Best Practices for Equity Research Analysts by James Valentine

This was a fantastic book for anyone looking to get into equity research analysis. It is, by far, the most highlighted book I own. I will probably re-read this in a couple years and every couple years thereafter.

James takes you through soft skills, hard skills, and considerations for publishing analysis. He also uses very thorough footnotes and references. Highly recommend this book, 10/10.

Much of the book is rock-solid wisdom disguised as common sense.

(All words in italics are mine. Everything else is from the book.)

If we knew what it was we were doing, it would not be called research, would it?—Albert Einstein

Introduction

Here are some of the more pronounced situations where equity analysts go wrong, which could be avoided by adopting best practices:

  • Cover too many stocks or fail to effectively manage inbound information flow, which reduces the likelihood of identifying unique insights required to generate alpha.

  • Fail to understand the critical factors likely to drive a stock, which leads to spending too much time on factors that won’t move a stock and too little time on those that will.

  • Don’t develop the unique industry contacts and information sources required to make differentiated stock calls.

  • Don’t understand how to interview a management team or industry contacts in a manner that extracts unique insights.

  • Fail to understand how companies and the media can deceive through numbers, thus missing opportunities to avoid “the blowups.”

  • Generate financial forecasts with no basis other than an inexperienced gut feeling or company management guidance, leading to earnings and cash flow forecasts well above realistic levels.

  • Apply premiums or discounts to valuation multiples on an arbitrary basis.

  • Communicate stock messages ineffectively, either by being too verbose or failing to identify how the analyst’s work differs from consensus.

  • Make poor ethical decisions due to a lack of understanding of how to spot and defuse conflicts of interest.

The best practices that follow are intended to help analysts avoid these mistakes as well as overcome typical challenges more easily. They’ve been divided into the five primary areas of the equity research analyst’s role, as highlighted in Exhibit I. 1. 1. Identify and monitor critical factors 2. Create and update financial forecasts 3. Use valuation methods to derive price targets or a range of targets 4. Make stock recommendations 5. Communicate stock ideas

analysts need to effectively communicate their message if they are to be rewarded for their efforts.

Be skeptical, very skeptical, and even more skeptical. Great analysts rarely accept anything at face value.

Beyond sheer intelligence, properly prioritizing your time is the single biggest factor that separates the good from the great. We all have the same 24 hours per day to find the 2 percent of information that matters, but some have figured out how to use the time better than the rest.

It’s tough to beat the market. In doing so, don’t look for shortcuts or quick answers as a substitute for thorough research, because they don’t work—at least not consistently. If they did, capital would be attracted to these “easy money” strategies until all of the alpha was captured.

Fear is more powerful than greed, but they are both important to watch. When you see others becoming fearful, look for opportunities. When you see others becoming greedy, look for an exit.

When it comes to the investment process, simplicity trumps complexity. The more complicated the model, catalyst, thesis, etc., the greater the likelihood something will go wrong.

Don’t mistake news for research:

Experts in the press often aren’t; they may simply be the person who had time for an interview.

Chapter 1. Do You Have What It Takes to Be a Successful Analyst?

When compared with novices, senior analysts:

  • Thoroughly understand inputs to their company’s production or creation of their service and the primary markets to which the company sells.

  • When recommending a stock, place more focus on the factors where their view is distinctly different than consensus.

  • Are more comfortable articulating the strategies of all the companies they follow and how they differ from their competitors.

  • When their price target materially differs from the current price, they know where their assumptions differ from the market’s.

  • Fully understand the peak and trough valuation levels for their companies going back at least 10 years.

  • Are more realistic in appreciating that even the best stock pickers don’t have 100 percent of the information necessary to make a stock call.

When compared with novices, senior analysts self-assessed themselves to be:

  • Less likely to have a calm disposition.

  • Less willing to find common ground in times of conflict.

  • Not as good at developing and maintaining relationships.

  • Less likely to encourage feedback from others.

Generating alpha is all about determining where consensus is wrong, a concept that often gets overlooked by less experienced analysts.

When making stock calls, rarely do they have all the information needed. In terms of personality, they tend to be headstrong, independent, and easily roused.

I’m not saying all great analysts are introverted, but rather they need to work and think independently to generate alpha.

Here are some attributes of great equity research analysts:

  • Intelligent: You don’t need to be the smartest person in the room, but given the intense competition, great analysts need to have above-average intelligence. Those analysts who retain what they learn, and can recall it at a later point when needed, are likely to generate more alpha than those who can’t.

  • Innately inquisitive: As children, their parents may have complained that they were asking too many questions or taking apart things that weren’t broken. Friends ask, “Why do you want to know that?” Great analysts are always asking why in an effort to determine where consensus could be wrong.

  • Self-motivated: There are tens of thousands of other professionals all looking for the same alpha-generating ideas, which means the winners need to be naturally motivated to jump out of bed before 6 a.m., be at their desks by 7: 30 in preparation for their morning meetings, and willing to work evenings and weekends to develop an edge.

  • Self-directed/ resourceful: Akin to reading all of the books in the library, the daily tasks of financial analysis can go into infinitesimal directions, most of which are dead ends. Great analysts don’t wait for their managers to tell them the next steps to take or to notify them when they’ve reached a dead end.

  • Focused: There are many distractions in the world of equity research that can consume an entire day but add nothing to the pursuit of alpha. Learning to stay on task and ignore distractions is a big part of the job.

  • Risk-taker: All great stock calls require the analyst to be out-of-consensus, essentially telling the rest of the world it’s wrong. Waiting for a more comfortable situation, when additional information becomes available, is usually too late because it immediately gets incorporated into the stock price. Great analysts are not uncomfortable when their well-researched thesis is in disagreement with others.

  • Influential: We spend a lot of time on spreadsheets but being an equity research analyst isn’t just about the numbers. It’s also about the people behind the numbers. Much of financial analysis is obtaining good information to make future assumptions, which is facilitated by having an extensive network of contacts. The three areas where it’s needed most are (1) getting information from management, (2) getting information from industry sources, and (3) conveying stock ideas to portfolio managers (PMs) (and clients and salespeople for the sell-side). In general, the more influential (charismatic by some definitions) an analyst is, the broader his or her network is, leading to better analysis.

Part 1: Mastering Organization and Interpersonal Skills

Closely cover means the analyst is expected to have a price target (or fair valuation range) derived from a thoughtful earnings or cash flow forecast in order to maintain an edge over the market. If the firm doesn’t expect this of the analyst, then more stocks can be covered, but this approach causes me to wonder how the analyst develops an edge. Buy-side analysts who are expected to always have current, fully integrated financial forecasts for every company under coverage, or to publish regularly to an internal system may struggle to cover 35 to 50 stocks, especially when new.

  • Many buy-side firms will expect their analysts to watch a large number of stocks, but only cover a small subset of that figure. If watch means to have a view only when there is a major news event, then more names can be covered.

  • When stocks are more homogeneous, a greater number can be followed. For example, oil stocks generally move as a group due to one factor: oil prices. Whereas biotech companies move almost completely independently of one another due to the unique patents and FDA approvals for each company. To test for this, conduct a correlation analysis of the daily or weekly closing prices for individual stocks within a universe over an extended period of time. Those with high correlation are likely being driven by a common factor and thus likely easier to cover.

  • Similarly, if stocks all belong in the same food chain, more can be covered than if they are completely unrelated. Following handset manufacturers, their parts suppliers, and wireless carriers will produce more synergy than having an analyst covering an unrelated basket of cyclicals such as forest products, autos, and chemicals, where few factors run through all of the stocks.

  • The levels of trading volatility and news flow for a sector will dictate how challenging a sector is to follow. When I was asked to add airlines to my coverage, I declined each time, in part because the news flow and volatility are so much higher than the rest of the transportation sector that it would have led to weaker coverage.

Once past the list of obvious candidates (e.g., after McDonald’s and Yum! Brands there is a big drop to the next publicly traded restaurant), find stocks that have these qualities:

  • Best match the requirements of the firm or clients, such as investment style or market capitalization.

  • Are less followed and have the possibility of surprising on the upside (studies show companies that are tougher to follow have fewer analysts, which arguably leads to more alpha opportunities).

  • Offer a broader window into the sector because they are a customer or supplier to the larger companies, or because they offer more disclosure. Food chain analysis is one of the best ways to develop unique insights.

  • If there are still too many stocks to cover, analysts should satisfy their personal curiosity by following stocks of interest, because they’ll dig deeper into stocks they find intriguing.

Everything analysts do during the day should help achieve the primary objective of identifying mispriced securities,

If the activity doesn’t meet this objective, stop doing it.

Here are just a few areas where analysts often use their time ineffectively:

  • Reading news feeds or e-mails that don’t add value to generating alpha (i.e., there’s nothing new). As one senior analyst put it, “If you chase all of the news flow and data points, you may miss the critical data that will actually drive a stock.”

  • Watching stock screens beyond a cursory look.

  • Attending sessions of an investor conference that aren’t likely to yield new insights.

  • Sell-side only: speaking with clients who ultimately aren’t paying for the analyst’s time.

The analyst who is on the offensive learns to ignore most, if not all, of the noise, so as to explore unique avenues that may lead to great stock picks.

Don’t forget that in order to maximize wealth on the buy-side or sell-side, an analyst must become a stock analyst, not an industry analyst.

Successful analysts spend as much of their day on conducting research offensively, specifically focusing on activities that help discover unique insights about critical factors. Some people might call these activities the proprietary aspect of research or the core to developing an edge. Examples include the following:

  • Making outgoing calls to information sources to get updates on critical factors

  • Reading industry journals for ideas and to find names of potential new information sources

  • Comparing spreadsheet data in a manner or format not easily available to the financial community

  • Forecasting earnings based on observations not readily available to the broader markets

  • Reading company regulatory filings for a specific issue in an effort to come up with a unique perspective on a critical factor (not just read filings to check the box)

  • Attending an event not marketed to the financial community that is “target rich” with investment-significant insights about critical factors

  • For the buy-side, calling key sell-side analysts for updates on critical factors

Learning the basics about a company is important early in the process, but the way an analyst works should evolve over time.

there’s one time management technique that deserves special attention: turn off pop-up e-mail and instant message alerts. Unless you’re in a trading environment, they only serve as a distraction. A study by Microsoft shows that it takes up to 15 minutes to refocus on a task after you’ve been distracted, which is what potentially occurs every time you click on a message alert. According to Basex, an IT consulting firm, the typical desk employee loses 2.1 hours of productivity each day due to these distractions. Entrepreneur magazine identified this problem in an article on the topic (Robinson, 2010: 61): As workers’ attention spans are whipsawed by interruptions, something insidious happens in the brain: Interruptions erode an area called effortful control and with it the ability to regulate attention. In other words, the more you check your messages, the more you feel the need to check them—

As part of good time management skills, analysts should plan their upcoming week in advance, at a time when there are minimal distractions such as end-of-day Friday or Sunday evening. This can be facilitated best by creating a recurring weekly calendar appointment for preparing for the upcoming week. It may seem like overkill, but it’s these little steps that bring discipline into the work flow, which is missed by many in the financial community who fail to add value. Here are some activities the analyst should consider for that recurring event:

  1. Review and block out time for upcoming obligatory appointments (ones where the analyst is required to attend) including travel. RSVP to those requests that require a response.

  2. Spend a minute or two reflecting on, “What unique insights did I proactively find this past week that will help generate alpha?” If the answer is routinely “none,” then more discipline needs to be put into the schedule.

  3. For analysts who discover in hindsight that all they do on most days are defensive activities, they should try blocking out time in their calendars for conducting proactive proprietary research. This should be scheduled during the times of the day when the analyst is most productive, whether that is due to personal preferences or fewer distractions. The frequency of this activity should be increased over time, especially as the analyst gets to know the sector and companies better. When possible, the analyst’s phone should be set to forward calls to voicemail in order to reduce distractions; for those working in a space without walls, put on a headset so people walking by think you’re on a call. At a minimum, screen inbound calls and only answer those individuals returning calls or with a proven track record of helping to produce insights.

  4. For those managing a team, ensure the team members are following a similar process.

in general, if an activity doesn’t help to understand critical factors but is required to do the job, attempt to do one of the following: delegate, automate, or outsource.

The key to avoiding burnout is to be aware of balance. It’s more difficult than it sounds, and often requires self-reflection or input from close friends. Here are some of the questions that should be periodically asked:

  • Are you enjoying activities outside of work?

  • Do you find yourself regularly in conflict between professional and personal goals?

  • Are you becoming annoyed with your job?

  • Do you genuinely celebrate personal and professional victories?

There are dozens of time management classes out there, but the two gold standards are Getting Things Done and FranklinCovey’s FOCUS program. Each offers a one-day seminar (for a fee) to master its unique time management system.

replacing the simple to-do list with a series of context-sensitive action lists, specifically: calls, errands, at home, at computer, agenda, waiting for, anywhere, someday/ maybe. If the action requires online research or a call to a portfolio manager, organize that task according to its appropriate category. Included in all of this are the tasks where you can’t yet act—waiting for and someday/ maybe. All of these lists are intended to live in one location, such as your Outlook tasks, Google Tasks, or Lotus Notes. Externalizing all tasks and projects to one system is intended to free up the mind to think creatively, innovatively, and freely.

Time Management Tips for Equity Research Analysts

  • Implement the prioritization skills taught in time management classes. (GTD and FranklinCovey are two of the better ones offered nationally.)

  • Plan your week in advance. (It will never play out exactly as planned, but having no plan puts your valuable time at risk of being wasted.)

  • Prioritze the types of events to put on your calendar, choosing more offensively focused events over defensively focused events.  Offensively focused events are those where proprietary insights are most likely to be found:–Private or small group meeting with industry expert–Visit with company management–Industry conference where few analysts are in attendance  Defensively focused events are those that likely provide background but not alpha-generating insights:–Quarterly earnings conference calls–Sell-side-sponsored investor conference (assuming no one-on-one meetings with management)–Site tour, especially when no senior management are present

  • Plan travel intelligently:  Once the companies are understood, attend only the portion( s) of events that are likely to help you identify or understand the critical factors.  Leverage time on a trip by trying to accomplish more than one goal. (If you’re going to be traveling, try to have more than just one meeting.)

  • Use time out of the office wisely; commuting and travel time can easily comprise 20 percent of the work week. Make sure to use this time for more than just reading the financial press.

  • During offensively focused research time, send all calls to voicemail, shut the door, or if in a common area put on headphones (or a headset) to make it clear to you and others that you don’t want to be disturbed.

  • Screen all in-bound phone calls, only taking calls from those who add insight or are responding to your questions.

  • Turn off pop-up e-mail and instant message alerts.

  • Unless in a trading environment, look at your stock screen only a few planned times per day (e.g., at the open, lunch, and near the close or every hour).

  • When possible, skim conference call transcripts rather than listen to the entire 45-to 60-minute event.

  • If a regular daily task is required to conduct research or communicate your message, but is of low value, consider delegating, automating, or outsourcing.

  • Periodically self-reflect to ensure that you’re not on a road to burnout.

  • Be smart about setting up an information hub to maximize insights and minimize noise. (Refer to Exhibit 5.3 for an in-depth discussion.)

  • Don’t spend time speaking to the press unless:

    • The journalist provides insights

    • Your ego badly needs gratification

    • It will improve your year-end review (which in most cases, it won’t)

  • Buy-side only:

    • Avoid attempting to read every sell-side report on every company and instead find the two to three analysts who meet your needs (Bloomberg, StarMine, and FactSet have features to identify sell-side analysts who are the best at forecasting earnings and stock picking). Watch for ratings changes or other big think pieces from the rest of the sell-side.

    • Unsubscribe from information services and analysts’ distribution lists if they don’t add value.

    • Avoid taking calls from those with an unproven ability to add value. (Let them go to voicemail until they begin to add value.)

    • Routinely remind sell-side salespeople of your interests and how they can add value.

    • Utilize sell-side or third-party financial models when it doesn’t compromise accuracy or insights (see discussion in Chapter 17), such as:

      • Creating the model architecture in terms of what’s important

      • Building historical data

      • Updating quarterly data

  • Sell-side only:

    • Return all non-time-sensitive calls at one block of time during the day (e.g., from 2 to 4 p.m.), delegating some of the less important calls to a junior member of the team.

    • Learn how to say no diplomatically (e.g., telling a salesperson you’re not doing lunch with a small client).

the most effective analysts are those who can influence others.

It usually takes much longer to establish credibility than to lose it. As such, be calculating when opening your mouth or putting a thought in writing, ensuring it’s helping you move toward establishing credibility rather than away.

To simplify things when setting up an information hub, an analyst should have a thoughtful strategy in response to these questions:

  • What needs to be collected?

  • Where will it come from?

  • How is it best organized?

The first step should be to create a list of all the services and applications utilized by your firm (e.g., Bloomberg, FactSet, Capital IQ, StarMine), because they are among the most useful weapons on the buy-side and sell-side battlefields. Access to good information and understanding how to receive/ retrieve it when needed is critical to an analyst’s success. Learning how to leverage market data vendor’s applications is time well spent.

At a minimum, have an individual filter/ alert for:

  • Each company

  • Each sector

  • Key words for all of the terms important to your analysis

When entering their contact information, include the following (set up a field for each of these if possible):

  • Where you initially met and who introduced you, if applicable.

  • The person’s specialty.

  • The types of critical factors this person can discuss. (You’ll want this in the record so that you can search on these terms in the future.)

  • Something personal (to use when opening your next conversation).

Chapter 6. Buy-Side Only: Maximize Benefits of Sell-Side Relationships

Most important:

  • Understands key sector factors, including secular changes

  • Understands a company’s competitive advantages and drivers of growth

  • Conveys integrity, professionalism, and trust

  • Is accessible and responsive

  • Provides access to company management

  • Provides insightful and accurate written product and financial models

  • Provides a sound basis for stock recommendations

Moderately important:

  • Provides frequent calls and visits

Not important:

  • Provides superior stock selection

  • Provides superior earnings estimates

Part 2: Generating Qualitative Insights

Chapter 7. Identify Factors That Impact a Sector’s Valuation and Performance

Great analysts are those who work on a more macro level. Most equity analysts are expected to look at stocks from a bottom-up approach. Those who can also look at them from a top-down approach have a competitive advantage.—Drew Jones, former Associate Director of Research at Morgan Stanley

It’s critical to conduct sector analysis in order to put company performance in perspective. Reena Bajwa, equity analyst, UBS Global Asset Management, makes this point when she says, “Understanding the industry and understanding the stocks are two different skills.”

Companies don’t operate in a vacuum; they compete within a sector.

… equity analysts must understand when their sector tends to historically outperform and underperform the market, something missed by many analysts. This critical step is advocated by many successful practitioners, including Drew Jones, who believes, “As the first step of an industry analysis, new analysts should develop a strategic view about the industry.” Portfolio managers want to see this to help frame the discussion. It also helps raise your game in terms of the types of discussions you can have with company management.

Here are the most useful types of analysis to conduct at the sector level:

  • Historical sector-level capacity and demand (and pricing, when available)

  • Historical sector-level financial metrics

  • Historical sector-level outperformance and underperformance compared with broader indexes

  • Food chain analysis

Working backward, valuation is usually driven by the growth rate of cash flows, a function of a company’s volume and pricing; volume and pricing are usually a function of sector capacity and demand. So we start by analyzing capacity and demand, all in an effort to forecast company-level valuation and stock prices.

One way to prioritize the more important capacity factors is to ask yourself, “Which factor has the most impact on changes in sector pricing?” Looked at another way, when sector returns start to improve, what is the first thing the companies expand to grow their businesses? Often, it’s a key piece of equipment or a certain type of employee being hired (e.g., sales, engineering). Once the capacity factor( s) has been identified, it may require obtaining capacity data from foreign companies; for example, assessing U.S. auto production includes volume from foreign producers.

Understanding the volatility and elasticity of pricing will be critically important when it comes time to develop financial forecasts.

If you find yourself getting bogged down trying to get all of the data to fit into one uniform spreadsheet, take a step back and remember that you’re attempting to understand how changes in capacity and demand cause fluctuations in the sector’s valuation. In the end, you may have to compromise and just take data from the sector’s three or four biggest companies, which may not provide an air-tight analysis, but it should help to meet your objective.

Adam Longson, an analyst at Morgan Stanley with a CFA and CPA, believes analysts should “approach a problem from top down as well as bottom up, not just to sense-check your analysis, but also to uncover implicit assumptions or errors that may come from using a single approach. This additional analysis helps you better assess what the Street may be missing.”

Here are some of the sector-level data that will be helpful in building this analysis:

  • Revenue

  • ASP for each major product or service

  • Earnings before interest and taxes (EBIT)

  • Pre-tax income

  • Net income

  • Free cash flow

  • Dividends

  • Net capital expenditures (including acquired leases)

  • Return on invested capital

  • Return on equity

Analyze the historical data to identify when growth rates and returns peak and trough as well as the length of time when stability exists (if it exists at all). Determine when the sector earns or exceeds its cost of capital. Going back to your earlier capacity and demand analysis and using historical macro-economic data (e.g., GDP, industrial production, retail sales), identify if there is a relationship with the sector’s financial metrics. It’s critical to identify the difference between cyclical and secular trends.

To derive useful valuation multiples, you’ll need some form of forward-looking consensus expectation for all the historical points in time, such as consensus earnings per share (EPS) or cash flow.

The overall goal of this analysis is to:

  • Identify periods of sector outperformance and under-performance. (Don’t be tempted to start looking at individual companies just yet.)

  • Isolate whether the relative performance is due to changes in the forward-looking valuation mulitples or changes in the consensus earnings and cash flow.

  • Identify the lead or lag time between changes in relative sector performance and changes in sector fundamentals.

Chapter 8. Identify and Monitor a Stock’s Critical Factors

The toughest part of the job is filtering out the material information from the noise.—Celeste Mellett Brown, a Morgan Stanley analyst with more than 11 years’ experience

The most distinguishing element of great analysts is that they put a disproportionate amount of time into forecasting only a few of the factors likely to move their stocks. This approach turns the traditional company analysis on its head because they’re not attempting to know everything about their companies. The problem many analysts have is that they approach company analysis similarly to college students, highlighting all 300 pages of their textbooks to ensure that everything is understood for the final exam. Great analysts focus their time on only those questions that have been asked in prior exams or, due to a change in the environment, are likely to be asked on the next exam. A seasoned manager of analysts echoes this view with, “There’s an opportunity for analysts to do a better job pre-defining the drivers of a stock and why investors own the stock.”

… it’s important to note that there are two elements of financial metric and valuation analysis, historical and current. The historical element obviously lends itself better to companies with long track records, which due to the natural lifecycle of a business, often equates to value stocks. The current element of the analysis is important for all stocks, but especially for growth stocks because so many of their critical factors are driven by the factors surrounding the company’s sustainable growth rate.

The human mind isn’t very good at deciphering anomolies buried in a page filled with numbers, which is why it’s often helpful to create a dedicated spreadsheet and graphs that show the compound annual growth rate (CAGR) of the key financial metrics, such as revenue; earnings before interest, taxes, depreciation, and amortization (EBITDA); EPS; CFPS, capital expenditures; and depreciation, depletion, and amortization (DD& A). It’s also important to review the change in returns over the time period. Using the DuPont return on equity (ROE) analysis is a good way to see how returns have changed over time based on the three important factors.

The best sources for preliminary information that should be reviewed before having any discussions include:

  • Company documents. (There is likely to be information in the management discussion and analysis [MD& A] section of the regulatory filings to help explain major changes in its financial metrics.)

  • Financial news written at the time of major stock moves.

  • Trade industry journals or websites that include articles written at the time of major stock moves as well as year-end reviews or an annual outlook.

  • Internal documents written by the analyst following the stock at the time of a major stock move.

  • Buy-side only: sell-side reports written at the time of a major stock move.

In order to create an edge, analysts must narrow down their list of factors to those that have good catalysts. Bill Van Tuinen, a seasoned buy-side analyst, looks for catalysts that are big enough to overcome the risks. If a critical factor’s catalyst is a broad-based macro event difficult to forecast, such as GDP or oil prices, it will be almost impossible to gain an edge over the market. As such, look for catalysts that can be identified and quantified through comprehensive research, such as determining the timing and likelihood of new industry regulations or the probability that a company’s new product will be successful. Some of the more common places to anticipate catalysts include the following:

  • Company-sponsored analyst meetings and calls

  • Earnings releases

  • The company’s annual pricing, volume, or earnings guidance or projection

  • Deadlines for new legislation, regulations, or court case outcomes

  • Pre-scheduled announcements by the company’s customers, competitors, or suppliers

  • New product releases or significant product extensions

  • Interim sales data for the company or the sector

Approach your information sources with a strategy, namely seeking out insights rather than waiting for them to surprise you in the form of an unexpected announcement from one of your companies. The strategy employed by Bill Greene, a Morgan Stanley analyst with more than 12 years of sell-side experience, is to “find something where you disagree with consensus and explore to see if it could make a difference in the stock.” One of the most gratifying experiences as an equity analyst is watching a stock react to a catalyst you forecast, well in advance of the market. Investigate the critical factors in order to refine your upside, downside, and base case scenarios (a process discussed later in Chapter 18). To ensure that you’re contacting your information sources in a timely manner on the topics that are likely to move your stocks, create a matrix of critical factors, issues to explore, potential catalysts, contact sources, and frequency of discussion. Review the list regularly to ensure that you’re staying ahead of the competition on the critical factors likely to drive your stocks. Here is an example:

For most analysts, almost every day will include a new piece of information that could lead to an additional critical factor. To remain on task and efficient with time, an analyst should use the flow chart in Exhibit 8.4 to determine if a new critical factor has emerged:

  1. Determine if new information is more likely to be an opportunity or risk.

  2. Briefly surmise the potential impact on the stock from this factor: a. Likely to occur within investment time horizon? b. Material (e.g., move financials more than 5 percent)? c. Will be triggered by a catalyst that can be forecast?

  3. If the factor meets the criteria above, determine if it’s not yet in the stock in terms of consensus expectations or the valuation multiple.

  4. If it meets all of the criteria above, it likely warrants further research to determine if it’s a critical factor.

Periodically challenge yourself to ensure you haven’t become complacent. Similarly, as you’re periodically reviewing your list of critical factors, make sure to remove those that have played out as expected or no longer meet the criteria discussed above.

In closing, here are some considerations I picked up from other research analysts and portfolio managers in terms of seeking out critical factors:

  • You’re not looking for data points but rather changes in trends.

  • Don’t “go underground” when conducting research; get out there and learn by having conversations. Inexperienced analysts hide in their spreadsheets, which fails to get them out into the debate.

  • You can’t do this on your own, especially when you’re new. You’ll need to ask for help from:

    • Colleagues in your firm

    • Investor relations

    • Sell-side (if on the buy-side)

    • Industry contacts

  • “The market often over-simplifies the investment thesis, which offers us an opportunity.”

Chapter 9. Create Sustainable Proprietary Sources of Insight

One of my most colorful buy-side clients put it well when he said, “The more I speak with companies, the stupider I get.”

There are two primary forms of channel checking: (1) informal, open-ended discussions with your industry sources; and (2) surveys conducted either one-on-one or in an automated manner.

Background research, such as reading industry journals or looking at historical relationships between data series, is critical for understanding the basics and developing a holistic perspective, but you’ll need to speak to information sources to develop an edge.

… one of your objectives should be to find industry contacts who would never be motivated to be part of an expert network, because this will offer you exclusivity of information.

Here are some of the most common mistakes analysts make when channel checking:

  • They are ill prepared because:

    • They don’t build a network of the right people.

    • They don’t immerse themselves into the field to meet contacts or get closer to the ones they know.

    • They don’t ask the right questions or understand the topic enough when questioning a good information source.

  • They don’t spend time wisely; specifically, they have discussions about factors:

    • The analyst already fully understands.

    • That aren’t likely to impact a stock price.

  • They draw conclusions based on channel checking with only one person, especially someone who may have a bias like a company CFO (this isn’t channel checking, it’s called interviewing management).

Chapter 10. Get the Most from Interviewing for Insights

Ask questions that will help to understand how management thinks rather than just get the answer. Rather than asking the margin for a new contract, ask how pricing is set to ensure there is enough margin—is it cost plus or market based pricing?

Mike Manelli, an analyst with sell-side and buy-side experience, remarked on this topic, “A lot of research is just making the calls to check the facts.”

If there’s an on-site tour, observe the intangibles:

  1. Are the executive offices:

    1. Opulent or run-down?

    2. Near the operations or very distant?

  2. Do employees take pride in their workspace (desk or factory floor) and show respect for one another?

  3. Is the warehouse empty or over-filled?

  4. Are the comments from management during your interview consistent with its public presentations and regulatory filings?

“One of the most important jobs of an analyst is to assess the quality of management.”

“Truthfulness decreases as we move from the feet to the head” (Navarro & Karlins, 2008: 55).

Given that you want to read the person’s body language as well as develop rapport, when entering a room for a meeting with management, attempt to get the closest seat to the person who will be interviewed. Somewhat related, if you have the chance to choose which manager to sit next to, make a point of getting to the person who influences or understands the critical factors the best. Don’t leave your seating to chance. It’s critical to get information as well as build a relationship with the managers who you think are likely to move up in the organization.

Part 3: Generating Quantitative Insights

Research by its very nature will result in dead ends, but knowing when to cut your losses and move on to the next project is a skill developed over time.

often there are deceptive games played with numbers.

Chapter 11. Detect Deceptive Numbers

Be skeptical of any data you receive from others. Just because a chart looks good in a company’s presentation doesn’t mean it’s conveying the information in a form you need for making investment decisions. Most importantly, start by assessing the biases of those providing the numbers; they will almost always have them.

Chapter 12. Leverage Statistics for Insights

Spearman’s rank coefficient.

If you’re using Excel, you’ll want to ensure that the Analysis ToolPak or Data Analysis is available in the toolbar (depending on your version of Excel, this may already be installed).

there’s a recognized body of knowledge in statistics known as exploratory data analysis, which is helpful for understanding the characteristics of your data.

The most commonly taught statistical procedure for examining the relationship between two variables is linear regression, sometimes known as ordinary least squares (OLS). As the term suggests, a linear regression assumes that the relationship between x and y approximates a straight line, like the scatterplots in the left panels of Exhibit 12.3. If the scatterplots show some curvature, like the ones in the right panels, then it may be appropriate to transform one or both series so that the relationship is brought toward approximate linearity (Mills, 1991). If you make such a transformation, then regression methods may provide sufficiently detailed analysis for forecasting purposes.

Chapter 14. Identify Yellow Flags through Forensic Accounting

Is the firm under pressure to maintain high growth rates in earnings or revenues?

Starting at the “30,000-foot view” look at the difference between the growth rates of revenues and earnings. When there is a large increase in earnings concurrent with flat or shrinking revenues, it should cause concern because it indicates earnings growth is likely from reducing expenses or from non-operating income. This also touches on the concept of earnings quality; namely, the highest quality earnings come from growth in revenue (units and pricing), because it’s more likely to be sustainable than earnings growth from cost cutting or asset sales. (Most companies can’t grow earnings into perpetuity solely by cutting costs or selling assets.)

This last note was a great point that I realized in my own business first-hand. You can only keep overhead so low before you’re selling office equipment to pay the bills and make people happy.

It’s also important to look at how much revenue is coming from changes in volume versus average selling price (ASP). ASP can increase due to the company extracting more economics from the customer, which should drop to the bottom line. Although, it can also be from other factors that won’t necessarily benefit earnings, at least not over the long-term. Information about these factors can often be found in the MD& A section of the 10-K filing or through discussions with company management. Unsustainable increases in ASP can come from:

  • Currency gains: If ASP rises during a certain period from currency benefits, it will likely reverse at some point when exchange rates revert. Also, if currency is inflating revenue growth, it tends to have the same impact on costs incurred in those local markets, potentially having a net neutral, or even negative effect on margins; the lesson here is in not assuming that higher ASP from currency is automatically positive for earnings.

  • Special assessments to cover higher expenses, such as a fuel surcharge, or to cover new government taxes: These types of boosts to ASP are usually offset by higher costs, thus resulting in no net benefit to margins.

  • Change in mix: When companies proudly state their ASP is up due to a greater percentage of higher-end product sales (more high-end laptop sales than low-end netbooks), make sure to understand the margins for each of these product lines. In the railroad sector, moving automobiles has historically yielded one of the highest ASPs of any freight type but also one of the lowest margins.

  • Change in revenue recognition: Accounting changes can impact ASP, but they’re usually one-time in nature and therefore don’t have a long-term benefit.

Other Yellow Flags: After completing your tactical review of the financial statements, look for other warning signs that aren’t in the financial statements:

  • Change in auditors: When a firm disagrees with its auditors and cannot resolve the disagreement, the auditors resign or the firm fires the auditors. This situation can arise when a firm uses an aggressive accounting treatment, and its external auditors tell the firm to use a more conservative approach. When any unscheduled event that is important to shareholders occurs, including a change in auditors, a firm is required by the SEC to file an 8-K.

Negative audit opinions:

  • High turnover in top management team: If more than one of the company’s key executives resigns (or is fired) during a short period of time, the company might have serious problems.

  • Weak corporate governance: The board of directors should include enough outsiders to be independent of the firm’s management team and act on behalf of shareholders (instead of simply rubber stamping management’s decisions). If the majority of directors are insiders, the board is less likely to be independent. The outsiders should also have enough relevant expertise to think independently of management. Also, boards that are too small (fewer than 6 people) or too large (more than 15 people) tend to be ineffective because they are easy for management to control. On a large board, each director is dispensable and it is likely that no individual is powerful enough to contest management’s decisions. Having the CEO also be the chairman of the board further reduces the ability of the board to be independent. Weak corporate governance is problematic because it will be difficult to stop management from making decisions that are not in the best interest of shareholders. Some of this information can often be discovered by reading the proxy statements.

Be cautious when a company does any of the following:

  • Reduces the amount of information it discloses or discloses substantially less than its peers.

  • Fails to mention that it’s benefiting from non-operating profits in good quarters but is quick to point out non-operating losses in bad quarters.

  • Takes special charges, write-offs, or restates earnings as though it’s an ongoing part of the business.

  • Routinely dismisses generally accepted accounting principles (GAAP) (or international financial reporting standards [IFRS]) earnings as irrelevant or meaningless. This can be heard when management criticizes a competitor for being too conservative with its accounting methods.

  • Fails to discuss targets or hurdles for large investment projects. Great companies understand how and where to invest incremental capital, treating it as a core competency. If a company announces a major capital expenditure project and the CFO can’t explain the expected return or at least the hurdle for new investments, the analyst should question the company’s capital budgeting process.

  • Fails to discuss complicated or counterintuitive issues, such as the thought process for a merger or acquisition (M& A) transaction or currency hedging.

  • Changes the manner in which corporate overhead expenses are allocated among its divisions. This is a favorite shell game used by some management teams to suggest that a struggling division is being successfully turned around even though it’s cosmetic because the costs are simply being shifted to the more healthy division.

  • Reports results much later than the competitors. In an era of point-of-sale cash registers, bar-coded warehouse inventories, and globally integrated accounting systems, there’s little reason for a company to report quarterly results much past 30 days after the quarter ends.

Chapter 15. Identify the Relevant Microsoft Excel Features for Equity Research Analysts

Super nerdy of me, but I want to be able to look back on these, reference them, and be able to grow long term. Just like you should too. Most of these are available on Youtube but I want to be thorough.

Further Resources: Tjia, John, Building Financial Models, Second Edition, New York: McGraw-Hill, 2009. Winston, Wayne L., Microsoft Excel 2007: Data Analysis and Business Modeling, Redmond, WA: Microsoft Press, 2004.

Chapter 17. Develop Company Financial Models to Elicit Insights

I’ve met many buy-side analysts who don’t maintain any models for their companies and instead rely on consensus for valuation purposes. I have a tough time getting my head around this, because having a unique financial forecast is often the primary factor for differentiating an analyst’s stock call. But as I discuss later, a good differentiated stock call can also be driven by a superior view on valuation or market sentiment. So for buy-side analysts who don’t model, understand that it will be difficult to generate alpha by having a financial forecast that is superior to market consensus. With that said, during my research for this book, I met a number of successful practitioners who start with consensus and then tweak it based on their perception of where consensus is wrong. The remainder of this best practice assumes that the analyst builds company models in an effort to identify when the market is wrong about a stock.

Just as Goldilocks had to find the porridge that wasn’t too hot or too cold, equity analysts should create financial forecasts that aren’t too detailed or too simplistic.

I love the simplified analogy here. He brings a children’s story and analysis together.

If the analysis shows that a factor is unlikely to move a stock, stop spending time on it. This is so difficult for analysts who try to model every aspect of a company, but they must cut their losses if a factor isn’t likely to be material.

This one is big, and I think many have a hard time with it.

Elements of a Good Company Model

A good model has all five of these characteristics (the A, E, I, O, U framework):

  • Accurate: Is it technically sound? Do the columns add up properly, and are the financial statements properly integrated?

  • Efficient: Is it easy to update and add columns and rows when necessary? Does it avoid complicated macros and circular references so that it’s quick to make changes?

  • Illuminating: Is it easy to see trends and anomalies in critical factors and key financial metrics, such as margins, earnings per share (EPS) growth rate, return on invested capital (ROIC), and spot accounting yellow flags?

  • Organized: Is it well documented so that others can follow along? Are all of the assumptions in one place? Are there separate spreadsheets for each of the financial statements and the company’s operating division breakdown?

  • Useful: Does it allow for critical factor assumptions to be changed easily so that multiple scenarios can help the analyst think about the unexplored possibilities? Does the analyst look at it as a tool to help identify when consensus is wrong, rather than a useless but necessary step required before making a ratings change?

Chapter 18. Forecast Scenarios for the Most Important Critical Factors

There are many different ways to be successful in almost every profession, but there’s usually one factor that sets apart the good from the great. For financial analysts, discovering alpha-generating ideas is arguably the most important skill to master, but it’s followed closely by accurately forecasting future earnings, especially for sell-side analysts. Research shows that abnormal stock returns are earned when following the recommendations of sell-side analysts who are among the top quintile of accuracy in forecasting earnings. If you’re on the buy-side, the recommendation here is to find the sell-side analysts who have the most accurate forecasts and if you’re on the sell-side, do your best at forecasting earnings. Based on my experience, I suspect the connection between earnings forecast accuracy and generating alpha is not the result of more complex financial models (although it can help at times), but rather an analyst’s ability to find insights surrounding critical factors, which is important to both activities.

In a perfect world, you’ll routinely uncover critical factors that: (1) have a large impact on a stock, (2) are likely to occur, and (3) are not in consensus. Unfortunately, many critical factors that you come across will fall into only two of the three categories, which leaves you with little to offer your portfolio manager or clients. Experienced buy-side analysts routinely tell me that successful sell-side analysts need to come up with only one or two good ideas per year to have a successful franchise. In general, buy-side firms require more from their analysts, but most don’t expect more than a handful each quarter. Don’t beat yourself up if you don’t have a great new stock call every week, but also occasionally reflect to ensure that you’re periodically offering recommendations that generate alpha.

Part 4: Mastering Practical Valuation and Stock-Picking Skills

Chapter 19. Understand the Benefits and Limitations of Common Valuation Methodologies

Valuation is easy. The tough part is fundamental analysis.—Phil Friedman, former Morgan Stanley Portfolio Manager,

Here are some of the broad steps they use when conducting stock valuation:

  • They have full command of historical valuation parameters for their stocks, or classes of companies, specifically those with similar financial characteristics, which is critical for understanding the valuation levels likely to be afforded in the future.

  • They are diligent in understanding why the market values their stocks at current levels.

  • They appreciate the limitations of the most traditional valuation methods, such as price-to-earnings (P/ E), price-to-free cash flow (P/ FCF), price-to-book (P/ B), price-to-earnings growth (P/ EG), and discounted cash flow (DCF).

Research shows that substantial improvements in price target accuracy occur when analysts use more rigorous multiperiod valuation techniques (e.g., DCF), rather than a simple heuristic such as the P/ E ratio. The stock picking performance is even better for the population of analysts who are shown to have the most accurate earnings forecasts (Gleason, et al., 2008). From an academic perspective, DCF appears to get the highest marks, because it measures future free cash flows of the firm, which are the core to almost every valuation methodology.* From a practitioner’s perspective, the basic P/ E ratio is most revered for its simplicity. Studies have shown that even though sell-side analysts use DCF in their research reports when discussing valuation, they rarely use it to justify a price target (Imam Barker & Clubb, 2008). According to that same study, here are the valuation methodologies that sell-side analysts rank as most important (ranked in order of importance):

  • P/ E

  • DCF

  • Enterprise value-to-earnings before interest, taxes, depreciation, and amortization (EV/ EBITDA)

  • P/ CF

I recommend using a multiperiod cash flow valuation as a reality check for a single-period multiples-based valuation. When they differ substantially, it should cause the analyst to dig more deeply.

There is no methodology that prevents biases from influencing outcomes.

Chapter 20. Overcome Challenges to Creating Discerning Stock Calls

Dennis Shea, who spent many years as a highly ranked sell-side analyst and a senior manager of both sell-side and buy-side analysts, has an insightful view about the qualities that make up a great stock picker:

  • Dispassionate, namely, they don’t allow nonrelevant factors to cloud their judgment.

  • Stick to their discipline and strategy over the long-term.

  • Self-aware of where they have expertise and where they don’t.

Where Do You Differ? Put simply: The key to generating alpha is having a more accurate view about a future stock price than the market. This can only be done on a consistent basis if the analyst has an edge over the market in one of the three areas that compose our FaVeS ™ framework:

  • Forecast: Financial forecast superior to the market. (This relies on many of the best practices discussed earlier.)

  • Valuation: Valuation methodology or valuation multiple superior to the market.

  • Sentiment: Forecast of investor sentiment superior to the market. (Sentiment, void of any fundamental changes, is often the only thing that moves a stock or market in the short-term.)

Among the three elements of the FaVeS framework, new analysts are more likely to have success in developing a superior financial forecast than the other two components that take more time and experience to master.

It’s critical to ensure that the “differentiated” element of a forecast is concentrated in an area of expertise or has been thoroughly researched, rather than being just a more bullish or cautious view. It’s for this reason that analysts should forecast upside, downside, and base-case scenarios before making a big stock call; it allows critical assumptions to be stress tested and forces the analyst to consider the other side of the trade.

When faced with questionable stories, swing for singles and doubles, rather than trying to be the home-run hero, especially if you are an analyst early in your career.

I disagree here. Life is short.

A well-established study showed that stock recommendations from sell-side analysts who are in the top quintile of earnings-forecast accuracy generate almost 75-basis-points-higher returns than a passive index, whereas recommendations from those in the bottom quintile underperform a passive index by over 50 basis points (Loh and Mian, 2006). Another study shows that price targets set by Institutional Investor’s “All American” analysts are achieved 54 percent of the time within 12 months of applying the target (Asquith, Mikhail, & Au et al., 2005). When they exceed the target, they do so by 37 percent.

“Don’t change your valuation methodology just because the stock is moving. Do so only if there’s a major change to fundamentals.”

A common mistake made by inexperienced analysts is to say that a stock’s multiple looks cheap without thoroughly reviewing the forecast. For example, if a stock is trading at a 9 times forward consensus estimate compared with its historical 10 times (10 percent below normal), it could be because the consensus estimate is stale and almost certain to head 10 percent lower, which the market may have already discounted in the stock price. So the analyst makes a big call only to discover her estimate (and consensus) needs to be lowered over the following three months, putting her stock multiple right back to where it belongs. Before an analyst recommends a stock based on a change in the stock’s multiple, the financial forecast should be rigorously tested to ensure that it’s not likely to soon move in the wrong direction.

The best stock calls are made by analysts with conviction.

Chris Leshock, equity analyst at Perkins Investment Management, put it well when he said, “Good investing is a peculiar balance between the conviction to follow your ideas and the flexibility to recognize when you have made a mistake.”

Focus on Quality over Quantity: It’s important to emphasize quality over quantity when it comes to stock picking. Feedback from the global survey of portfolio managers mentioned earlier, suggests a sell-side analyst needs to come up with one to two good stock ideas per year. Yes, per year. I didn’t specifically ask about their buy-side counterparts, but it seems like it wouldn’t be much higher, except for trading-oriented shops; after all, it’s about generating alpha, not trading volume. Based on my experience, many equity research analysts believe they need to be producing a major new stock call every month, or for some, every week, which can be a futile effort. (Are that many stocks in a sector materially mispriced every week or month?) Analysts who have this tendency should instead channel their energy toward finding proprietary information that either confirms or refutes their existing stock calls. By coming back to the portfolio manager or clients with new value-added nuggets of information about their calls, the analysts can provide more value than chasing a new story every few weeks.

Chapter 21. Avoid Common Psychological Challenges That Impede Sound Investing

While not scientifically verified, I’ve found successful value investors to be more in the upper left quadrant (individualist), and growth investors to be more in the upper right quadrant (adventurer).

The following psychological pitfalls are great to know, as simply knowing about them can help any investor steer clear of them.

  • Confirmation Bias: Holding two conflicting views at the same time makes the human mind uncomfortable, a psychological phenomenon known as cognitive dissonance. Thus, we seek out information that confirms a preestablished view and ignore or reject evidence that contradicts it. Studies have shown that analysts underreact to unfavorable new information in earnings reports, convincing themselves that the situation is only temporary, and the status quo ante will soon be restored

  • Overconfidence: Financial professionals tend to be intelligent, often graduating near the top of their classes. While this can provide the extra credentials and confidence needed to land a role as an equity research analyst at a highly regarded firm, it can also lead to shortcomings in investing. A raft of studies shows that about 75 percent of people surveyed rank themselves

  • Self-Attribution Bias: Investors will often attribute their successes to personal intelligence and skills, while dismissing their mistakes as not their fault. In reality, some of the wins are just plain luck (the stock moves the right way for the wrong reasons), while some of the losses are the result of poor research. … Nicolosi, Peng, and Zhu (2009) found that, on average, investors increased their number of trades after a good month (“ I’m a genius”), but didn’t reduce their number of trades after a bad month. Poor results tend to get explained away as bad luck (Schoenhart, 2008: 80; Mangot, 2009: 48).

  • Optimism Bias: Investors tend to be too optimistic about their winners, which causes them to overlook or fail to properly investigate the risks of prospective investments. Bernartzi, Kahneman, and Thaler (1999) surveyed over a thousand investors and found that 74 percent spent more time thinking about potential gains, while only 7 percent focused more on potential losses.

  • Recency Bias: Analysts can become overly biased by information or personal experiences that occurred recently, while undervaluing information learned in the distant past.

  • Momentum Bias: This is the desire to chase stocks that have already rallied, or believing that market trends will continue (Mangot, 2009). “Don’t keep recommending a stock just because it’s going up” is a belief held by Alkesh Shah, sell-side analyst at Evercore Partners.

  • Rules of Thumb (Heuristics): Rules of thumb are mental shortcuts we use to make decisions more quickly, which are important in order to remain efficient in the job. However, they can lead to problems if relied upon blindly (Schoenhart, 2008: 30–32). Constantly relying on the same initial stock screen or one specific valuation metric (e.g., P/ E) is likely to limit your opportunities. Research has shown that substantial improvements in price target quality occur when analysts appear to use a rigorous valuation technique rather than a heuristic (Gleason et al., 2009). The investment drivers and risks for a stock are always changing, which means the heuristic about when to buy or sell a particular stock may break down over time (Schoenhart, 2008: 30–32).

  • Reaching Conclusions Prematurely: Even the most highly rated money managers make investment decisions without 100 percent of the needed information, but this can be taken to an extreme when analysts draw conclusions before completing the necessary research. One mental shortcut that can be abused is representativeness; if item A has some of the characteristics of group A, it must belong to group A (e.g., thinking that all companies in the same sector have similar prospects).

  • Familiarity Bias: We have a tendency to prefer the things we’re familiar with over those we’re less familiar with. The problem in that is, if someone asks you to make a recommendation between a stock you actively follow and one you only know tangentially, you’re more likely to recommend the one you know.

  • Falling in Love with a Stock: You have a favorite stock, but you can’t bear to part with it even though it has reached your price target. Your emotional attachment (Mangot, 2009: 72) might be due to the stock performing well for you over the years or because the CEO treats you like family when visiting the company.

  • Sunk Cost Fallacy: You spend considerable time researching a stock and then feel obligated to have a strong view, either positive or negative. This is especially problematic for less experienced analysts, who want to impress their boss or clients when initiating coverage on a new sector. It can also be a problem if you’ve made a considerable investment in a stock, and then something occurs that isn’t in your investment thesis. When that happens, ask the following question: Would you still buy the stock? If not, it should probably be sold, but due to all of the effort to get it into the portfolio, it can be difficult to reverse course, especially if the stock was added recently.

  • Snakebite Effect: After having been burned with a particular stock, you say, “Never again.” This may be a good strategy in a situation where a company or sector has a long-standing structural problem that isn’t going away (e.g., excess capacity such as in the airline sector), but don’t let it blind you from giving an old investment a second look.

  • Anxiety: Being bombarded with daily stock gyrations, especially for a less experienced analyst, can be overwhelming; it can also lead to taking action in an effort to reduce anxiety—action that may be unwarranted. Early in my career, I watched my stocks’ daily moves so closely that I found the need to change ratings every two to three months, often missing the longer-term opportunities.

  • Overreaction: Contrary to the Efficient Market Hypothesis, the market can be quite irrational in the short run, and if you spend too much effort overanalyzing this volatility, it could cloud your judgment or cause you to make the wrong decision. These short-term, often unjustifiable, swings, such as concerns over a potential Fed tightening on Monday, may be completely forgotten when Wal-Mart reports a blowout quarter on Wednesday. Fundamentals generally don’t change from one day to the next, and so market moves are often driven by emotion (market sentiment). To this extent, it’s not uncommon for the financial markets to overshoot toward the upside on good news and overshoot toward the downside on bad news (Dreman, 1998: 239; Trammell, 2003: 46–47).

  • Loss-Aversion: It’s been proven in numerous studies that people dislike losing more than they like winning, which is why a stock loss tends to take on disproportionate significance relative to the overall portfolio or universe, when compared with a winner. This can be seen in investors who will avoid selling a stock at a loss, with a hope that it will move back into the black, even if the investment thesis is no longer intact (Schoenhart, 2008: 59, 70).

There are a few steps an analyst can take to avoid a broad group of them:

  • Document your thought process, and review it periodically.
    This is the only one I highlighted because it is extremely valuable.

  • Document changes to your financial forecasts.

  • Utilize trusted colleagues and investment committees to find blind spots in your investment thesis and prevent you from revising history.

  • Create automatic stop-loss triggers (e.g., 15 percent of the purchase price) or other mechanical sell disciplines to take the angst and resistance out of selling losers early.

Part 5: Communicating Stock Ideas so others take Action

Chapter 23. Create Content That Has Value

This is one contributor to the plethora of mediocre research out there: Company and sector analysts are compelled to spew a regular stream of facts and company-sponsored propaganda, all in an effort to feel like they’re producing something.

For anyone new to the industry, be advised that shoddy equity research can be spotted fairly quickly; it lacks facts to support the conclusion. Conversely, one of the most compelling aspects of a great stock call is that it’s supported with data points. This isn’t to say every good analyst has 100 percent of the required information to ensure that a stock call is successful (which is unrealistic), but rather that the basis for the stock call is supported by information that’s been thoroughly researched.

Chapter 25. Convey the 7 Critical Elements of Stock Recommendations

Messages conveying information to make stock recommendations or trading decisions should strive to have the following elements:

  • Conclusion-oriented (starts with conclusions)

  • Appealing (has a hook)

  • Stock-oriented (talks about stocks)

  • Concise (brief as possible without excluding supporting information)

  • Aware (acknowledges alternative views and avoids attacking people)

  • Data-driven (supported with data)

  • Easy-to-understand (can be understood by almost any practitioner)

Footnotes

Examining financial data across different periods of time is called vertical analysis. Common-size financial statements also facilitate comparison of financial data across different firms at the same point in time. For more information, see Financial Accounting, 3rd edition, by Dyckman, Magee, and Pfeiffer.

There is good discussion on bridging a connection between multiples-based and cash-flow-based valuation methodologies in Chapters 7 and 8 of Damodaran on Valuation, Second Edition. Hoboken: John Wiley & Sons, 2006.

Disclaimer: The information provided on this website is for general informational purposes only and should not be considered investment advice. Please read our full disclaimer for more information. You can access it by clicking HERE.

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