...The use of earnings forecasts in stock recommendations: Are accurate analysts more consistent?† Andreas Simon Orfalea College of Business California Polytechnic State University San Luis Obispo, CA (email: ansimon@calpoly.edu) Asher Curtis David Eccles School of Business The University of Utah Salt Lake City, UT (email: asher.curtis@business.utah.edu) This draft: September, 2010. Forthcoming, Journal of Business Finance and Accounting. ABSTRACT: We examine how analysts’ conflicting incentives to be either accurate or optimistic affect their choice to generate stock recommendations with rigorous valuation models or growth-based heuristics. Consistent with prior research the average analyst recommendation is negatively associated with rigorous valuation models and positively associated with growth-based heuristics, we document that these associations are weakest for the most accurate analysts and strongest for the least accurate analysts. We also find evidence consistent with consistency between recommendations and valuation models underlying the positive future returns from trading on the most accurate analysts’ recommendations. Our results are consistent with reputation incentives to be accurate mitigating the use of optimistic growthbased models in generating stock recommendations. Keywords: Forecast Accuracy; Fundamental Valuation; Stock Recommendations; Analyst Reputation. † Andreas Simon and Asher Curtis are, respectively, from the Orfalea College of Business...
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...Management Excellence Toolkit-Part 4: Improve Your Estimating and Forecasting Effectiveness March 16, 2011 by Art Petty Leave a Comment 27 Note from Art: Your decisions define you as a leader and a manager, yet we spend very little time in our busy lives finding ways to improve our abilities in this area. This Management Excellence Toolkit Series will help you recognize the challenges and pitfalls of individual and group decision-making and offer ideas on improving performance for you and your co-workers. Part 1 of this series emphasized the importance of developing, updating and referencing a Decision Journal. Part 2, focused on understanding how we make decisions and how various traps and biases often derail us. In Part 3, we tackled the power and importance of framing situations properly to improve your odds of success. Part 4 focuses on improving estimating and forecasting accuracy by strengthening management and leadership practices. Let’s kick this one off with the conclusion: poor management and leadership practices make a tough job tougher by introducing pressures and biases that directly impact estimating and forecasting activities. If these environmentally imposed biases weren’t enough, human nature gets a vote as well. Studies in the field of decision-making have shown, “we are systematically over-confident in our own abilities.” Consider the unscientific annual BusinessWeek poll results: “90% of managers believe they are in the top 10% of all performers...
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...Public School Enrollment Changes in Little Rock, AR Within the city boundaries, the Little Rock School District provides good quality education to students who live there as well as to students who live outside the city who choose to transfer to one of the magnet or interdistrict schools. The magnet school programs were awesome additions to the school district. One of the schools we will focus on today is Booker Arts Magnet Elementary. Booker Arts Magnet Elementary is one of the original magnet schools whose focus is on the arts. Its appeal is due to the exciting focus on such arts as dance, drama, music, visual art, orchestra, and piano lab. This environment is believed to be a creative learning environment even for those exceptional students. There are other magnet schools which focus on other subjects from Science to Foreign Languages. Because of their popularity there was great excitement through the communities. Parents had to apply in their various districts to get into these schools and many were put on waiting list to get in. The number of students rose within the district by leaps and bounds as reflected in chart below for school year 2006/2007. These schools are also recognized for their multicultural diversity and high academic standards. As times changed, there began to be an increase in private schools, many of which began scholarship programs to lure in moderate to low income families, who normally couldn’t afford the private sector. Because many private...
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...Fashion fascinations for Spring 2010 Spring 2010 exemplifies clothes that are soft, feminine, not overtly frilly and most of all capturing that easy-sexy look effortlessly. Here are the fashion fascination highlights for Spring 2010. 1. Skater Dresses. Yes, every little girl’s favorite sport--figure skating is finally hitting the runways this season. This short dress is a favorite for A-list celebs such as Zoe Saldana and Chloe Sevigny. Skater dresses are so flattering because it flares from the waistline giving a girly & youthful feel. The soft, layered hemlines whether done in pleats or ruffles are sure to make any woman twirl with delight. This dress shows off your lean legs-instantly giving you that svelte look. This look is easy-sexy that comes in soft hues such as lavender, blush and peach. Spring shows are filled with this fantasy inspired look from Louis Vuitton, Christian Dior to Stella McCartney. It is highly recommended that you invest in this piece, as this dress will most likely be wearable for the summer. 2. Gray for day, silver for night. Gray is the new go-to color for day. It’s an easy flattering color that will suit almost everyone. Designers have handpicked a light gray color for spring 2010 shown in most skirts, shorts and blouses. Night time signals the need for some eye-catching hue--silver. Another color that is easy to wear but designers are gunning for the sequined, sparkly silver hue. Arrays of choices are available as designers such as...
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...LAB’S MODULE: FORECASTING In this exercise, you will learn how to create forecasts for a product group through SAP. SAP provides a complete set of forecasting tools that can be used in a number of sales and operations areas. The most flexible set of forecasting tools are provided in the Sales and Operations Planning (SOP) transaction. The flow of the forecasting flowchart can be seen below: [pic] 1: Create Product Group |Purpose of Exercise | |To assist with Sales Order Planning you firstly need to create a Product Group. Product groups (product families) support high-level | |planning. A product group combines other product groups and materials. | |Menu Path |Logistics ( Production ( SOP ( Product Group ( Create | |Trans Code | | The Create Product Group: Initial Screen appears. 1. Type KidBikeGrp### in the Product group field. 2. Type ### Sport & Fun Kid Bike Prod Grp in the Description field. 3. Type DL00 (Plant Dallas) in the Plant field. 4. Type ST (items) in the Base Unit field. 5. Check that Materials radio button has been selected. ...
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...Earnings Forecasts: A Primer By Ben McClure AAA | investopedia.com Anyone who reads the financial press or watches CNBC on television will have heard the term "beat the street", which really just means to beat Wall Street earnings forecasts. Wall Street analysts' consensus earnings estimates are used by the market to judge stock performance. Here we offer a brief overview of the consensus earnings and what they mean to investors. What are Consensus Earnings? Consensus earnings estimates are far from perfect, but they are watched by many investors and play an important role in measuring the appropriate valuation for a stock. Investors measure stock performance on the basis of a company's earnings power. To make a proper assessment, investors seek a sound estimate of this year's and next year's earnings per share (EPS), as well as a strong sense of how much the company will earn even farther down the road. (For further reading, see Earnings Guidance: The Good, The Bad And Good Riddance?) That's why, as part of their services to clients, large brokerage firms such as Citigroup and Merrill Lynch (the "sell side" of Wall Street and other investment communities) employ legions of stock analysts to publish forecast reports on companies' earnings over the coming years. A consensus forecast number is normally an average or median of all the forecasts from individual analysts tracking a particular stock. So, when you hear that a company is expected to earn $1.50 per-share...
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...FINAL PROJECT: Chapter 1: Page: 23 Case Study: National Air Express 1. Is the productivity measure of shipments per day per truck still useful? Are there alternatives that might be effective? The productivity can be measured by the number of stops covered by each driver. I think measuring shipments per day per truck is still useful. It helps to keep on track with the amount of services that can be offer on every day basis and with the area covered by each driver. By doing that, the company can tell how many areas have been covered by a driver per day; therefore productivity can be assessed in measurable way. 2. What, if anything, can be done to reduce the daily variability in pickup call-ins? Can the driver be expected to be at several locations at once at 5pm? To reduce daily variability in pickup call-ins, the company should avoid call-ins during peak time; what I mean is that the company can offer to its customer’s deals to call at maybe nights when the network is not that busy so people for important calls only can use and benefit from the network. By offering deals to clients that call at night times the driver might be able to make to several place before peak time which is 5pm. This strategy can be apply in order to reduce the business during the day time so the driver can easily and correctly do their job. 3. How should package pickup performance be measured? Are standards useful in an environment that is affected by weather, traffic, and other random variables...
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...Please cite this note as: OECD (2014), “OECD forecasts during and after the financial crisis: A Post Mortem”, OECD Economics Department Policy Notes, No. 23 February 2014. OECD FORECASTS DURING AND AFTER THE FINANCIAL CRISIS: A POST MORTEM OECD Economics Department Policy Note no. 23 February 2014 This Policy Note is published on the responsibility of the Secretary-General of the OECD. The opinions expressed and arguments employed herein do not necessarily reflect the official views of the Organisation or of the governments of its member countries. This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law. © OECD 2014 You can copy, download or print OECD content for your own use, and you can include excerpts from OECD publications, databases and multimedia products in your own documents, presentations, blogs, websites and teaching materials, provided that suitable acknowledgment of OECD as source and copyright owner is given. All requests for public or commercial use and translation rights should be submitted...
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...OCTOBER 2002 | | | | | | | | | | Financial forecast for Lowe's | | | | | | | | | | | | | | | | | | | | | | Fiscal year | ASSUMPTIONS | | 2001 | 2002F | 2003F | 2004F | 2005F | 2006F | | | | | | | | | | | Growth in new stores | | 14.5% | 16.9% | 15.9% | 13.8% | 13.0% | 13.0% | | Sales growth for existing stores | | 2.9% | 3.0% | 2.6% | 3.9% | 4.9% | 6.4% | | Total sales growth | | 17.3% | 19.9% | 18.5% | 17.7% | 17.9% | 19.4% | | | | | | | | | | | Gross margin | | 28.8% | 29.2% | 29.5% | 29.5% | 29.5% | 29.5% | | Cash operating expenses/Sales | | 18.3% | 17.7% | 18.0% | 18.0% | 17.7% | 17.5% | | Depreciation/Sales | | 2.4% | 2.4% | 2.4% | 2.4% | 2.4% | 2.4% | | Income tax rate | | 37.0% | 37.4% | 37.5% | 37.5% | 37.5% | 37.5% | | | | | | | | | | | Cash & ST Inv/Sales | | 3.9% | 3.9% | 4.1% | 4.1% | 4.5% | 4.5% | | Receivable turnover | | 133.5 | 133.5 | 133.5 | 133.5 | 133.5 | 133.5 | | Inventory turnover | | 4.4 | 4.4 | 4.4 | 4.2 | 4.2 | 4.0 | | P&E Turnover | | 2.6 | 2.6 | 2.8 | 3.0 | 3.2 | 3.2 | | Payables/COGS | | 10.9% | 10.9% | 10.9% | 10.9% | 10.9% | 10.9% | | Other curr liab/Sales | | 4.2% | 4.2% | 4.2% | 4.2% | 4.2% | 4.2% | | | | | | | | | | FORECAST | | | | | | | | | Number of stores | | ...
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...Introduction Budgets and Forecasts are predictions of future income and expenses and cash flow. They also predict future performance with financial forecasts and projections and with financial models. Why Budget and Forecast? Budgets and forecasts provide a feasibility analysis. They can help develop a business model, review the company’s key assumptions, and identify resource and capital needs. Budgets and forecasts can be used to find funding. They demonstrate the potential of the business to investors and lenders. Budgets and forecasts can also be used as a management tool. They can help the organization establish milestones and require accountability for accomplishing the milestones. They can help identify risks and show benchmarks. This will help business owners make the necessary adjustments to avoid the risks, to reach the milestones, and to measure up to benchmarks. Forecasts are important because it can establish measurements to guide management, to facilitate planning, and to facilitate goal setting. As part of the forecasts, the company will review key concepts and issues that will make a difference in the company’s survival. The company also needs to forecast the resources it will need and set up a schedule for using and replenishing it’s resources. For years, companies have viewed their budgets and forecast simply as a mandatory estimate of the upcoming year’s revenues and expenses. However, this attitude is quickly changing as the marketplace becomes...
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...tell the STATA that this dataset is the time series format by using “tsset time” command. Then, the autocorrelations and partial autocorrelation are used to examine that whether the series is non-stationary or not. As can be seen the autocorrelation and partial autocorrelation graph below, they can be suggested that the series is non-stationary because the AC graph The series is non-stationary as the autocorrelations decrease slowly as the number of time lags increases and the partial autocorrelations show a large spike close to one at lag 1. Autocorrelation (AC) Partial autocorrelations (PAC) To estimate the fitted model, there are four possible trends that are chosen to compare as follows: Linear trend model In order to forecast the trend, we start to fit a linear trend model to the data by regressing the GDP on a constant and a linear time trend. The p-value of the t- statistic on the time trend is zero and the regression’s R2 is high so it can be implied that the trend appears highly significant. Moreover, as can be seen in the residual graph, it can be concluded that the linear trend is inadequate due to the fact that the actual trend is nonlinear. Residual Additionally, the linear model is not suitable when compared the fitted linear trend and the actual trend in the graph below. Quadratic trend model It can be seen that the quadratic trend is...
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...European Anaiysts' Earnings Forecasts Stan Beckers, Michael Steliarcs, and Alexander Thcmson Forecasting company cnrniu^s /s ( difficult and hazardous task. In nn 7 efficient market where annly^^ts learn from ptist mistakes, there should be no persistent and systematic biases in consensus earnings accuracy. J^rcvious research has already established how some (single) individualcompany characteristics si/stematically influence forecast accuracy. So far, however, the effect on consensus eariiings biases of a comptmy's sector and country affiliatioti combined with a range of other fundameutal chanieteristics has remained largely unexplored, ilsiiig data for 19932002, this article diseiitangles and quantifies for a broad universe of European stocks how the number of analysts following a stock, the dispersion of their forecasts, the volatility of earnings, the sector and country classification of the covered conipamj, ami its nuirket capitalization influence the accuracy of the consensus earnings forecast. 5 ecurity analysts are considered to be the premier experts in the assessment of a company's prospects. Their research efforts are largely directed at producing accurate earnings forecasts, which are a key input into equity valuation models. Although the importance of financial analysis is beyond dispute, its quality has become the subject of much scrutiny and debate. Academic research has a long history of documenting systematic earnings forecast errors, but analysts' conflicts...
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...Financial forecasts As part of your plan you will need to provide a set of financial projections which translate what you've said about your business into numbers. You will need to look carefully at: how much capital you need if you are seeking external funding the security you can offer lenders how you plan to repay any borrowings sources of revenue and income You may also want to include your personal finances as part of the plan at this stage. 1 Financial planning Your forecasts should run for the next three (or even five) years and their level of sophistication should reflect the sophistication of your business. However, the first 12 months' forecasts should have the most detail associated with them. Include the assumptions behind your projection with your figures, both in terms of costs and revenues so investors can clearly see the thinking behind the numbers. 2 What your forecasts should include Break even analysis Profit and loss forecast - a statement of the trading position of the business: the level of profit you expect to make, given your projected sales and the costs of providing goods and services and your overheads. Cashflow statements - your cash balance and monthly cashflow patterns for at least the first 12 to 18 months. The aim is to show that your business will have enough working capital to survive so make sure you have considered the key factors such as the...
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...3.5 (see p. 73) would be denoted Y1 = 147.6,Y2 = 251.8, Y3 = 273.1, ... , Y52 = 281.4. Mathematical notation must also be developed for distinguishing between an actual value of time series and the forecast value. A^ (hat) will be placed above a value to indicate that it is being forecast. The forecast value for Yt is Yt^. The accuracy of a forecasting technique is frequently judged by comparing the original series Y1, Y2, ... with the series of forecast values Y^1, Y^ 2, .... Basic Forecasting Notation Basic forecasting notation is summarized as follows. Yt = value of time series at period t t = forecast value of Yt et = Yt - Yt^ = residual, or forecast error Several methods have been devised to summarize the errors generated by a particular forecasting technique. Most of these measures involve averaging some function of the difference between an actual value and its forecast value. These differences between observed values and forecast values are ofteri referred to as residuals. A residual is difference between an actual value and its forecaste Equation 3.6 is used to compute the error, or residual, for each forecast period. et = Yt - Yt^ et = forecast error in time...
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...Forecasting Methods A time series is a sequence of observations which are ordered in time. Inherent in the collection of data taken over time is some form of random variation. There exist methods for reducing of canceling the effect due to random variation. Widely used techniques are "smoothing". These techniques, when properly applied, reveals more clearly the underlying trends. Enter the time series Row-wise in sequence, starting from the left-upper corner, and the parameter(s), then click the Calculate button for obtaining one-period-ahead forecasting. Blank boxes are not included in the calculations but zeros are. In entering your data to move from cell to cell in the data-matrix use the Tab key not arrow or enter keys. Features of time series, which might be revealed by examining its graph, with the forecasted values, and the residuals behavior, condition forecasting modeling. Moving Averages: Moving averages rank among the most popular techniques for the preprocessing of time series. They are used to filter random "white noise" from the data, to make the time series smoother or even to emphasize certain informational components contained in the time series. Exponential Smoothing: This is a very popular scheme to produce a smoothed Time Series. Whereas in Moving Averages the past observations are weighted equally, Exponential Smoothing assigns exponentially decreasing weights as the observation get older. In other words, recent observations are given relatively more...
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