Forecasting Performance

Typically, forecasting involves making projections of cash flows to some point where the company has a steady state going forward  



The point when the Steady State going forward is reached

This steady state going forward is characterized by two properties

• the company grows at a constant rate with a constant reinvestment ratio, and 
• the company earns a constant rate of return on existing capital and new capital invested.

The Explicit Forecast Period

The horizon to the steady state, called the explicit forecast period, is usually 10 to 15 years.

This explicit forecast period should be divided into

• a first forecast period of five to seven years, where the statements will include many details,and,
• the remaining years' forecasts where the statements are simpler with less detail, which avoids the error of false precision.

Such forecasts require assumptions concerning a host of variables, including the return earned on invested capital and whether the company can stay competitive.



Steps in the Forecasting Process

There are six steps in the forecasting process.

1. Prepare and analyze historical financial statements and data.
2. Build the revenue forecast consistent with historical economy-wide evidence on growth.
3. Forecast the income statement using the appropriate economic drivers.
4. Forecast the balance sheet entries.
5. Forecast the investor funds into the balance sheet.
6. Calculate ROIC and FCF.

Additional issues include

• determining the effect of inflation,
• nonfinancial drivers, and 
• which costs are fixed and which are variable.

Price target - this information is helpful for getting a sense of what others are thinking about the stock's price.

Price target is a share price analysts say the stock will achieve at some future date.

Analysts often attach a period to the price, such as a one-year price target of $ 18.

The information is more suggestive than quantifiable.

It is helpful for getting a sense of what others are thinking about the stock's price.

The Day Ahead: The Perils of Bottom-Fishing

By Brian Sozzi | TheStreet.com – Tue, Oct 23, 201

By choice, I will stitch together earnings-season notes and play in Excel from the comfy confines of a space no bigger than a restroom in a one-bedroom apartment. To some this would appear akin to self-torture, but to me if offers a physical bubble around any harmful toxins that want to enter the analyses I'm conducting. Stupidly, I allowed a toxin to cross through to the other side on Monday evening, and its name was "Bottom Toxin." After the Dow gagged Friday, we've heard that the world's economic growth rate is now bottoming, and we must quickly welcome an array of earnings-season violators into the portfolio -- or, if you are me, onto the client watch list.

Snauseges? I comprehend that everyone in the #FinServices sphere wants to be the next rock star, that person of perfection who predicts that a market or a stock will likely head higher or lower by 10%. Sure, my dudes, we have to justify fees, be they for execution (research is an add-on, the ultimate "intellectual capital") or some other business being promoted through Google'sGOOG search algorithms.

But as a person who has been trained to first-smash a company's fundamentals into small pieces and then be the pitchman for or against exposure to the stock, I have to ask this simple question: Do the masses truly grasp the characteristics of a "bottom" in a company's performance or in country's economy? Further, for those identifying bottoms all over the place, I fancy there should at least be more than a few data points to support the brick-laying that are alleged to have brought us to financial spoils.

I took a momentary trip to the "bottom," and this is what I learned.

A Bottom, Deconstructed

● Pricing power is hard to come by, as companies become promotional to maintain market share. If Company A is ramping promotions, best believe that Company B and Company C will promote. Inside of that, it's hard to tell which company is winning and with what detriment to margins. Specific to this earnings season, the chatter was that third-quarter profit estimates would be eclipsed with ease. Guess what? That isn't happening, and it's starting on the top line. Are you willing to model for an  expansion in the price-to-earnings multiple in this scenario?

● There are excess goods sitting in end markets. This leads to a mouse-eats-snake development as goods bulge in factories and stockrooms. In upcoming 10-Q releases, skip to the inventory section and target the "finished goods inventory" component -- it's unlikely to be pretty for many companies that had earnings shortfalls. It requires time to sell off products collecting dust, even if a price discount has been enacted.

● There is this natural tendency for executives to believe an improved macroeconomic environment will alleviate the aforementioned issues, but they are hesitant to share this with analysts and shareholders for fear of over-promising and under-delivering. As a result, we are left exposed to potential false reads by the market -- as is currently the case, with stocks reacting harshly to earnings misses.

These are the primary takeaways to my trip to the bottom. I don't want to completely ruin your day with zillions of earnings bullets flying by. You see, the bottom is an ugly place to be, a barren wasteland where the slightest bit of rain brings hope. Stock-pickers will play with their discounted cash flow models, modeling in "reasonable" free cash flow and P/E multiple assumptions -- yet there is no real assurance they are reasonable enough.

At some point, yes, we will have to circle back to the industrial complex, call the big names oversold and then plunk down wagers on brighter quarters in 2013. However, I remain hesitant to call that in names such as Caterpillar CAT and Texas Instruments TXN , as the market is not telling us that should be the game plan right around now.

Deep Thought

Caterpillar traded off the lows of the session in response to earnings. If that was a type of stealthy bullish tell, am I a complete whack job in saying that the action should have spilled over to comparable companies in industrials -- for example, General Electric GE ? Heck, shouldn't the stock have closed at session highs? Theoretically, if a name like Caterpillar is moving counter to conventional wisdom -- that the world stinks -- then sentiment must be mirrored elsewhere in terms of sectors.

Uncensored

On Sept. 5, I said this on Decker's Outdoor DECK : "I'm not feeling how its outlook is shaping up on cost of goods sold, nor on what this means to consumers." On Oct. 23, I say this: Stay far away from this stock. Holiday-quarter guidance will be slashed, inventories are likely to be elevated (again), and core Ugg brand sales will be weak. But why stay far away? Well, there is an outside chance lower prices cleared some excess inventory, and that could trigger hope consumer appetite still exists for the brand -- which would crush the shorts.

http://finance.yahoo.com/news/day-ahead-perils-bottom-fishing-120000614.html

Buy, Sell, Hold: What it Really Means. Just remember as an individual investor not to put too much value the next time you see a report stating an analyst rates a stock a “Buy,” “Hold,” or “Sell.”

Gary Spivak, Tuesday, June 12th, 2012

Your Money >>> 

Buy, Sell, Hold: What it Really Means

In early May, I was intrigued when a few brokerage firms “initiated” coverage of Facebook with “Buy” ratings and price targets in the mid-$40 range — even before the stock was publicly traded. Now, if the stock were to trade near its $38 IPO price, is it still a “Buy” if it’s only going to get to the mid-40s?

Given the disappointing post-IPO performance of the stock and questions about what a particular analyst said or didn’t say to some clients, I thought it would be a good time to look at what makes a sell-side technology equity research analyst tick.

More importantly, how do they generate revenue for their firms?

For the most part, a technology equity analyst (which I have been for the past 14 years) is an honorable, hard-working person trying to make a decent living in a highly competitive environment where trading commissions are declining. But what you need to know is that, in most cases, the analyst isn’t compensated if they make you — John or Jane Q — money on stock picks. From a purely economic standpoint, they simply don’t care.

Billy Crystal used to have a recurring skit when he was a regular on Saturday Night Live called Fernando’s Hideaway. That’s the one where he coined the phrase “You Look Mahvellous!” In the skit, he would frequently utter the saying, “It is better to look good than to feel good.”

For the typical sell-side analyst, it’s better to look good than to be good. It’s more important to be interestingthan it is to be right.

My point is — don’t be taken in when an analyst says, “Buy.” I’m certain they believe it, but there are other factors and conflicts you should be aware of.

“Buy,” “Sell,” or “Hold”

To understand why, let’s review what an analyst does. The analyst works hard to produce a report, sometimes fairly detailed, sometimes with a unique perspective, sometimes merely updating investors on current events, but almost always with a “Buy,” “Hold,” or “Sell” recommendation attached to it.

This report is summarized in “The Morning Meeting,” where the analyst conveys the essence of the message to the sales force. The sales force then may ask questions of the analyst to better understand the message. Ultimately, the salesperson then gets on the phone to their clients to deliver the message — “we say ‘Buy’ XYZ today, and here’s why.”

In many cases, the top clients are the large mutual funds and hedge funds. Why? They’re the ones that pay the most commission dollars. If the portfolio manager at the fund finds the comment interesting, he may place a trade with the brokerage firm issuing the research report. And that is primarily how the cash register rings.

Now, please notice that I said “finds the comment interesting.” I did not say “finds the comment convincing.” Let’s look at why.

When asked what they value in sell-side research, portfolio managers typically point to “idea generation” and “access to management.”

They do not say, “We look for the best stock pickers.” There are two obvious reasons why they don’t say this.

First

If they admitted that they got their stock picks from listening to a sell-side analyst, they would be failing to justify their own existence.

Second

The sell-side analyst who truly is a great stock picker ends up on the buy side. That’s where the decisions are made, and that’s where a good stock picker is worth the most money.

So, whether it’s self-serving or not, the buy side will admit to paying little attention to whether an analyst has a “Buy” rating or not. They’re looking for the incremental things — is this analyst looking at something differently, have they spoken to somebody I haven’t that may have a particular insight, have they recently spent time with the management team?

Believe it or not, there’s nothing sinister in this. It’s just a natural result of the environment for an analyst. Just remember as an individual investor not to put too much value the next time you see a report stating an analyst rates a stock a “Buy,” “Hold,” or “Sell.”

Charlie Munger - Projections do more harm than good

Reading Tea Leaves

" I have no use whatsoever for projections or forecasts.  They create an illusion of apparent precision. The more meticulous they are, the more concerned you should be.  We never look at projections but we care very much about, and look very deeply, at track records.  If a company has a lousy track record but a very bright future, we will miss the opportunity,"  explained Warren Buffett.

Charlie Munger, added that in his opinion projections do more harm than good.  "They are put together by people who have an interest in a particular outcome, have a subconscious bias, and its apparent precision makes it fallacious.  They remind me of Mark Twain's saying, 'A mine is a hole in the ground owned by a liar.'  Projections in America are often a lie, although not an intentional one, but the worst kind because the forecaster often believes them himself."

Here is how Graham and Dodd looked at projections.  "While a trend shown in the past is a fact, a 'future trend' is only an assumption.  The past, or even careful projections, can be seen as only a 'rough index' to the future."

More than five decades have passed since those words were said, and Buffett still agrees.

Earnings Forecasts Made Easy

Earnings Forecasts Made Easy

John Price, PhD

This article describes research on a new test that is included in the Conscious Investor Investment System. The result is that we can provide earnings forecasts on selected stocks that are five times more accurate than the average of analysts' forecasts.

In the long run, the value of a stock is the discounted value of the cash that can be taken out of the company during its remaining life. The usual analysis requires two inputs.

• Firstly, a forecast of how much cash the company is going to generate year by year. This is generally written as a percentage growth rate starting with the current cash.



• Secondly, a rate at which this cash should be discounted.

There are two extra ingredients that are often pushed to the background.

• The first is what do we mean by the cash that can be taken out of the company. The simple answer is the earnings. A better answer is one of the variations of free cash flow. I’ll talk about this in a later article. To keep things straightforward, here I will just use earnings.



• The second extra ingredient is confidence. How confident are we with the earnings forecasts? I have seen investors' eyes glaze over as they started imagining the yacht they were going to buy. They had found a stock and forecast its earnings to grow at 30% per annum. The market had missed it and now our starry-eyed investors were ready to make a killing. Alas, even though this was the forecast, what are the odds of it being accurate?

First, lets consider how well the professional do. In 1997 Lawrence Brown published a study in the Financial Analysts Journal looking at 130,000 forecasts by analysts from 1985 to 1996. He found that the average absolute error was a whopping 91.6 percent.

The difficulty is that analysts are starting behind the eight ball. They are assigned a group of companies and told to forecast their earnings. Unfortunately the earnings of companies such as Chiquita Brands and the Venator Group have more ups and downs and twists and turns than The Beast roller coaster in Cincinnati.

But we do not have this problem. No one tells us which companies to analyze. We have 10,000 companies to choose from so why not turn the problem around and focus on those companies about which we can have confidence?

One way to do this is to eyeball the historical earnings of companies and pick out those companies with earnings that grew smoothly. Next, extrapolate the data for these companies to forecast future earnings. This works to some extent, but I wanted to automate the selection/forecasting process.

This is where STAEGR™ enters, a new test I developed for my investment software Conscious Investor. It measures the stability of earnings growth from year to year and expresses it as a percentage. The maximum figure of 100% represents earnings that go up, or down, by the same percentage each year. The calculations are based on fitting an exponential curve to the historical data with more emphasis on the stability of the growth of recent earnings. Special adjustments are made for negative earnings, for extreme outliers, and for earnings near zero.

Using Value Line data, I considered all the companies with eleven years of earnings data from 1988 to 1998 inclusive. Next I divided the companies into ten groups ranging from those with the highest STAEGR over the ten years from 1988 to 1997 to those with the lowest STAEGR over this period. Each group contained 115 companies.

The next step was to calculate the earnings growth over the ten-year period using another Conscious Investor function. Earnings in 1998 were forecast using 1997 data and this historical growth figure. Finally the forecasted earnings were compared with the actual earnings in 1998.

The result of most interest to us was that the forecasted earnings of the high STAEGR group were extremely accurate. For the technically minded, the forecasted earnings explained 98 percent of the variation of the actual earnings. This can be seen in the accompanying chart.

The points represent the earnings figures, forecast and actual, of the companies in the group. Most of the points lie on or near a straight line which means that actual earnings were very close to the forecasts using historical earnings. The STAEGR of this group of 115 companies was 93% and up.

Another way of describing the results is that the average absolute error for this group of was 16 percent compared to the analyst error of 91.6 percent for all stocks. The difference is even more significant than it appears since the forecasts for the STAEGR method were for a full year whereas those of the analysts were only for the next quarter.

The results for the second group of stocks was similar. Their STAEGR ranged from 90% to 93%. This means that when we focus on stocks with the highest levels of STAEGR, say 90% and up, then the past growth or earnings is a statistically reliable predictor of earnings for the following year.

The accompanying chart shows the data for group of stocks with the lowest STAEGR.

In contrast, to the previous chart, clearly the dispersion of the data points is much higher. Notice that for some of the points the forecast is negative while the actual earnings are positive and for other points the opposite holds, positive forecasts resulting in negative outcomes.

The way these points are scattered is typical of the groups of stocks with lower STAEGR. In each case, the accuracy of the predictions using historical data was lower in two ways. Firstly the data points were more dispersed. Secondly the line of best fit had slopes further away from 1 and in many cases it was negative.

The study shows that you can have more confidence that earnings will continue to grow as in the past for stocks with a high level of STAEGR.

Here are some of the companies with the highest levels of STAEGR.

Company Ticker STAEGR
William Wrigley Jr. WWY 99.80%
Trustco Bank Corp TRST 97.20%
Bed Bath & Beyond Inc. BBBY 98.90%
Westamerica Bancorporation WABC 98.90%
Harley-Davidson, Inc. HDI 98.60%
Matthew's International MATW 98.50%
Johnson & Johnson JNJ 98.50%
C.H. Robinson Worldwide, Inc. CHRW 98.20%
Quality Systems, Incorporated QSII 97.50%
Old Second Bancorp, Inc. OSBC 97.30%
FactSet Research Systems, Inc. FDS 97.20%

Companies with the lowest levels of STAEGR were Chiquita Brands CQB (1.0%) and the Venator Group Z (0.8%).

Of course, just because we have confidence in our forecasts of future earnings of a company does not mean that we should rush out and buy it. But it does provide a solid basis for any buy/sell/hold analysis. Sorting stocks with the high levels of STAEGR for earnings as well as sales is another of the unique features of Conscious investor.

http://www.conscious-investor.com/articles/articles/article0008.asp

Analysts' earnings forecasts

Investors should be aware that in an up cycle, analysts would do two things:

1. to upgrade the earning forecast almost on a regular basis, and,
2. to accord the stock on a higher valuation (i.e. stock is now valued at a higher PE ratio).

This, we call, earning expansion and PE ratio expansion.

Normally, the analysts would do this a couple of times during a complete up cycle.

In a down cycle, the reverse happens. That is, earning and PE ratio (valuation) contract.

For those who have been investing over the last 4 years, they would have observed these in the analysts reports during the bull and the bear phases of the market.

What lessons should we learn from this?

We should not be sucked into this as we know that a very high EPS forecast is not sustainable (as compared to its historical records), and hence disappointment or downgrade would ahve to occur and we need to get out of this before it happens.

Thus, it is very important to know the big picture to gain an inkling of which stage of the economic cycle we are in now and how it is going to move looking forward.

Hence, when we look at EPS growth, we should ask ourselves whether it is sustainable in the next few years.