CFA Institute

“The descent is always more sudden than the increase; a balloon that has been punctured does not deflate in an orderly way.” — John Kenneth Galbraith I traveled with my family to London and Normandy, France, in July 2022. The trip’s primary purpose was to meet up in Normandy with my father-in-law, who had always dreamed of visiting the sites where the tide turned in World War II. I did not realize that our excursion would have so much relevance to today’s economic conditions. On 21 September 2022, the US Federal Reserve intensified its attack on inflation with its third consecutive 75 basis point hike to the federal funds rate. The Fed also warned that more monetary tightening was forthcoming and would continue for at least the next year. Threading the Needle on Threadneedle Street The Fed is in a difficult position: It must prepare the public for the impending economic pain but without inciting a panic. The reality, however, is that a recession is now a virtual inevitability. Why? Because the Fed can only use blunt policy tools to reverse what have become extreme economic conditions. This makes it extraordinarily difficult to engineer a soft landing. The last two comparable events, the 1920 and 1979-to-1981 tightening cycles, both triggered severe economic contractions. During our visit to London, my son and I visited Threadneedle Street and the Bank of England Museum, where we played the Inflation Game. The goal is to balance a steel ball at the mid-point of an air tube denoted with a 2% inflation marker. The player — or an annoying father — then pushes an “economic shock” button that shakes the tube, dislodges the ball, and sends it to either the extreme right, which represents inflation, or to the extreme left, which represents deflation. My son struggled to return the ball to the target, overshooting several times before getting it to settle back on 2%. The Inflation Game at the Bank of England MuseumImage courtesy of Mark J. Higgins, CFA, CFP® The Inflation Game is a perfect metaphor for the Fed’s predicament since the onset of the COVID-19 pandemic in March 2020. First, the massive economic shock sent the ball careening to the left. The Fed and the federal government responded by flooding the economy with liquidity to ward off extreme deflation and a potential depression. Then, in 2022, after the excessive stimulus had shifted the ball too far to the right, leading to high inflation, the Fed reversed course. It will almost certainly overshoot the target again, only in the other direction, before it can finesse a return to the comfortable 2% target. The Human Costs of the Great Depression This monetary tightening will have consequences — the ball has simply strayed too far from the midpoint. This will produce economic pain in the form of declining asset values, job losses, and general anxiety about the future. That does not mean that the Fed takes its responsibility lightly. The Fed’s leadership knows that its policies will cause short-term pain, but it also knows that the long-term consequences of policy blunders — or of doing nothing — are much more severe. This brings us to the second stop on our trip: Normandy, France. That World War II broke out less than 10 years after the start of the Great Depression is no coincidence. In 1929, the Nazi party was on the verge of collapse. The German economy was recovering from the devastating hyperinflation of the early 1920s, and renewed optimism was taking root. In the 1928 elections, the Nazis won only 12 of the 491 seats in the Reichstag. But then the Great Depression hit. Millions of Germans joined the ranks of the unemployed, and the economic decline seemed to have no bottom. In the September 1930 elections, the Nazis won 107 out of 577 seats and set about dismantling the Weimar Republic. The experience of the 1930s and 1940s is worth remembering. When central bankers flood the market with liquidity to forestall a Great Depression–level event, their primary goal is not to prop up stock prices but to save lives. Would World War II, and all its horrors, have occurred without the Great Depression? Probably not. Could similar disasters have developed in 2020 — or 2008 — had central bankers and government policymakers throughout the world failed to stop the panic? It’s a distinct possibility. The Misery of the Great Inflation The dislocations of the Great Inflation from the late 1960s to early 1980s caused similar levels of deprivation in the United States. The Misery Index, which adds the inflation rate and the unemployment rate, reflects this. During the worst years of the Great Inflation, Misery Index readings were almost as bad as they were during the Great Depression. The average Misery Index from the peak period of the Great Inflation from 1968 to 1982 was 13.6%, versus 16.3% during the 1930s. The US Misery Index, 1929 to 2021* Sources: Federal Reserve Bank of Minneapolis, Department of Labor statistics*The official Misery Index begins in 1948. Unemployment and inflation data used to calculate the Misery Index prior to 1948 is based on a different methodology. Nevertheless, the general trend is likely to be directionally correct. History demonstrates that economic suffering breeds popular discontent, which in turn, breeds civil unrest and violence. That’s what happened amid the Great Inflation of the late 1960s and 1970s in the United States. Indeed, the misery of the Great Inflation was even more insidious than that of the Great Depression. An economic collapse is easily understood as a source of suffering. The debilitating anxiety caused by constant price spikes is harder to grasp. It took the foresight and courage of Paul Volcker to magnify the pain temporarily to rein inflation in over the long term. Sympathy for the Fed The Fed and other public officials are easy to criticize, but I believe they take their responsibilities seriously and understand that their decisions affect the lives of millions of people. Their quick

Aswath Damodaran doesn’t care how rigorous our valuation methods are. The greatest challenge in valuing companies isn’t coming up with better metrics or models. It’s dealing with uncertainty. In fact, more precisely, the problem is NOT dealing with uncertainty, according to Damodaran. As humans, we tend to respond to uncertainty with denial or avoidance: Our first reaction is to make the problem worse. And uncertainty is always greatest with younger companies because they have not only less history and more unknowns but also virtually infinite potential. At the Alpha Summit GLOBAL by CFA Institute, Damodaran discussed the art and pitfalls of valuing young companies. The key is learning to deal with the biases that lead us astray when we encounter uncertainty. “Those unhealthy practices are what get in the way of valuing your company,” he explained in his presentation, “Dreams and Delusions: Valuing and Pricing Young Businesses.” To help us overcome uncertainty and improve our valuations, he laid out a framework of simple valuation rules. Choose the Form of Your Destructor Uncertainty comes in many forms, and Damodaran sorts them into three categories. The first is estimation uncertainty versus economic uncertainty. While we can reduce estimation uncertainty by gathering more or better information, economic uncertainty is harder to mitigate. “I’m going to give you some bad news,” Damodaran said. “Ninety percent of the uncertainty we face in valuation is economic uncertainty. No amount of homework or data is going to allow it to go away.” The second grouping is micro uncertainty versus macro uncertainty. Micro uncertainty focuses on the company itself — what it does, its business model, etc. Macro uncertainty encompasses interest rates, inflation, government policies, and other factors beyond a company’s control. In most valuations of publicly traded companies, macro uncertainty dominates the discount rate. The third category is continuous versus discrete uncertainty. For example, under normal conditions, exchange rates fluctuate continuously without having a major impact on a company’s cash flow. Discrete uncertainty involves things that don’t happen often but that can be disastrous if they occur. If the company’s main operating currency suddenly devalues by 75%, that kind of discrete event will have a catastrophic effect on the business. With these three categories in mind, Damodaran turned to the larger question of dealing with uncertainty in valuations for younger firms. The process begins with understanding the life cycle of companies, going from younger to middle aged to old. Each stage has different characteristics and risks. For younger companies in particular, micro-uncertainty tends to be most important. As companies mature, macro-uncertainty becomes more significant. But uncertainty is greatest for young companies because everything is in flux, which is why they tend to provoke the unhealthiest responses. What do these responses look like? First, we sometimes simply shut down because the uncertainty is overwhelming. Second, we deny that the uncertainty exists or pretend that we can’t see it. Third, we use mental accounting: We make up rules of thumb based on companies we valued in the past. “Then there’s a fourth and very dangerous form of dealing with uncertainty, which is you outsource. When you feel uncertain, what do you do? You call in a consultant,” Damodaran said. “You just don’t take responsibility then for what goes wrong.” Want Better Valuations? Tell Better Stories To value young companies well, we have to account for all these different types of uncertainty, and we have to manage our own, often unhealthy reactions to uncertainty: paralysis, denial, avoidance, and outsourcing. Damodaran suggested some simple coping mechanisms and a three-step process. Step one is to come up with a story, something he describes in Narrative and Numbers: The Value of Stories in Business. Damodaran believes we have grown too dependent on financial models, to the point of losing the plot. “A good valuation is a marriage between stories and numbers,” he said. “When you show me the valuation of a company, every number in your valuation has to have a story that’s attached to it. And every story you tell me about a company has to have a number attached.” With well-established companies, it’s possible to project numbers into the future. But this doesn’t work with young companies: It generates junk valuations because last year’s numbers can’t be projected forward. With young companies, it’s hard to convert a story into numbers. Doubt becomes a factor. We’re afraid of being wrong. But we’ll come back to that. “Second step: Keep your valuations parsimonious. Less is more,” he said. “I know the instinct that a lot of people have in valuing companies is to add more detail, and we now have the tools to do it. We’re drowning in detail. I see valuations that often run to 300-line items and 15 worksheets. Let it go.” Rather, Damodaran recommends homing in on a few essential variables. For young companies, he focuses on six factors. The first three apply to the business model: revenue growth, target operating margin (to capture profitability), and sales-to-invested-capital ratio (to reflect how efficiently growth is captured). “The other three metrics are related to risk. Two relate to your costs,” he said. “One is what does it cost you to raise equity. And the second is how much does it cost you to raise debt. That goes to your cost of funding.” What’s the last risk-related metric? The likelihood that your company will fail. “Every discounted cash flow valuation is a valuation of your company as a going concern,” Damodaran said. “But there’s a chance your company might not make it, especially for young companies.” The component to measure riskiness itself is cost of capital. With higher growth and higher reinvestment, Damodaran expects to see higher risk. A valuation that shows high growth, low reinvestment, and low risk should raise questions. If there are internal inconsistencies, we need to have solid reasons for them. The Proper Care and Feeding of Discounted Cash Flow Analysis What’s the most common error when applying discounted cash flow analysis to young companies? Ignoring economic first principles,

The stock markets over the last two years have been variously nerve-racking and exhilarating depending on who you ask and when. But for behavioral finance aficionados, the COVID-19-era equity markets have offered a rare opportunity to witness an almost never-ending sequence of behavioral biases in action. Indeed, we can draw straight lines from various market phenomena observed since March 2020 to specific behavioral biases and sets of biases. Staying Away One mistake investors made early in the pandemic was not buying quality names after the initial COVID-19 plunge. To be sure, cruise lines and other firms in the direct path of pandemic-related related disruption were going to be a hard sell, but many companies that experienced sharp corrections had long track records of highly profitable operations across multiple business cycles. They were cash-generating machines with strong balance sheets, powerful brands, wide and loyal customer bases, significant pricing power, wide moats, etc. The pandemic was not going to sink them. Demand was bound to recover. Share Price1 January 2020 Share Price16 March 2020 Change from1 January 2020 Share Price3 May 2022 Change from16 March 2020 Coca Cola $55 $45 -18% $63 40% Nvidia $60 $51 -15% $196 284% Salesforce $167 $124 -26% $178 44% McDonald’s $200 $149 -26% $250 68% Apple $74 $63 -15% $166 163% BlackRock $501 $357 -29% $631 77% Merck $92 $70 -24% $90 29% Charles Schwab $48 $31 -35% $69 123% Facebook $210 $146 -30% $212 45% Caterpillar $151 $93 -38% $214 130% So why did so many of us — including yours truly — hesitate and miss out on the opportunity of a lifetime? Because of a mix of the following biases: Myopic Loss Aversion: We overfocused on short-term losses and underemphasized the potential for long-term gains. This led us to avoid assets that had experienced recent volatility.  Continuation or Extrapolation Bias: This also played a role. Because we had just been on the volatility rollercoaster, we assumed the ride wasn’t over, that it would continue indefinitely into the future. Regret Aversion: This was another key bias. We feared the consequences of errors of omission, of not buying the right stock, just as much as those of commission, or buying the wrong stock. So many of us stayed on the sideline. Chasing Pandemic Winners The massive monetary and fiscal stimulus that began in March 2020 combined with the work-from-home (WFH) phenomenon guaranteed that many stay-at-home stocks would become huge pandemic winners. Share Price23 March 2020 Share Price31 October 2020 Change Fiverr $24 $146 508% Peloton $23 $116 404% Pinterest $14 $59 321% Sea Limited $43 $158 267% Zoom $135 $461 241% Despite the surge, however, many of these were absurdly priced loss-making companies even back in April 2020. It was also clear that demand was being pulled forward and that the stupendous revenue growth achieved during the pandemic was unsustainable in the medium to long term. So why did so many of us jump on the bandwagon and refuse to get off? Self-Enhancing Bias: Who deserves credit for our success? We do. If we bought Peloton and its price quadrupled in six months, it was because of our stock-picking genius rather than dumb luck or a market fueled by cheap money. Herd Behavior: Much like a school of fish that swims in the same direction, we humans mimic the behavior of others. When in doubt, we go with the crowd in forming our opinions or making quick decisions. And that’s especially true in a bubble or crisis. Confirmation Bias: We choose what information we consume about our decisions and we gravitate towards data that validates them. So we surround ourselves with people and media that tell us what we want to hear. From April to October 2020, financial news media trumpeted the pandemic winners, the Pelotons and the Zooms. A famous investment newsletter to which I subscribed wrote only about these sorts of stocks, talking up the positives and ignoring any negatives. Missing the Clues on Inflation Few expected inflation to soar so high or to stay high for so long. We underestimated the magnitude of the splurge on consumer goods amid the lockdowns and overestimated the strength and resilience of global supply chains. And the demand and supply-side shocks drove inflation to 40-year highs. Why did we miss the signals? Because inflation had barely budged in 10 years. Massive quantitative easing (QE) in the aftermath of the global financial crisis and record low unemployment had had little inflationary effect. Since inflation hadn’t increased in so long, we assumed it never would. If $4.5 trillion hadn’t done the trick, what was a few trillion more? Availability Bias: That’s what behavioral economists call this. It comes down to the three Rs: We recall what’s recent and consider it relevant. The first two Rs are fine, but the last is a disaster. Many of us weren’t alive for the last stagflation, when interest rates hit 20% in the early 1980s, and know only the rather benign inflation that has been the story ever since Paul Volcker tamed the dragon back in 1982. So we believed the future would look like the recent past. The Robinhood Effect Remember the meme stock mania in early 2021? When Jim Cramer and company couldn’t stop talking about GameStop and Hertz and AMC? AMC shares jumped 250% in five trading days and GameStop’s shot from around $17 to $350 in January 2021. The Wall Street Bets subreddit was largely responsible. The forum grew 400% in less than a week, from two million users to over eight million. Many forum members had never directly invested in the market before. Stimulus checks had fattened bank accounts and we bid up these stocks to ridiculous levels. A few hedge funds had shorted some of them and many retail investors saw a chance to stick it to the big shots. Some hedge funds got caught in the ensuing short squeeze. But fast forward a few months and the meme stocks collapsed, leaving many investors with huge losses.

Introduction The Shanghai Stock Exchange Composite Index (SSE) was booming in early 2015, and as it soared, legions of new investors rushed in to try their luck at securities speculation. Although stock bubbles were nothing new, this one had two peculiarities. First, under the regulatory framework, SSE stocks could not rise or fall more than 10% on any given day, which after several months of a bull market, made for some unusual-looking stock price charts. Second, many retail investors focused on buying “cheap” stocks, or those that traded below 20 renminbi (RMB). Like all bubbles, this one eventually deflated. The SSE plunged nearly 40% between June and September 2015 and taught many novice investors the difference between price and valuation. A stock trading at $5 may be overly expensive, just as one that trades at $1,000 may be a bargain. While experienced investors understand this intuitively, many financial advisers still make similar mistakes. On any given day, they meet with prospective and current clients to discuss their financial outlook. Central to these conversations are forecasts, often in the form of Monte Carlo simulations, that estimate the value of the client’s investment portfolio at their prospective retirement date. Here is why this is a flawed approach and why there is a better way to anticipate future returns. Expected Returns Thousands of metrics have been tested across time periods and geographies, but there is no evidence that any investor, even those equipped with artificial intelligence (AI)-powered strategies, can forecast individual stock prices or that of the entire market in the short to medium term. If it were otherwise, mutual fund and hedge fund managers would generate more alpha. Forecasting the long-term expected returns should be more feasible. Although not a perfect relationship, S&P 500 returns over the next 10 years have tended to reflect the current earnings yield, or the inverse of the price-to-earnings (P/E) ratio. Put another way, valuations matter, and the higher the earnings yield today, the higher the expected returns 10 years from now. US Equity Returns vs. Starting Earning Yields Sources: Online Data Robert Shiller, Finominal US investment-grade bonds over the last 20 years demonstrate the relationship between expected long-term returns and current valuations even more strongly. The bond’s initial return was the equivalent of the annual return for the next 10 years. For example, if the current bond yield is 2%, then the expected return is likely 2% per year for the next 10 years. So, you get what you pay for. US Bond Returns vs. Starting Bond Yields Source: Finominal The Folly of Monte Carlo Simulations Financial advisers rarely use stock and bond market valuations to build their long-term forecasts. Rather, they primarily run Monte Carlo simulations that do not consider valuations at all. The inputs for these simulations are historical prices and a few model assumptions, while the output is a range of expected returns with a certain probability and assuming a normal distribution. A portfolio’s range of expected returns may be 13.45%, with a bottom quartile expectation of –0.63% and an upper quartile expectation of 25.71%, given an 85% probability. Such a result will only confuse most clients, but even if it doesn’t, the underlying method is flawed and should not be applied to investment portfolios. All financial products come with the same warning label: Past performance is not indicative of future results. Just because equity markets have gone up for years doesn’t mean they always will. We can cherry-pick a few points in time — January 2000, November 2007, and December 2007, for example — when the S&P 500’s return was miles away from its actual realized return over the next 12 months. Naturally, at these moments, the S&P 500’s P/E reached record levels. But that is not an input for a Monte Carlo simulation. Actual US Stock Returns vs. Monte Carlo Projected Returns Source: Finominal We can select similar periods for US investment-grade bond markets, such as December 2008, July 2012, or August 2020, when yields reached record lows. At those points, Monte Carlo simulations would recall appealing past returns and forecast the same trajectory going forward. But bonds do become structurally unattractive at certain yields. Yields on European and Japanese bonds went negative during the last five years — but not if we only looked at Monte Carlo simulations based on past performance. Actual 10-Year US Treasury Returns vs. Monte Carlo Projected Returns Source: Finominal Capital Market Assumptions For those forecasting expected returns for an investment portfolio, capital market assumptions are an alternative to Monte Carlo simulations. The process is much simpler and only requires the capital market assumptions, which are available for different asset classes and equity factors from various investment banks and asset managers, and a factor exposure analysis of the portfolio. These can be differentiated into upside, base, and downside cases so that the forecast delivers a realistic range of outcomes. Tools to help accomplish this are freely accessible. Finominal’s Return Predictor, for example, can estimate the return contributions for a diversified portfolio of equities and bonds. Contribution to Predicted Annual Returns of Diversified Portfolio Source: Finominal Further Thoughts Monte Carlo simulations have obvious flaws, but so do capital market assumptions. Market analysts and economists alike have a poor track record when it comes to generating accurate forecasts. If they were good at it, they would be fund managers making money off their predictions. As it is, no fund manager can time the market with any consistency. But asset managers rely heavily on valuations when creating their capital market assumptions, so they may be preferable to simplistic Monte Carlo simulations based on past performance. Whatever the method, the forecasts will inevitably be wrong, but one approach is slightly more foolish than the other. For more insights from Nicolas Rabener and the Finominal team, sign up for their research reports. If you liked this post, don’t forget to subscribe to Enterprising Investor. All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the

Defined contribution (DC) plans are among the most common ways for US workers to save for retirement. US DC plan programs totaled $9.6 trillion in assets as of the third quarter of 2023 when they represented 22% of all US retirement assets. This creates tremendous responsibility for plan sponsors as they provide and manage retirement benefits on behalf of their employees. To help plan sponsors, we curated seven topics that we believe they should make top priorities for their retirement programs in 2024. 1. Complete a Comprehensive Target Date Fund (TDF) Review Target date funds (TDFs) are a distinguishing feature of DC plans: 85% of plan sponsors offer them. These funds automatically rebalance to become more conservative as participants near retirement. For this reason, TDFs appeal both to plan participants seeking a hands-off approach to managing their retirement savings and to plan sponsors that use such funds as their plan’s qualified default investment alternative (QDIA). In fact, of the 80% of plans with a QDIA, 86% of them use a TDF. As a result, plan participants often have their entire account balances invested in a TDF. This makes a strong selection process as well as diligent and ongoing monitoring absolutely essential. The US Department of Labor’s (DOL’s) guidance “Target Date Retirement Funds — Tips for ERISA Plan Fiduciaries” outlines TDF selection best practices. Plan sponsors should review the complete guidance before evaluating their TDF. In our own reading of the guidance, we identified three important questions that plan sponsors should ask themselves. Together, they serve as a litmus test to determine if a TDF review might be warranted sooner rather than later: Did your initial analysis of investment options consider your company-specific workforce demographics? Did your initial analysis include an evaluation of multiple TDFs? Have you reviewed your TDF selection, beyond normal performance monitoring, within the last three years? If the answer to any of these questions is no, plan sponsors may want to prioritize a TDF review in 2024. 2. Trending and Trendy vs. Beneficial and Necessary Articles, conference sessions, and webinars that herald new ideas that will make DC plans “better” can be distracting and often blur the line between marketing and thought leadership. As an example, historically, most retirement planning communications have emphasized accumulation. In the past two years, they have expanded to “decumulation” strategies that focus on what happens after retirement. This has created a wave of sponsored content promoting in-plan annuity or “lifetime income products.” Despite the supposed popularity of such products, only 9.9% of plans actually offer them to their plan participants. The industry is in the midst of a rapid innovation cycle propelled by the Setting Every Community Up for Retirement Enhancement (SECURE) 2.0 Act of 2022, increased competition among service and product providers, and other secular trends. It is an exciting time, and much of what is being developed may serve plan participants well in the future. But plan sponsors have to maintain their discipline and embrace a holistic, goals-based approach when they evaluate trending DC plan products, features, and solutions. 3. Offer Comprehensive Employee Financial Education Resources To recruit and retain top talent, plan sponsors must customize their financial education strategy to the needs of a diverse and evolving workforce. Different generations of workers engage with educational content in different ways: Some prefer in-person meetings, videos and articles, or one-on-one sessions. What resonates with someone early in their career may not work for someone approaching retirement. As a result, plan sponsors must target, differentiate, and vary their education methods to engage all their employees. A well-managed retirement plan supplemented by comprehensive financial education resources can be a critical recruiting and retention tool. Our clients have enjoyed the greatest success when our employee education consultants work with our retirement plan advisers to build annual education campaigns that incorporate the diverse needs of their employees. A little bit of planning goes a long way in improving participation, engagement, deferral rates, and other important metrics. 4. Focus on Holistic Financial Wellness Last year, inflation and the threat of a looming recession were top of mind for many Americans. Three statistics from a recent PNC survey of corporations and their employees emphasize this: Seven in ten employees reported feeling financial pressure that negatively impacted their work. Three of four employers reported that employees’ financial stress affected operations, leading to reduced productivity, lower morale, and decreased performance. Nearly one in four (23%) survey participants spoke with a financial adviser in the previous three years. Plan sponsors can help employees with their financial well-being by making their retirement plans more than just a vehicle for saving. A nuanced emphasis on financial wellness can not only improve employee financial health but also foster greater productivity and talent retention. Providing access to group education sessions during the workday, encouraging the use of calculators and other online recordkeeper tools, and facilitating individual consultations with financial educators are all helpful steps. 5. Evaluate Your Recordkeeper The recordkeeper industry is rapidly consolidating while struggling to keep up with a highly active regulatory environment. While some recordkeepers are meeting the challenge, others are falling behind. As part of their fiduciary duty, plan sponsors must regularly evaluate providers on two key dimensions: Services and Products. Plan sponsors analyze the services rendered to determine if they need improvement. For a recordkeeper’s participant website, among other products, plan sponsors might survey participants or even personally test the experience. They should document these findings as part of review meetings at least every year and save them in a fiduciary file for future reference. Fees. A good fee evaluation process compares what a plan charges relative to other plans of similar size in assets and participants that provide similar services to a similar number of people. We engage an independent fee benchmarking service to provide this information to our clients that they can then save in their fiduciary file. If recordkeeping relationships are not meeting their standards, plan sponsors should explore whether other providers are better fits. 6.

The Art in Fundamental Analysis Financial statement analysis represents the art in fundamental equity valuation and helps creditors and investors make better economic decisions. For reporting purposes, corporations prepare statutory statements that combine accounting rules describing the accrual process, management estimates of projected events based on past experience, and managerial judgment that is subject to a cost-benefit rationale. Corporate press releases about quarterly earnings announcements reflect this. The net earnings per share number, which ultimately increases shareholder equity, is mostly neglected in management discussions and analysis. Indeed, alternative numbers based on massaged earnings information tend to be the focus. The current use of pro-forma, or alternate, numbers to represent true operating earnings stems from corporate management’s need to meet earnings estimates and support stock prices for companies that have little or no positive net earnings to report. This is why we need to reconnect the economic implications of accounting for depreciation with goodwill amortization / impairment charges, which are universally assumed to be non-cash charges, and other one-time charges. The Case for Pro-Forma Adjustments That pro-forma earnings supposedly reflect a business’s true performance is the basis for their theoretical support. However, accounting earnings, as the accepted language of business, do reflect true economic performance. Let me explain. Depreciation reflects a decline in an asset’s value and in the future benefits that owning the asset confers due to normal business usage. As a charged expense, depreciation is accounted as an earnings reduction. But without a corresponding cash outflow, adding to earnings to compute economic (cash) income or cash flow from operations may be justified. Depreciation Accounting When an asset is purchased Asset = (Cash) (a) When depreciation is recorded Depreciation = Asset – Depreciated Asset (b) Substituting (a) in (b) Depreciation = (Cash) – Depreciated Asset (c) From (c), always (Cash) > Depreciated Asset (d) From (c) and (d) Depreciation = (Cash) (e) Or, (Depreciation) = Cash (f) Note: Parentheses represent a negative number or outflow. A merger or acquisition generates goodwill when the purchase price, or transaction value, exceeds the fair value of the net assets acquired. Whether cash, stock, or some combination thereof is exchanged, the goodwill amount recorded from the transaction is the same. It thus represents the intangible expected future benefits to the acquiring entity of integrating the target entity’s operations. Since goodwill amortization / impairment represents the reduced future benefits from ownership of the net assets acquired, it is charged as an expense to current income. However, since no corresponding cash outflow occurs, it may be reasonable to add to earnings in calculating the economic — read: cash — income or cash flow from operations. Goodwill Accounting Assuming goodwill is createdby a cash acquisition When a company is acquired Net Assets Acquired + Goodwill = (Cash) (g) By rearranging (g) Goodwill = (Cash) – Net Assets Acquired (h) From (h), always (Cash) > Net Assets Acquired (i) From (h) and (i) Goodwill = (Cash) (j) When goodwill is written off (Goodwill) = Cash (k) Note: Parentheses represent a negative number or outflow. The Case against Pro-Forma Adjustments Both depreciation and goodwill amortization / impairment charges reduce reported earnings and, as a pass through effect via retained earnings, diminish equity accumulation. So, to examine the validity of the premise of depreciation and goodwill amortization / impairment adjustments for reconciling accounting earnings to economic income (EBITDA or cash flow analysis), the case must be made in economic terms. Framework for Illustrating Corporate Activity Relationships Asset accounts affected by the purchase of an asset or purchase method acquisition Cash Net Assets Acquired Equity accounts affected by a purchase method acquisition Shareholders’ Equity comprising Equity Share Capital, Share Premium (APIC), and Retained Earnings Nominal account depicting a diminution in future benefits from a purchased asset Depreciation Nominal account representing a diminution in future benefits from acquired net assets Goodwill The Logic Gap Pro-forma income analysis converts accounting earnings into economic income. But there is some cognitive dissonance: Economic theory is a decision-enabling mechanism for the rational allocation of scarce resources — cash in this case — among alternative uses. In economic analysis, investments in any tangible or intangible assets are just another form of holding cash. After all, the net worth of a corporate entity with $1 million in cash or immovable / intangible property of equivalent value is the same. Barring bankruptcy, corporate entities are theoretically expected to exist in perpetuity. Hence, asset liquidity is not a major consideration in valuation exercises. The nature of its assets makes no difference to the corporate entity as long as their ownership satisfies the shareholder objective of maximizing wealth. Also, given that the purchase of any movable, immovable, or intangible property for cash affects only the asset side of the balance sheet, the individual asset values may change, but the total asset value remains the same. From an economic perspective, absent the accounting language for business transactions, the whole process translates into the economic (cash) income model and cash flow computations. Simplified Accounting Statements Balance Sheet at the beginning of the given financial year Equity Capital 200 Cash 100 Retained Earnings 100 Fixed Assets 200 Total 300 Total 300 Income Statement for the given financial year Sales 500 Expenses 300 Depreciation 100 Net Income 100 Cash Flow from Operations for the given financial year based on the above Net Income 100 Depreciation 100 Total 200 Balance Sheet at the end of the given financial year Equity Capital 200 Cash 300 Retained Earnings 200 Fixed Assets 100 Total 400 Total 400 The exhibit above presents the basic accounting statements used for reporting purposes in any given year and is simplified for illustration’s sake. To calculate cash flow from operations, depreciation charges are added to net income. Mathematical Representation of Income Statement S – E – D = N   (01) Where, S = Sales Expenses = Expenses excluding Depreciation D = Depreciation N = Net Income Also (01) can be rewritten as: S – E = N + D   (02) The reformulation in

Dynamic and “emergent” complex systems. can be found everywhere from ecosystems to economies to our underlying biology. By striving to understand the way these systems work, we can make sense of the world in which we live and better prepare for future events. This approach is known as systems thinking, and it is gaining in popularity in many fields including economics, finance, and investment management. Read this blog post to learn about systems thinking and how it can be applied to sustainable investing. Systems Thinking in the Financial Markets Scholars and practitioners have described financial markets as complex adaptive systems (CAS) in which many different participants within the system “constantly change their actions and strategies in response to the outcome they mutually create.” Central to this notion is the idea that discrete actions of system participants or components modify the overall behavior of the system in a way that is more than the sum of those participant or component parts. This concept is called “emergence,” and what emerges at the system level is referred to as the system’s “emergent properties.” In the realm of financial markets, outcomes are more than the aggregation of individual investor decisions. Interaction among the participants within the investment process — buyers, sellers, brokers, dealers, analysts, managers, or advisers — generates behaviors at the system level. The resulting emergent properties might include market volatility, risk, and return distribution. These patterns are particularly relevant given the increased market share of index funds that track broad market movements. Financial markets are especially complex because systems are embedded within other systems in ways that produce emergent properties at each level. Equity mutual funds, for example, are collections of different stocks modified by fund managers at varying times that produce emergent, fund-level risks. Likewise, hedge funds are systems of activity of investors and hedge fund managers who produce emergent hedge fund strategies that impact the broader investment ecosystem. An important thing to remember is that emergent properties then shape the subsequent activities of underlying market participants who, through their interactions, generate market-level volatility, risk, and return characteristics. In turn, the new market characteristics shape future activities like buying/selling of securities, reallocation of portfolios, and the ability of companies to raise capital. Exhibit 1 demonstrates the emergence of system-level features from individual or component “agent” interactions (bottom-up causality) and the influence of those emergent features back onto agents (top-down causality). Exhibit 1. Bidirectional Influence of Agent-level and System-level Features Emergent properties in finance are significant because they allow us to understand noteworthy events in market behavior like financial bubbles and crashes. Notably, emergence is happening all the time, not just during times of high volatility. Sometimes, the underlying dynamics of the system reinforce ongoing stability in the market. In the world of dynamical systems — where all possible states of the system are mathematically modeled as vectors across a state space — stability can manifest as an “attractor” toward which the unfolding system gravitates. Constraints Matter Systems thinking offers new insights for analyzing past market behavior. Beyond tracking historical trends in the market, we must also consider historical constraints. Unlike direct causes, constraints work by shaping the possibility landscape. Although constraints may carry a negative connotation because they are generally understood as restrictive, some constraints open new possibilities within the system. Referred to as “enabling constraints” by scientists, they influence interactions that drive the system toward a particular emergent state that would otherwise be unavailable. Consider what happens when a roundabout replaces stop signs at an intersection. This constrains the behavior of each car. Stop signs facilitate stop-and-go coordinated behavior from their constituents, whereas roundabouts constrain movement to enable a slow, ongoing flow of traffic within the circle. Stop signs require each driver’s attention to be oriented to cars in multiple directions, whereas roundabouts demand attention to oncoming traffic in one direction. Importantly, the newly constrained patterns of traffic flow enable a drastic decrease in the likelihood of accidents. Put simply, roundabouts constrain patterns of behavior in ways that alter the probability of car crashes and bring about new system-level interactions that are unavailable with stop signs. In finance, we often seek out direct causal forces to explain crises. An example is the 2008 housing market crash. We might consider the foreclosures of subprime mortgages in mortgage-backed securities to be such a direct cause. But constraints have a unique role to play in the causal story because they facilitated the likelihood of a system-wide crash. Lenders were subject to lax underwriting standards and disclosure requirements, which increased the likelihood of offering loans with unconventional, higher-risk terms. While low- and middle-income households depended on home ownership as a primary source of financial security, many of these homeowners were unfamiliar with the risks associated with unconventional loans. In addition, the low interest rate environment drove a wide range of lenders and consumers across the United States to refinance existing loans with non-traditional and adjustable-rate mortgages (ARMs). Lenders and consumers became entangled in a web of risk layering where unconventional terms such as no-downpayment, interest-only, and piggyback loans were combined. In systems thinking parlance, market participants engaged in a vast network of loan agreements that constrained their future behavior and produced “a geometric increase in the propensity to default.” The growing network of ARMs established pre-2008 served as enabling constraints within the system, producing levels of risk within the housing market that were unforeseen. Importantly, enabling constraints are context dependent. In the roundabout example, the constraints that produce fewer vehicle accidents are well documented. In locations where cyclists are common among cars, however, roundabouts increase bicycle-related accidents. Thus, constraints in one context might have a different effect in another context. While ARMs themselves are not inherently problematic, when placed in the context of unsustainably low interest rates followed by rate resets and falling housing prices, the chance of mass foreclosures leading to a market crash was high. A recent publication also emphasized that the probability of a market crash was grossly underestimated because

The Case for Long-Term Value Investing: A Guide to the Data and Strategies That Drive Stock Market Success. 2022. Jim Cullen. Harriman House. The bright yellow dustjacket of Jim Cullen’s The Case for Long-Term Value Investing suggests either caution or sunshine. On the cautious side, investors acknowledge that market-exposed assets lost value in 2022 and question whether they ought to liquidate and run for the hills or follow a discipline that will fulfill investment objectives over the long haul. On the sunny side, Cullen proposes a discipline that should produce satisfactory risk- and inflation-adjusted returns over a five-year period, if not much longer. Cullen is a rare author among contemporary active asset managers, with a career of 60 years in investment management. His lifetime provides a scale of experience that few have, and he generously shares it here, supported by analysis, backtesting, and memorable stories of investments gone well or awry. The simple style of presenting the value strategy and how to apply it in any type of market will convert many who doubt its success into believers. What is long-term value investing? It is clear that Cullen defines “long term” as at least five years. Ignoring that perspective highlights numerous short-term melt-up markets that leave value stocks in the dust. Examining longer periods reveals a far different picture. Cullen presents abundant data covering very long stretches of time, generally concluding in 2020. Sticking to long-term investment goals rather than chasing momentum for fear of missing out leads to higher performance than growth investing provides. The rolling five-year basis that Cullen emphasizes smooths performance and sheds light on the growth/value debate. He makes a compelling case for a long and steep downside for growth stocks when they ultimately correct. The author’s examination of the lowest P/Es (the bottom 20%) and the highest dividend yields (the top 20%) also considers growth of earnings and dividends over time, encouraging focus on the stock rather than the stock market. Emphasis on the lowest price-to-book ratios further boosts the case he makes for value. Many of us question the valuations of assets reflected in book value, with an extreme example being bank and financial assets before and during the financial crisis of 2008–2009. Outside of traditional industries, such as airlines, metals, and energy, and acknowledging the dominance of the tech era, with its high or non-meaningful price-to-book ratios, low price-to-book can be an effective screening tool. The lowest price-to-book ratios of the S&P 500 Index performed quite nicely alongside the lowest P/Es and the highest dividend yielders, except in individual years during bubbles or melt-ups. The graphic evidence is presented convincingly in a chart depicting “The Three Disciplines” and how they performed in each year from 1968 to 2020. As astute as Cullen is in convincing us of the realities of value investing, he also provides thoughtful analysis of inflection points in markets based on such critical considerations as government, corporate, and individual debt levels; the level and direction of interest rates; and consumer confidence. In reviewing the current data, readers may come away assured that the current bear market might not prove long lasting, especially for those who focus on valuations, earnings, and dividend growth and stay the course. Cullen considers market timing the silent killer of investment performance, especially in the case of “strategic” shifts to cash and attempts to improve returns. The shifts to cash that he addresses are those that last for a month or more. Just a few moves out of the market can result in substantial investment underperformance, especially in frightening times of extreme illiquidity and deep recession. Two other points require mention. Value investing is applicable to all capitalizations and geographic areas, including emerging markets. Small-cap value has done remarkably well over the long term owing to the frequency of takeovers. Covered call writing can usefully come into play, considering the sharp drop in bond yields occasioned by a 30-year bond bull market, even as interest rates creep up. Cullen shares a covered call writing strategy for tax-exempt investment accounts that enhances portfolio performance, as opposed to investing in selected bonds solely for income. A section titled “Getting Started — New Investors” occupies just a few pages before the book’s final note. I found it to be hugely entertaining and educational. The author highlights saving, investing, and the beauty of compound interest. Most readers will find it startling that he recommends annual investment contributions until age 80! My suggestion to the new investor would be to aim for this long contribution period but if that is not possible, to attempt at least to reduce expenses by the amount one cannot continue to contribute to investments. After reading his well-presented case for long-term value investing, testing for additional periods beyond those published, and reviewing recent economic data with a critical eye as Cullen does, I agree with him that this is a book for all investors. This is so even though analytically inclined investors will likely go beyond his stated criteria for security selection — that is, the lowest P/Es and price-to-books coupled with the highest dividend yields. If you liked this post, don’t forget to subscribe to the Enterprising Investor. All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer. Professional Learning for CFA Institute Members CFA Institute members are empowered to self-determine and self-report professional learning (PL) credits earned, including content on Enterprising Investor. Members can record credits easily using their online PL tracker. source

US government money market funds have enjoyed record inflows this year as their 5%-plus yields — the highest in decades — and lower-risk status have obvious appeal for investors.  But we believe intermediate high-quality bonds may offer an important and compelling option for clients’ longer-term portfolio allocations thanks to their historically elevated yields, longer duration profiles, and potentially negative return correlation with equities and other higher-risk assets. 1. Yields are at a 16-year high. Yield is often the best predictor of a bond’s total return over the intermediate or longer term, and the yield of the Bloomberg US Aggregate Index (Aggregate Index) may represent an attractive valuation entry point for investors. In contrast, yield is not a good predictor of longer-term returns for money market funds. After all, money market interest rates can change on a daily basis and pose reinvestment risk over short time horizons. Moreover, the market has recently pushed out major rate cuts into the second half of 2024. But if the economic outlook deteriorates more quickly than is currently expected, the US Federal Reserve could slash short-term interest rates sooner, further compromising money market yields and total returns. Looking ahead, we believe investors should consider the value longer-duration bonds may offer in a future environment marked by federal funds rate cuts beyond what the market has currently priced in. While cash offers limited upside, as previous results indicate, the Aggregate Index could generate an intermediate-term total return in excess of today’s yield. 2. Duration has traditionally benefited from falling interest rate environments. While the Fed has pledged “higher for longer” short-term rates, should the economy fall into recession over the next year, they may choose to cut rates sooner than currently expected. High-quality bond market total returns have tended to outperform in falling interest rate environments. Why? In part, because of the longer interest rate duration profile. Money market funds, on the other hand, do not have significant duration exposure and will gain little benefit from a move lower in interest rates. As the following exhibit demonstrates, when the Fed has eased monetary policy over the past 25 years, it has cut interest rates quickly and sharply. In periods like the present, when rates exceed 5%, rate cuts have totaled 4.5% to 5% over an approximate 1.5-year period. The fixed-income markets currently forecast federal funds rate cuts of less than 1% over the next 1.5 years. During past Fed easing cycles, the Aggregate Index outperformed cash by a considerable margin, even amid the global financial crisis (GFC) when credit spreads widened significantly. When the Fed Cuts Rates, Intermediate Bonds Have Benefited Source: Bloomberg as of 5 May 2023 Data represent past performance, which is no guarantee of future results. Rate cut cycles begin with the date on which the Fed cuts rates and end with the lowest rate in each cycle. Bloomberg indices represented include three-month Treasury bills, five-year Treasury bills, and the US Aggregate Bond Index, a measure of the US bond market. Indices are unmanaged, and their returns assume reinvestment of dividends and do not reflect any fees or expenses. It is not possible to invest directly in an index. In other words, intermediate bond duration has tended to dominate credit spread movement in recent rate-cutting cycles. Once the Fed has reached its terminal rate, longer-term yields have usually declined as investors start to discount lower forward interest rate expectations. US 10-Year Treasury Yields after the Fed Paused 3. The value of the longer-term negative return correlation relationship between bonds and equities can be valuable for portfolio construction. Historically, high-quality bonds tend to act as the portfolio “anchor,” giving investors the stable income and relatively low or negatively correlated returns to equity market returns. That relationship was upended in 2022. During the fastest and largest interest rate increase cycle since 1974, bond and equity prices moved largely in tandem and sustained historic losses. As the Fed nears its terminal rate, we believe high-quality bonds are well positioned to reassume their traditional role as a portfolio “diversifier.” Bonds Have Shown Negative Return Correlation with Risky AssetsReturn Correlations of Bonds vs. Stocks Sources: Bloomberg and Amundi US as of 30 September 2023. The return correlation relationship displayed above illustrates the valuable role bond exposure can play in reducing portfolio return volatility relative to money market funds.  With higher yields and income, the classic 60/40 equity/bond allocation could once again become the dominant target for investors. Looking Ahead In the wake of the Fed’s unprecedented interest rate hikes in 2022 and 2023, investors are now presented with an opportunity to consider historically elevated yield options across the entire yield curve. While many investors understandably focused their initial attention on money market funds in search of safety and yield, intermediate bonds now offer a compelling alternative when considering potential benefits from elevated income, total return, and portfolio diversification. While the Fed’s ultimate short-term interest rate path is somewhat uncertain, we believe the current tightening cycle is nearing its peak and, in response, investors may be well served by extending the duration of their fixed-income exposures. If you liked this post, don’t forget to subscribe to Enterprising Investor. All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer. Image credit: ©Getty Images / PashaIgnatov Professional Learning for CFA Institute Members CFA Institute members are empowered to self-determine and self-report professional learning (PL) credits earned, including content on Enterprising Investor. Members can record credits easily using their online PL tracker. source

Investors tend to view an index fund’s tracking error in a purely negative light. When a fund fails to track its benchmark especially well, investors’ assumption is that the fund manager is probably bad at their job. But there could be another story here. Maybe the fund manager is allowing some tracking error as a means of avoiding taxable events. After all, every time a fund manager sells or rebalances a position to track the benchmark index, it constitutes a taxable event that will diminish the fund’s post-tax performance. So, do index funds with lower tracking error have better or worse post-tax performance? To investigate this issue, we pulled data on all US-dollar-denominated index mutual funds across six different asset categories: large-cap equities, emerging market equities, fixed-income, small-cap equities, US value, and US growth. We then assigned each fund with a tracking error designation: high, middle, or low. For each category, we calculated both the median return and the median post-tax return over the past five years. We defined tracking error as the standard deviation of the difference between the returns of the fund and those of the tracked index over an annual time frame. So, what did we find? Large-cap equity, emerging market, and fixed-income funds with high tracking error exhibited better post-tax performance than their low tracking error counterparts. Large-Cap Funds Tracking ErrorCategory Median Five-YearReturn Median Five-Year Post-Tax Return Low 9.66% 4.74% Middle 10.43% 7.83% High 10.44% 7.88% Emerging Market Funds Tracking ErrorCategory Median Five-YearReturn Median Five-Year Post-Tax Return Low 0.36% 0.08% Middle -0.53% -0.70% High 0.78% 0.35% Fixed-Income Funds Tracking ErrorCategory Median Five-YearReturn Median Five-YearPost-Tax Return Low 0.62% 0.17% Middle 0.90% 0.30% High 1.12% 0.66% For instance, the low tracking error category of large-cap equity funds had a 4.74% annualized post-tax return over the past five years, while its high tracking error counterpart generated 7.88%. But this isn’t the full story. In the small-cap, value, and growth fund categories, the results were completely different. For each of these asset classes, low tracking error funds did tend to exhibit better post-tax performance. For instance, high tracking error small-cap funds had a 4.99% median annual return over the past five years, compared with 5.77% for their low tracking error peers. Small-Cap Funds Tracking ErrorCategory Median Five-Year Return Median Five-YearPost-Tax Return Low 7.35% 5.77% Middle 5.36% 3.72% High 6.76% 4.99% US Value Funds Tracking ErrorCategory Median Five-YearReturn Median Five-YearPost-Tax Return Low 8.72% 6.11% Middle 7.84% 5.52% High 7.25% 4.34% US Growth Funds Tracking ErrorCategory Median Five-YearReturn Median Five-YearPost-Tax Return Low 11.37% 7.96% Middle 12.24% 9.44% High 10.67% 6.17% So all in all, our examination revealed mixed results. We didn’t find that a fund’s tracking error was a good predictor of post-tax performance. Low tracking error did not seem to be an indicator of index fund quality, although higher tracking error may, in certain situations, help funds avoid taxable events and thereby boost post-tax returns. If you liked this post, don’t forget to subscribe to the Enterprising Investor. All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer. Image credit: ©Getty Images / matejmo Professional Learning for CFA Institute Members CFA Institute members are empowered to self-determine and self-report professional learning (PL) credits earned, including content on Enterprising Investor. Members can record credits easily using their online PL tracker. source