Definition: EPS Momentum - “An increase in the earnings per share growth rate from one reporting period to the next.” (Source: NASDAQ)
EPS Momentum helps investors pick stocks...but not just any kind of stocks. Our model identifies and signals only those experiencing high growth. Our algorithm is designed to identify companies who Earnings, Price, and Sales Momentum is accelerating and to produce a “buy” signal when all three metrics reach their optimal measure.
The model measures changes in a number of fundamental criteria, ranks the magnitude of those changes, and produces buy signals at the optimal time. Use these signals to inform your investment decisions and improve your investment performance. EPS Momentum helps you achieve fundamental portfolio acceleration! Click here to get started.
Behavioral Finance identifies nearly 150 cognitive biases that lead people to make investment mistakes. The EPS Momentum model eliminates some of these biases using a logic-based approach uninfluenced by human intervention. Our algorithm uses specific data triggers to produce buy and sell signals that help you minimize behavioral finance mistakes and optimize your returns. And, the EPS Momentum model produces specific measurable results you can see!
EPS Momentum is the collaborative brainchild of mathematicians, programmers, designers, fundamental and quantitative analysts, derivatives traders, and portfolio managers. The owners of EPS Momentum have more than 100 years combined capital markets and IT experience and are alumni from major firms such as Bloomberg, Canon, Bear Stearns, and Merrill Lynch.
The EPS Momentum website helps individual investors eliminate the confusion about what stocks to own and when to own them. Our proprietary algorithm is the result of nearly two decades of research and thousands of interviews with institutional investors, hedge fund managers, and behavioral scientists. It is designed to identify investment opportunities and reveal them in clear, concise, and visually-appealing graphical displays.
The EPS Momentum model analyses the sales and earnings reported by public companies as well as the estimates and estimate-revisions published by Wall Street research (sell-side) analysts. Then it converts this data into easy-to-understand, actionable signals that answer two simple questions:1) What stocks should I buy?
We answer these questions visually using simple graphics that eliminate the noise surrounding the investment question. Our model identifies investment candidates that meet certain fundamental criteria and then alerts you whether or not now is the time to make an investment. The output is straightforward and unmistakable:
EPS Momentum derives its name from our multi-momentum methodology designed to identify emerging trends in EPS. More importantly our model defines EPS as Earning Price and Sales momentum. The Earning and Sales piece is contained in the EM indicator and the Price momentum is in the TM : Timing Momentum.
Our model measures changes in a number of fundamental criteria, ranks the magnitude of those changes, and produces signals (flags) when they enter into a calculated sweet spot. Use these flags to inform your investment decisions to improve performance and returns. EPS Momentum helps you achieve fundamental portfolio acceleration!
EPS Momentum indicators are simple. Buy when they are green. Don't buy when any of them are red. These simple-to-understand indicators include Earnings Momentum, Timing Momentum, Timing Bias, and Market Score. These four components are the heart and soul of the EPS Momentum Signals, which are informed and supported by a number of other proprietary analytical tools.
Each analytical tool is presented in a series of widgets that isolate their importance and clarify their utility. The EPS Momentum Signals Widget answers the “What” and “When” questions. The remaining widgets provide further fundamental analytics that support those answers and display them in straightforward tables and simple-to-understand graphs.
EPS Momentum assigns specific scores to various metrics in order to rank the investment attractiveness of the underlying stock. Our scores are based on raw, unadjusted data. The scoring system we developed produces absolute rankings that stand on their own merits. They are not relative to something else or created based on percentiles.
Stock rating systems that compare stocks against others can produce false positive scores. A relative rank score of 99 may actually be unreliable if all of the stocks in the peer group are underperforming, are significantly off their highs, or are in a downtrend. The 99 rating will simply be highlighting the stock that appears relatively better than the rest in a bad universe (i.e., the least worst in an undesirable pack).
Stock rating systems based on a percentile rank can also produce false positive scores. A high percentile rank means only that a given data point was better than the majority of all of the other data points observed. It says nothing about any of the actual observations or the absolute differences between them. If all of the data points observed were lackluster, then being the least lackluster is hardly encouraging. That’s why it is possible for a stock to be the 99th percentile even if its earnings growth is flat.
Because EPS Momentum scores are absolute, not relative or percentile ranked, they represent a much more accurate gauge of each metric.
Behavioral Finance employs theories from psychology to try to explain why stock prices behave the way they do, especially when that behavior is erratic or severe. It attempts to describe why human beings make the financial decisions they make - even when those decisions would appear to most people to be irrational.
In many ways the theory of Behavioral Finance demonstrates that the Efficient Market Hypothesis (the idea that stock prices always reflect every piece of information in real time and that all events are always fully reflected in those prices) can’t be possible because human nature always gets in the way of pure logic or dispassionate objectivity.
The Earnings Momentum, or EM Score, is a proprietary measure that considers both the rate of change and the acceleration of that rate of change in a company’s revenue and earnings. EM Scores are based on quarterly non-GAAP year-over-year changes and are presented as numerical values. These values are raw scores. They are not normalized, ranked into percentiles, or scaled relative to other stocks - but, they are adjusted for seasonal trends.
The formula to calculate EM Score gives a slightly higher weighting to reported revenue than reported earnings-per-share. This is because sales is an objective metric uninfluenced by one-time accounting adjustments and gains or losses that result from recognizing otherwise extraordinary items.
Our model attributes a high EM Score to companies that have revenue and earnings growth ranging from 17% to 20%. It attributes a negative EM Score to companies that have reported previous negative quarters, whose earnings are decelerating, or that report an abnormally weak quarter compared with the same prior-year period. Revenue and earnings-per-share data are continually analyzed using the most recent twelve fiscal quarters. This information populates a predictive statistical model against which current quarter data is compared to arrive at the most recent EM Score.
The Earnings Momentum Score rests on a continuum from -50 to +50 based on the strength of a company’s current earnings and revenue growth. A score above +20 indicates that sales and earnings momentum are accelerating and signals that the stock should be considered for investment. An EM Score at or above 20 does not trigger a buy signal. The EPS Momentum algorithm produces buy signals only when each of the factors it measures all reach their optimal score.
The specific data triggers that produce investment buy signals are:
Earnings Momentum Bias, or EM Bias, reflects intra-quarter changes in institutional holdings and perception among sell-side analysts. EM Bias in an informational signal only and does not have an impact on EM Score. We use EM Bias simply to gauge sentiment before and after our model identifies fundamental and timing opportunities in a particular stock. Changes in the two components of EM Bias are often a precursor changes in price (up or down).
Another proprietary indicator we developed is Timing Momentum, or TM Score, which begins by comparing a deliberate series of long-term, intermediate-term, and short-term moving averages to quantify the attractiveness of a stock’s price movement.
The formula to calculate TM Score begins with the creation of trend coefficients based on the delta between a stock’s 252-day high and two predefined price points: one at 90% of the 252-day high; the other at 80% of it. The formula then quantifies the exterior bands of two rolling price windows: a long-term trend component based on the first standard deviation of the stock’s 60-week volatility pattern; the other based on the standard deviation of the stock’s 20-day volatility pattern. The formula then calculates an intermediate score based on the weighting of the 3-day moving average of this derived factor relative to the stock’s 5-day moving average. This score is enhanced by two additional (separate) calculations based on a raw comparison of the stock’s price to its 5-day moving average and a comparison between its 5-week and 20-week moving averages. The sum of each of these factors is added to our proprietary Market Score to arrive at the final TM Score.
TM Score generates a signal only when it reaches a binary trigger point. That trigger point is always above zero and until it is reached, a TM Score has no predictive value in the EPS Momentum model. In the final analysis, TM Score quantifies a stock’s basic fundamental price trend. Scores have no set numeric boundaries, but are meaningful only when they are above zero. Stocks with a negative score have a negative trend...avoid these. A signal is produced only when TM Score is above 0. Consider these stocks for investment.
Timing Bias, or TM Bias, is a short-term version, and acts as a leading indicator, of TM Score. It is the quotient of two very short-term moving averages that give recent price moves much more weight than older data resulting from price moves over the previous few days. As such, TM Bias can change often and quickly. The EPS Momentum model uses TM Bias to the extent that it can suggest an impending trend reversal. Long-term momentum cannot turn positive without TM Bias first turning positive.
TM Bias ranges from -10 to +10 and has no indicative value below 0. Only when TM Bias is positive can TM Score be positive. Because the data used to calculate TM Bias is so short-term in nature, it can produce false signals. TM Bias should not be used to signal a stock’s reversal off of a bottom. But, it can suggest a positive change in a stock’s basic short-term trend and quantify its immediacy and timeliness. But, that signal must be confirmed by a positive TM Score in order for the EPS Momentum model to change from red to green.
The Market Score, or MS Score, quantifies the relative performance of the stock compared to the general stock market. We use the SPDR® S&P 500 ETF (SPY) as our proxy for the market. Our calculation uses a 10-Day Exponential Moving Average as a smoothing mechanism that gives recent activity more weight than older data.
MS Score oscillates around 0 with no set minimum or maximum. It quantifies a stock’s relative strength compared to the broad stock market and a signal is generated only when it reaches a binary trigger point. That trigger point is always above zero and until it is reached, an MS Score below zero has no predictive value other than to show that the stock is to be avoided. Only when the score is above 0 is there an MS Score buy signal.
SPDR® is a registered trademark of Standard & Poor's Financial Services, LLC.
The EPS Momentum model is based on several other proprietary measures, or scores. They are unique to our methodology and no firm on Wall Street, or elsewhere, publishes comparable data. These proprietary scores include:
The quarterly earnings cycle does not occur in a vacuum and sell-side analysts may revise their opinions, outlooks, and earnings estimates in the 90-day period between company reports. Changes in earnings estimates can be a leading indicator of future stock performance - higher or lower.
The challenge for investors is that analyst revisions do not occur in concert or on a set or predictable timetable. They are infrequent and unannounced. This unpredictability makes data analytics difficult. Nevertheless, earnings revisions can be one of the most influential factors affecting stock price movement.
The EPS Momentum algorithm records changes in estimates and quantifies them to produce a one-of-a-kind Revision Score. Our Revision Score reflects net positive or net negative changes to the mean earnings estimate of all published sell-side analysts.
Revision Score fluctuates between -5 and +5. It reflects the weight, scale, and number of changes to estimates. A negative score reflects net deterioration. A positive score reflects a net increase. A 0 score shows that any revisions published during the quarter have not changed the mean.
Institutional investment managers are required to report their ownership in public companies (above a certain threshold) within 45 days of the close of every calendar quarter. These regulatory filings shed light on the level of interest fund managers have in a given stock.
Our proprietary Institutional Score is derived from a combination of factors including the number of holders and the extent of, and changes to, their holdings. It is used to confirm trends and signal changes in medium- and long-term investor sentiment. The scale of our Institutional Score is -5 to +5. It considers any change in the number of institutional holders (up or down), the size of holdings (of both new and existing owners), and the net aggregate total of all holdings.
While any score above 0 is positive, Institutional Score is not a component of the EPSM Signals
that alone does not create a buy signal. Instead changes in Institutional Score should be monitored and treated as a potentially informative, albeit, lagging indicator. Institutional Score is helpful in confirming established trends identified by other EPS Momentum widgets. This is especially the case when Institutional Score trends (higher or lower) over more than one quarter.
Cash Back PE was created, and is used exclusively, by EPS Momentum to compare a company’s near-term price-earnings multiple to its long-term growth prospects. It does this by combining analytical methodologies of both fundamental equity analysis and traditional capital budgeting. As such, it can be thought of as a hybrid present value synthesis of a stock’s long-term price-earnings ratio (PE Ratio) and price/earnings-to-growth-ratio (PEG Ratio).
The Cash Back PE formula tabulates available earnings growth projections of sell-side analysts (a polynomial-interpolated earnings growth assumption is used in the absence of such estimates) for each period going out five years. Beyond year five the model forecasts longer-term annual earnings out to year 30 using the historical annual average rate of inflation since 1920 (rounded to the closest integer). The sum of these represent a company’s estimated accumulated earnings per share for the next 30 years. This calculation is made using analysts’ published high estimates, low estimates, and the mean of all estimates.
Using these estimates and the stock’s most recent trading price, the EPS Momentum Cash Back PE formula calculates the high, low, and mean number of years required for the stock to earn its current trading price (i.e., its theoretical payback period).
By combining two traditional valuation metrics (PE Ratio and PEG Ratio) and converting them into a long-term hybrid analytical tool allows investors to evaluate a stock’s long-term growth prospects using a long-term gauge (traditional PE and PEG look out only 12 months). It also creates one powerful valuation tool capable of comparing disparate securities (e.g., stocks with similar PE and/or PEG Ratios but different long-term growth expectations) on an apple to apples basis.
To the left of the main the EPS Momentum Dashboard you are presented with a menu of widgets. These widgets are the underpinnings of the EPS Momentum value proposition. They describe the various components of our service and display the building blocks we offer to help you maximize fundamental portfolio acceleration.
EPS Momentum allows you to customize stock charts to display data in a manner that is most appropriate for your style. From line charts to Japanese candlesticks, the form and function of the charts you create can be completely personalized to include more than a dozen different data series and attributes without affecting the proprietary data that only EPS Momentum provides.
All charts display Earnings Momentum (EM) and include histograms of Timing Momentum (TM), Timing Bias (TM Bias), and Market Score (MS) as well as their current value. Each value coincides with the display presented in the ESPM Signals Widget.
Each time you produce a chart every one of the widgets to the left of it is automatically populated with the same stock symbol and the Investing Journal Widget tells you whether the EPS Momentum algorithm currently owns, or has ever owned, that particular stock.
This is the heart of the EPS Momentum website. The EPSM Signal Widget answers the questions: what stock should I buy; and, when should I buy it? In addition to answering these fundamental questions, the widget also explains how our algorithm arrives at those answers.
The left side of the Signal Widget displays an unmistakable green or red box answering the question about the fundamental side of the equation. Is this stock’s earnings momentum sufficient to warrant investment? Green means yes. Red means no.
The EPSM Signal Widget shows you if a stock’s earnings momentum meets our fundamental test for investment. It displays the EM Score (the basis for the green or red signal) and provides a green or red arrow reflecting the current EM Bias. Also presented is our proprietary debt indicator flag. A red alerts you when a company’s leverage exceeds 100% of equity.
The right side of the EPSM Signal Widget answers the timing question. If the opportune time to make an investment is at hand, the box signals a green “YES”. If the timing is not right the box displays a red, “NOT NOW”. The Timing Momentum indicator box will remain in the red “NOT NOW” position when the TM Score is positive unless the underlying stock’s move is confirmed by both TM Bias and Relative Outperformance (Market Score). WhenTM Bias or Market Score indicate a buy signal the arrow to their left will be green and point upward. WhenTM Bias or Market Score are pointing downward the Timing Momentum box will be in the red “NOT NOW” position.
Beneath the EM Score box on the left and the TM Score box on the right the EPSM Signal Widget provides additional information that does not impact either score or its constituents. Each indicator displayed in the lower (middle) box provides general sector and market data and is for informational purposes only.
The first indicator provides information about the sector in which the quoted stock is a component (we use the Select Sector SPDR® ETF family to represent the eleven industrial sectors that make up the S&P 500). This Sector Outperformance signal is displayed with either a red arrow pointing downward or a green arrow pointing upward. A green arrow indicates that the sector is outperforming (exhibiting relative strength compared to) the broader market. When the arrow is red and pointing downward it indicates that the sector is underperforming (exhibiting relative weakness compared to) the market. The ETFs used to determine this information are presented below that in white.
Beneath that is a red arrow pointing downward or a green arrow pointing upward to characterize the general trend of the overall market (as defined by the relationship between the 5-week moving average to the 20-week moving average of SPY).
It is important to note that the lower middle box is intended only to provide information about general sector and market conditions. The EPS Momentum model can still produce buy signals on individual stocks even when the trend of the market and/or sector are negative. The model is intended to identify long-term investment opportunities not market or sector timing signals.
The EPS Momentum algorithm doesn't just create hypothetical investment signals, it is also programmed to use those signals to make automated investments. The investments are made using the logic-based approach outlined above allowing the machine to make all of the decisions uninfluenced by human intervention. While the investments are made in a simulated account, the results that are produced are real. We document each investment that the EPS Momentum system buys and sells and maintain a journal that catalogs them.
The journal displays the current total value of (theoretical) capital accumulated as a result of the algorithm’s investment decisions, the investment return that the machine has generated, the number of trades it has executed, and the initial amount of capital the computer started with. The journal also reveals the largest single investment gain on any of the individual investments (“Max Win”) as well as the the single largest loss incurred by the algorithm (“Max Loss”).
Each investment is chronicled from inception to completion (if applicable). For all investments the widget documents the profit or loss incurred (whether realized or unrealized), the date the investment was made and at what price, the date the investment was closed (if sold) and at what price, and the number of days the investment was (or currently has been) owned. For investments that are still open the widget displays the current stop-loss price as well as the distance between the current price and the stop.
The specific data triggers that produce investment buy signals are:
Investment positions are initiated programmatically. If the four data triggers are met, then four days after earnings are announced the EPS Momentum algorithm initiates a “buy” at the opening price of the subject stock. If earnings are announced before the market opens, then that day is counted as day one. If earnings are announced after the market closes, then the next day is treated as day one.
All investments in the EPS Momentum “portfolio” are initiated with a $10,000 “paper” purchase. At the time the purchase is made the algorithm automatically sets and records an internal stop loss order to sell at a price equal to 93% of the opening investment price. Then, each day after the position has been established, the system automatically resets the same proportional stop loss based on the closing price of the stock every day. In this way, an initial risk of loss is automatically set at 7% and then if the stock increases in value over time, the algorithm locks in ever increasing downside limits to prevent those gains from being eroded.
Note: The descriptions above are for informational purposes only. EPS Momentum is not a broker, dealer, or a registered investment advisor. Under no circumstances does the information above represent a recommendation to buy or sell a security. Nothing described in this widget is intended to to be (nor does it constitute) investment advice.
The Profile Widget provides a brief description of a company, the products it makes, the markets it serves, the distribution channels it utilizes, and the city where it’s located. Also provided is information about the sector and industry group to which the company belongs. A link to the company’s website is provided as well.
The Timing Momentum Widget is broken into five separate sections to reveal:
A stock’s TM Score is highlighted at the top of the page and is confirmed with a green ”Yes” or red “No” just below that in this first section. Highlighted in the same green or red field is the stock’s price change (in percent) since the company’s last earnings announcement date. Below that is the closing price of the stock on that date, and then, its last quoted price (previous session’s close). Below that is the ratio of the stock’s recent trading volume relative to its historical weekly (last four weeks) and daily (last five days) moving averages. To the right of the green or red field are displayed the high, low, and mean 12-month price targets of the sell-side analysts that cover the stock.
EPS Momentum calculates an investment allocation in the exact same proportion that the algorithm uses to make paper/auto-investments. Based on an assumed $10,000 investment the calculator produces a quotient of the number of shares the algorithm would buy of this particular stock. The calculator also produces a default stop loss price based on a common multiple of the average true range (ATR) of the stock. The EPS Momentum algorithm calculates the stop at two times the daily ATR. That price is then used to calculate the maximum loss (in percent) that would be incurred if the stock were to be purchased at the current price and then fell to the stop price and sold. This data is expanded upon greatly in the next section.
EPS Momentum calculates various other scenarios to help you determine the stop loss level that is most appropriate for your investment style and risk tolerance. Here we calculate various prices at which a stop loss order might be placed and display the potential loss for each price in terms of percentage, share price points, and total actual dollars based on the quantity of shares calculated in the Investment Allocation section (described above).
The stop loss prices calculated in this section expand upon the default stop loss price. Here we display the ramifications of more severe volatility and less severe volatility. As a starting point we repeat the default stop loss setting (2 ATR) and add to the display above that the effect of a stop loss set at the daily average true range (1 ATR). We also display (below the default) the price at the weekly ATR. And, below that we display the stop loss price using the second standard deviation of the stock’s statistically predicted volatility.
Use this section of the widget to help tailor your stop losses based on a given stock’s unique volatility characteristics. Stocks with higher volatility may warrant tighter stops (i.e., 1 ATR). Less volatile stocks might justify less rigid parameters. We display a few examples to help you scale or position your stops based on what fits best with your investment style and risk tolerance.
The table in this section illustrates the trend in TM Score, TM Bias, and MS Score over the last six trading sessions (including the current day) and is intended to help you identify improving or worsening trends as they are happening.
On the right side of the page is a visual representation of the stock’s one-year price movement and predicted price volatility. 30-day and 52-week highs and lows are obvious on the graph and represent extreme and intermediate reference points on the continuum. Also obvious is the last price of the stock, which is distinguished by a white dot. The key reference point on the chart is the red dot signifying the closing price of the stock the day of the company’s last earnings announcement.
Each of the predicted prices on the right side of the graph are calculated from this reference price based on the average true range of the stock and the second standard deviation of the stock’s statistically predicted volatility.
The graph provides a visualization of the data calculated in the STOP Position section of the widget and uses those same trading ranges to predict statistically-valid potential prices on both the downside and the upside.
The Revisions widget highlights our proprietary Revision Score and presents in a straightforward set of tables the underlying data used to create it. At the top left of the page the current Revision Score is compared to what it was in the previous quarter. To the right of these scores is detail showing the number of sell-side analysts who have commented on the company over the number who have yet to publish new research. Just below that in the same table is the actual number of upward and downward revisions published in the current quarter and the previous quarter. Next to that, to the right of the dashed line, is a reconciliation relating the company’s fiscal quarter to the actual calendar quarter.
Analysts’ changes (in percent) to revenue projections for the current quarter, next quarter, current year, and next year are presented on the left below the Revision Scores. Changes (also in percent) to earnings-per-share estimates for these same time periods are listed below that. The table shows how these estimates have changed in the current week, the last week, the last month, the last 60 days, and the last 90 days. To the right of these numbers are the actual earnings-per-share estimates themselves. All of this source data is illustrated in the chart beneath the tables. The Revision Score chart spans the last year-and-a-half.
The EPS Momentum Revision Score can be viewed as a potential precursor to changes in EM Score. Revision Score provides a clear indication of how analysts’ perception of a company - and its growth prospects - are evolving over time. A positive sloping Revision Score graph means that analysts’ believe that a company’s earnings are expected to rise.
The EM Matrix provides detailed insight into a company’s sales and earnings momentum. Quarterly data is presented at the top of the widget in columns for the current and previous two years. Full year data is presented in columns at the bottom of the widget for the current and previous three years. All data is displayed in both tabular and graphical formats.
The widget’s default display includes a table that allows you to compare earnings-per-share data quarter-by-quarter. These reported earnings per share numbers are used to calculate the year-over-year earnings growth rate for each respective quarter (compares numbers in the same column). This is vividly displayed in a color-coded table below the quarterly EPS numbers.
The color-coded table also displays the rate of acceleration (or deceleration) of earnings growth from one quarter to the next (compares numbers in the same row). This acceleration or deceleration is based on the change in a company’s earnings growth rate between quarters to help you visualize whether its earnings are growing (or shrinking) at a faster or slower pace than in previous quarters. Earnings Surprise, Price Change, and Revision Score are presented beneath the color-coded table.
Earnings Surprise represents the difference between a company’s actual reported earnings and the mean earnings estimate of sell-side analysts. Price Change represents the percentage move the stock has made in each respective quarter from the day before earnings were announced until the close of the company’s next fiscal quarter. For the current quarter the change is calculated from the day before the last earnings announcement until the close of the last trading session. Revision Score is our proprietary metric reflecting changes to the earnings estimates of all sell-side analysts.
Beneath this data we highlight, in yellow numbers in a yellow rectangle, quarterly changes to the company’s EM Score. Below this are presented, in another color-coded table, the company’s annual earnings-per-share numbers, growth rate, and acceleration.
Click on the EPS/Sales button highlighted in yellow on the top left of the widget to reveal the company’s quarterly and annual revenue data. You can toggle back and forth from this view to compare revenue growth to earnings-per-share growth and vise versa. The default display panel can also be expanded by clicking the icon on the top right of the widget.
Clicking on the expand arrows reveals linear trendlines for all of the data presented in the tables on the left. As noted above, clicking on the EPS/Sales button lets you toggle to between trend analysis for reported and expected revenue metrics and reported and expected earnings metrics.
Atop the column of charts another toggle button is highlighted in yellow. The default expanded setting tells you how many days remain before the company next reports earnings. Clicking on this button switches the view from a graphic presentation to a columnar table of numerical data. This information includes sell-side analysts’ mean earnings estimates for the next two quarters and next two years. The EPS Momentum model uses these estimates to calculate expected growth rates, acceleration rates, and EM Scores.
The Guidance Widget is a straightforward presentation of what a company believes its forward-looking revenues and earnings will be in the next couple of quarters. The widget also includes an historical perspective looking back over the last year to show how the company’s past guidance compared with what sell-side analysts were saying about their sales and earnings.
The widget is broken into two tables; one for earnings-per-share, the other for revenue. The data presented include the date the company provided the guidance, what that guidance was, and how it compared with sell-side analysts’ estimates.
The guidance numbers displayed (for both sales and EPS) represent the mean within the range provided in a company’s forward-looking statements. The variance, or surprise, is the difference between that derived number and the mean estimate (for revenue and earnings) of all sell-side analysts.
The Shareholders & Liabilities Widget provides insight into the EPS Momentum Institutional Score and provides some of the data used to calculate it. The data are presented in both tabular and graphical formats and the widget begins with the company’s Institutional Score in the top table.
In the table immediately below the score is displayed the company’s debt-to-equity ratio. When a company’s leverage exceeds 100% of equity the red debt indicator flag appears on the EPSM Signal Widget. The next number in this table is the percentage of the company owned by insiders (corporate officers, directors, and other affiliates) and the percentage of the company that is owned by institutional investors.
The table to the right of this information displays the total number of company shares that have been issued and that are outstanding. This table also reveals the number of outstanding shares that are available for trading (float). It also provides the company’s current market capitalization (total number of shares outstanding multiplied by the stock’s current market price).
There are three tables below this information and each relates to overall institutional ownership of the company. The table on the far left provides information on the number of institutions that own the stock, the percentage of them that have increased their stake in the last quarter, the percentage that have decreased their holdings in the last quarter, and the percentage of institutions that have neither bought nor sold shares in the last quarter.
This information is quantified in the table to the immediate right, which shows the net effect of these changes in holdings. The table highlights the percentage change in overall institutional holdings as well as the total (net) change in the number of shares held by institutions.
The table to the right of this presents in tabular form the trend in institutional holdings over the last two years. That trend is displayed in rich detail using four colorful histograms at the bottom of the widget below the tables.
These graphical representations of institutional holdings show how fund managers employing various invest styles have changed their holdings in the stock over the last few quarters.
The PE & PEG Widget uses five tables to display evaluation metrics that consider both short-term and long-term earnings estimates. A description of those tables as they appear on the widget in clockwise order is as follows.
The widget’s main table displays data based on the “High”, “Mean”, and “Low” earnings estimates and price targets of sell-side analysts. Data presented in the first three rows include (by column from left to right) the EPS Momentum Cash Back PE, the Long-Term Earnings-Per-Share Growth Rate, the stock’s 12-Month Price Target, the calculated Price-Earnings-Multiple of the stock based on its 12-Month Price Target, and the EPS Momentum Cash Back PE based on the stock’s 12-Month Price Target.
Directly beneath this data in the main table under the Cash Back PE (first column) is displayed the stock’s current trading price. Below that is the current Price-Earnings-Multiple of the stock based on the mean earnings estimate of sell-side analysts and the stock’s current trading price. The PE multiple of the stock based on its current trading price and the mean analyst estimate for the next 12 months appears under that. And, below this is the PE multiple looking out two years from now. The last metric in this column is the stock’s current price/earnings-to-growth-ratio.
The next table (top right) displays the EPS Momentum Cash Back PE multiples for the stock based on its current trading price and the High”, “Mean”, and “Low” earnings estimates of sell-side analysts.
The table beneath this presents the sum of earnings estimates and estimated earnings growth rates. Data in the top three rows are based on the mean estimate of sell-side analysts for the next five years. Data in the bottom row is based on the EPS Momentum forecasted terminal earnings growth rate out to year 30. The first column presents total earnings for the respective periods. The second column presents the respective earnings growth rates.
The table beneath this is intended to show you the ratio of a stock’s price change to the change in its earnings growth (PG/EG). Data are presented for the latest quarter and previous four quarters.
The first row details the change in the stock’s trading price for each respective quarter. The second row illustrates the annual earnings growth over (or under) the same period a year ago. And, the third row is the quotient of the two. EPS Momentum is unique in its use of this valuation tool.
We calculate the price growth to earnings growth ratio, or PG/EG, to quantify the degree to which a stock’s price is rising relative to the earnings growth the underlying company is generating for investors. A PG/EG above 1.0 signals that the stock’s trading price in that quarter grew faster than earnings grew in the period. A PG/EG below 1.0 signals that the company’s earnings in that quarter grew faster than the stock’s trading price. This metric is helpful on when both the change in stock price (the numerator) or earnings growth (the divisor) are positive.
The last table in the widget is to the left of this table and provides very traditional fundamental valuation metrics for the current and previous four quarters. Here we see the company’s Profit Margin, its Earnings Yield, its Return on Equity, and it Price-Earnings Multiple.
The EPS Momentum Stock Screener allows you to filter stocks using four distinct categories. Two of the categories - Description and Financials - will seem very familiar and straightforward. The other two - EPS Momentum Analytics and EPS Matrix - may be less familiar and worthy of further explanation.
The Description screen allows you to filter using common categories such industry or sector. But, it also allows you to screen by categories that highlight the unique value of our proprietary model, including the date a company last reported earnings, the date it last offered revenue and sales guidance to analysts, and the number of days remaining until it next reports earnings.
Screens available in the Financials filter include easily recognized fundamentals like shares outstanding and market capitalization, debt-to-equity, return-on-equity, and return-on-assets...among others. But, just like the Description screener, the Financials screener also allows you to filter by the more proprietary factors that our algorithm monitors. These include price change since the last earnings report, earnings surprise percentage, and changes in earnings estimates. The EPS Momentum Stock Screener also includes two filters that are completely proprietary to our model. These include our own Analytics Screener and Matrix Screener.
The EPS Momentum Analytics Screener lets you filter by Earnings Momentum (EM Score) and Timing Momentum (TM Score), as well as each one of our other proprietary scores, including Market Score, Institutional Score, and Revision Score.
The EPS Momentum Matrix Screener lets you search for stocks based on the key metrics of our proprietary model - namely revenue and earnings. This screen allows you to filter using specific period-over-period changes as well as surprises and acceleration. It also also you to screen for stocks that have announced sales or earnings surprises.