, among others.
The market for shares of the largest companies is more efficient because many more analysts follow such securities compared to those who follow small and lesser-known companies. The prevention of serious investment errors is at least as important a factor in overall investment success as is the discovery of undervalued securities.
Even though market prices reflect some relatively sophisticated analyses, prices still do not fully reflect all the information that could be garnered from publicly available financial statements. Even in the absence of direct information about management expertise, financial ratios can reveal much about who will make it and who will not.
This investment approach does not attempt to identify firms with superior growth prospects, which may or may not be realized. Instead it focuses on solid firms that are temporarily mis-priced by the market. One of the most attractive areas for investment is small-capitalization stocks.
Based on the analysis-of-corporate-financial-reports course in Harvard Business School's MBA program: "Published corporate financial statements can represent genuine managerial performance, or they can represent the illusion of performance. Investors who can tell the difference have a considerable advantage in making their investment decisions."
While most companies act ethically, some take advantage of gray areas in the rules to "make the numbers." When one of the three financial statements contains shenanigans, warning signs generally appear in the others. Savvy investors often compare net income with Cash Flow from Operations and become concerned when CFFO lags net income.
The authors looked for financial statement clues indicating that something was amiss, drawing on surveys of approximately 200 lenders to understand how earnings surprises occur. A key insight: when a company overstates revenue, one or more accounts on the balance sheet must also be overstated. Professor Mulford has noted that a key red flag auditors look for is a discrepancy between net income and operating cash flow—precisely the kind of divergence HAv2.3 is designed to surface.
Distorting one section of the financial statements throws the numbers out of whack in some other section. Invariably, an allegation of irregularities in corporate financial reporting is followed by a vehement, formulaic denial. Analysts must be disciplined enough to disbelieve the innocent explanations that companies routinely provide for ratios that in reality reveal trouble down the road. An influential 1966 study found that of all the ratios tested, the best predictor of bankruptcy was a declining trend in the ratio of cash flow to total debt. Financial statements are vulnerable to manipulation, much of which is perfectly legal—often, the specific aim of the manipulators is to outfox credit analysts who mechanically calculate ratios without pausing to consider whether accounting rules have defeated the purpose.
O'Glove tells investors precisely where to scrutinize financial reports, and how to make sense of what they find. Regarded by many investors as a forensic bible, the book trains readers to look beyond reported earnings and assess the true economic health of a company. (WSJ, 6/2/07)
A book about the people who profit from collapse, who specialize in detecting disaster, and the methods they use to track the demise of companies. How to make money by shorting and how not to lose money by selling are different sides of the same coin. James S. Chanos of Kynikos Associates tends to focus on the numbers, with his use of return on invested capital as a key financial indicator being unique. One common shortcoming is to rely on management or Wall Street analysts. Shorts almost always judge correctly whether the business is seaworthy—on the timing of the demise, they are seldom right. Add two years to the short's best projection and you may only have a couple more to wait. Grizzled analyst wisdom says sell the stock of a company building a new headquarters—owned, not leased: it's a top-of-the-earnings-cycle clue. You can hide disgusting accounting practices with growth for a very long time.
What the auditor is really saying: (1) We took a look. (2) We did a few tests. (3) The financials are probably OK. (4) If they are not OK, we didn't write the financials—management did. What the auditor doesn't say: (1) We guarantee our work. (2) We did an intense, excellent review. (3) We could have been fooled, and therefore be completely wrong. A bracing guide to reading behind the veneer of audit opinions and corporate disclosures.
A rigorous practitioner-oriented guide to interpreting corporate financial reports, with emphasis on the analytical techniques that distinguish genuine financial performance from accounting-driven illusions.
Even if you are a competent, careful, and hardworking executive, you might end up making avoidable, predictable mistakes. One can draw a false conclusion from accurate facts. Fact-checking is not the same as story-checking. The technical quality of financial analysis is no longer a source of differentiation between good and bad decisions: it is a prerequisite.
If you arm an investor with the right psychological tools, you could give him a critical edge—helping him avoid mental blunders and seize opportunities he might have missed if he were less self-aware. Investors get so caught up in the markets that they don't consider their attitudes and biases and how they might be impacting their decisions. You make investment mistakes not because you lack information, but because you ignore the information you already possess. You don't follow your systems or pay attention to your indicators because powerful internal forces stand between you and success. Some investors are very good at cutting their losses, but not so good when it comes to holding or increasing a position—it all comes down to being psychologically able to win. Winners are tough to find, so once you've latched on to this precious commodity, don't give it up without a solid reason. You can train your mind to make wiser and more beneficial decisions about how to invest your money.
In every domain, the outcome tail is wagging the decision dog. Writing down key facts informing your decision acts like a vaccine against hindsight bias.
Bubbles are the result of a herd of people who collectively start paying more for something than its intrinsic value. In bubbles, the herd and its collective psychology prevail over the individual. Euphoria wins out over skepticism.
As prosecutors later found, the bank "lied to clients that it was conducting rigorous due diligence when in fact [it] had stopped doing any due diligence whatsoever." Gross is great; but net is where it's at.
On Crazy Eddie's implosion: "Wall Street analysts just wrote down what [the PR man] told them and did not bother with all that financial stuff." The lesson remains as relevant as ever.
In 1998, six Cornell MBA students used statistical tools to identify clear signs that "Enron may be manipulating its earnings." The report was publicly posted; anyone could have read it.
Management may arrange for a valuation report from a respected professional, then alter it to support a fraudulent valuation. Reports should be reviewed carefully for signs of altered text, missing pages, or insertions.
Bankers have no issue advising companies on how to invest billions of dollars, but are often at a loss as to what to do with their own money. Real companies with real people managing them do deals for one reason: they feel pressure.
Half the firms studied gave no consideration to the possibility that poor quality, long lead times, late deliveries, and dependence on a single source of critical products could hurt their bottom lines.
A long history of how and why the Department of Justice came to avoid prosecuting major corporations, with direct consequences for investor protection and accountability.
Most organizations are far more effective in suppressing employee ideas than promoting them. The most important indicator one leading manager uses is not a financial metric but the number of ideas implemented in the previous week—the best leading indicator of a company's future performance. When managers first realize the value in the ideas of their employees, it is a profoundly liberating experience. Employees become allies in solving problems, spotting opportunities, and moving the company forward—and when managers decide to let their employees think alongside them, they have joined the Idea Revolution.
Bankers in the class told the author they would frequently produce elaborate valuation spreadsheets for client proposals, knowing the numbers were essentially nonsense—bearing the appearance of competence and intelligence, but meaning desperately little. The degree enabled them to get jobs that robbed them of their private lives. The author's conclusion: do what you love, don't settle, and if you love what you do, the money will follow.
A comprehensive account of Cooper's role as an Internal Auditor in uncovering massive financial fraud at WorldCom, including her experiences conducting operational and financial-statement audits. The main perpetrator manipulated financial ratios to deceive auditors, analysts, and investors into believing they were accurate and legitimate. Importantly, the utilization of HAv2.3 would have effectively detected WorldCom's manipulations of bad-debt allowances and reserves, as well as the conversion of expenses into capital expenditures—surfacing the fraud through the numbers alone.
Successful stock investing requires the ability to detect different financial irregularities and signs of financial difficulty well in advance of companies entering bankruptcy proceedings or experiencing devastating stock-price declines. One should continually monitor investments by setting alerts at News.Google.com and Seeking Alpha, and annually update prior HAv2.3 analyses with the most recent SEC Form 10-K data. Free SEC filing alerts are available at www.secfilings.com.
"Don't blame Wall Street analysts, rank-and-file investors and journalists for failing to read corporate earnings reports from beginning to end… It's the financial figures within these pages that are critically important… The turgid language in these dull corporate reports is actually sprinkled with important clues about major problems—and there is a way to get an inkling about them without actually having to read every word. When the language in the current text varies a great deal from previous versions, it frequently signals trouble that will become evident several months later." — NYT (research by Lauren Cohen, Harvard Business School)
Professor Cohen's research suggests that textual changes in the "risk factors" section are the most likely to predict subsequent share-price movements, with 86% of reports with substantial wording changes negative in tone. Until such "Lazy Prices" research is widely understood, it may be possible for some investors to profit from it. That said, the practical challenge of quantifying "a lot of changes" remains significant—changes are just "another piece of evidence." Stick with a thorough analysis of the numbers.
One might exit an investment—at a profit or a loss—when HAv2.3 indicates unreasonably high valuations, developing financial stress, and/or mismanagement. As the WSJ has reported, the highest price-to-growth (PEG) ratios are often indicators of over-valued stocks: a PEG over 4 is a warning sign. PEG ratios provide an objective measure of valuation rather than relying on gut feelings. Our experience has shown that, when liquidating, it is best to liquidate the entire position. Otherwise, one might be tempted to average-down another time if the stock's price declines again.
After-action reports are imperative whether there was a profit or loss. Robert Olstein, who runs the Olstein Financial Alert fund, is so focused on balance sheet analysis that he refuses to meet with company management for fear of being influenced. His skepticism took root in the Quality of Earnings Report—a newsletter he founded with Thornton O'Glove in 1970 that scrutinized company balance sheets and warned subscribers about problems.
"In looking back, the lack of access forced Mr. Wold to rely only on publicly disclosed numbers and outside resources for his analysis, and in doing so he got it right. Maybe that is the moral of this story: Let the numbers do the talking, not the company." — WSJ
For ongoing portfolio monitoring, Bob Olstein of Olstein Funds begins SEC 10-K analysis with the income-tax footnote: "What I want to see is a reconciliation of the income the company is reporting to shareholders and the income being reported to the IRS. A big difference between the two can be a red flag that requires further research." He also examines inventory footnotes: "A huge build in raw materials and work in progress relative to finished goods can mean orders are picking up. The reverse can be if finished goods are building and raw materials are not."
History's corporate scandals offer sobering lessons. The list of companies whose financial shenanigans were detectable through rigorous financial statement analysis—had investors known where to look—includes Enron, WorldCom, Tyco, Crazy Eddie, ZZZZ Best, Wedtech, Sunbeam, Krispy Kreme, and many others.
"Crazy Eddie is hardly the first stock to confound securities analysts. But in this case, Crazy Eddie's founder himself inspired much of their bullishness. His ability impressed them, and he was their principal source within the company. Yet, while the public was buying Crazy Eddie shares, Mr. Antar sold them—heavily." — WSJ
The pattern repeats across generations. Sunbeam's board of directors, even while overseeing the company, ultimately stated they had been "seriously misled by prior management"—Sunbeam restated 18 months of earnings and filed for bankruptcy. A board or investor with proper financial statement analysis tools might have detected the fraud sooner.
The importance of financial statement literacy continues to generate extensive media coverage. Selected themes and sources, for reference:
The WSJ has reported that accounting-fraud indicators have signaled economic trouble before broader market recognition—making tools like HAv2.3 valuable for early detection.
Company insiders made billions before the SPAC bust, with executives and early investors selling shares worth $22 billion while retail investors were left holding the losses.
The WSJ has documented how analysts and companies dance expectations downward in tandem—analysts deliberately lowball estimates, helping companies beat them and boosting stock prices. "To call such predictably engineered numbers 'surprises' is almost absurd."
Research continues to confirm that investors over-rely on past performance rather than underlying financial fundamentals—a costly bias that FSA discipline can correct.
Bloomberg has reported that investing novices are calling the shots for $4 trillion at U.S. pensions—a troubling governance gap with direct implications for beneficiaries.
Experiments show that when you discover your peers disagree with your investment choices, your decisions become up to three times more likely to match theirs—without conscious awareness of being influenced.
The following annotated PDF analyses demonstrate the HAv2.3 methodology applied to real public companies, each of which experienced financial distress, earnings manipulation, or bankruptcy. As Howard Schilit of the CFA Institute has noted: "Accounting manipulation… tends to be done within the letter of the law and technical interpretations of accounting standards but presents a misleading picture of the economic performance of the company… There are no smoking guns here. You have to find signs of companies camouflaging problems." HAv2.3 shows you the signs.
Our Satyam HAv2.3 Analysis detected problems including a Probability of Manipulation as early as 2004. Our Enron HAv2.3 Analysis detected financial problems while the market price of Enron's stock was still rising to its all-time high—early identification that would have allowed an investor to benefit from the run-up while avoiding the devastating decline that followed.
HAv2.3 detected financial problems while Enron's stock was still rising to its all-time high. Early identification enabled informed decision-making before the catastrophic collapse.
Download PDF →HAv2.3 detected a Probability of Manipulation as early as 2004—years before the $1.5 billion accounting fraud became public in 2009.
Download PDF →An annotated HAv2.3 analysis including red-flag cross-references to related media articles, illustrating how financial distress signals appear in the data well ahead of public recognition.
Download PDF →HAv2.3 balance sheet analysis revealed the warning signs visible to any investor who knew how to read the numbers—well before JCP's eventual bankruptcy filing.
Download PDF →A comprehensive annotated HAv2.3 analysis demonstrating the full breadth of ratio and earnings-quality analysis the tool provides.
Download PDF →The following companies have been analyzed using HAv2.3, each of which subsequently experienced significant financial distress or bankruptcy. These analyses are available upon request.
Contact FSA@ConcernedShareholders.com to request any of these analyses or the current version of HAv2.3.