Category Archives: Discounting

Disney (DIS), Berkshire Hathaway (BRK) and the discounting mechanism

May 6, 2020 By in Discounting, discounting in the AI age, Uncategorized Tags: , Leave a comment

discounting

This is Wall Street jargon for the investor process of factoring into today’s prices the effects of anticipated future events.

old school

Pre-2009, legions of experienced securities analysts and portfolio managers pored over company SEC filings and put that information together with their industry and business cycle knowledge to make reasoned projections of future company profits–and of possible stock performance if their guesses were right.

In bear markets, investors paid little attention to the future.  In bull markets, this is the time of year investors would begin to adjust their thinking not only for this year’s possible profit gains but next year’s as well.

 

in the AI world

I don’t know yet.  But I think this is a crucial thing to try to figure out.

recent data points

BRK had its annual investor event last Sunday.  When I entered the stock market in 1978, CEO Warren Buffett, professional investor and disciple of Benjamin Graham, was already an investing legend.  This was based on his earlier-than-everyone-else understanding of the value of intangible assets like brand names and distribution networks.  The last fifteen years or so have not been especially kind to Mr. Buffett, but he remains a legend nonetheless.  Anyway, at the meeting Buffett announced that BRK had sold its entire $6 billion stake in major domestic airlines.

Those stocks fell by about 10% on Monday.  Why did he sell?  My simple answer is that airlines need to sell an average of 70% of their available seats to break even on a financial reporting basis.  That’s impossible to achieve while social distancing protocols are in effect–and unlikely, I think, even when those are lifted.

But who didn’t know that before Sunday?  Monday’s price action indicates there certainly was someone.

DIS

DIS reported March-quarter results after the close yesterday.  Y-ear-to-date, DIS has underperformed the S&P, although wildly outperforming other leisure and entertainment companies (softer fall, more muted rebound).  This is partly, I think, (justified, in my view) admiration of the company’s transformation under CEO Bob Iger, partly the possibility that the DIS streaming service will be a success.  While investors haven’t been particularly positive, press coverage has been uniformly upbeat.

In yesterday’s conference call, the financial press”learned” that the company’s theme parks are closed, movie theaters are shut and ESPN is showing reruns of old spelling bees and writing about Korean baseball because there’s no live domestic sports.  the company also decided to halt the dividend for now.  Financial press coverage has turned sharply negative.

in early trading today, DIS is flattish.  It will be interesting to see how it finishes out the day.

today’s discounting mechanism

January 6, 2020 By in Discounting, Uncategorized Tags: 3 Comments

discounting

Discounting is Wall Street jargon for new information being factored into stock prices.

Discounting isn’t a single thing.  In the 1920s, for instance, company managements issued unreliable financial statements while happily passing along inside information to their bankers.  Ordinary investors fended for themselves with the only tool they had back then–watching prices and stock charts.

When I entered the stock market in late 1978 there were already laws requiring publicly traded companies to file detailed financial statements with the SEC.  From the early 1970s cadres of well-paid analysts poring over them and creating the microeconomics of firm and industry behavior.  Yes, there were still throwbacks who expected analysts to be part of their public relations efforts…and there was pressure on analysts who worked for brokerage houses to make their ideas known to the proprietary trading  desk before anyone else.  Still, the playing field was a lot more level.  There were significant rewards for original research conclusions, particularly with traditional growth companies, where the game was, and still is, finding situation where the consensus was too pessimistic about the rate of profit growth and/or the length of time unusually high earnings gains could be sustained.  Typically, stocks would start to rise a year or more in advance of confirming earnings.  In over-bullish markets investors might discount as much a three years into the future; in the depths of bear markets investors would stick to actual earnings and not discount the future at all.

In the 1990s this dynamic began to change, as investment managers began to lay off their in-house analysts on the idea that relying on brokerage research was a lot cheaper and a lot less effort.  In 2000, the SEC passed Regulation FD, which required publicly-traded companies not to make selective disclosure of corporate information (the presumed recipients were investment bankers and institutional shareholders).  Replying to an analyst’s novel question or inadvertently revealing information through body language became worrisome enough that companies either stopped having meetings or developed canned presentations and pretended they were news.  In the wake of the financial crisis, brokers laid off virtually all their experienced analysts.  Since academics are totally clueless about finance, this left no place for newcomers to learn how to do traditional analysis.

Enter AI–whose specialty is reacting to newly released information with lightning speed rather than anticipation of yet-to-be-announced developments.

What is a fundamental analyst to do?

Strategically, fundamentals-based investing remains the same, I think–figuring out potentially market-moving information before the average market participant does.  Today’s tactics are different, though.  Fifteen years ago, the best strategy would have been to amass a large position in a given stock and wait for the market to work out what you already knew.  Price action would tell you when/if that was happening.  There would likely be bumps in the road, but these would offer opportunities to add.

I think the better course of action now is to start with a smaller position and use AI-induced volatility to add and subtract.

 

 

 

 

 

discounting in the age of algorithms

April 5, 2018 By in algorithmic trading, Discounting, Uncategorized Tags: , , 1 Comment

what discounting is

In traditional Wall Street parlance, discounting is factoring into today’s prices the anticipated effect of expected future events.  Put another way, in the best possible case, it’s buying a stock for, say $.25 extra today, thinking that in a week, or a month or a year, news will come out that makes the stock worth $1, or $10, or $100 more than it is today.

two components

They are:

—having/developing superior information, and

–correctly gauging what effect dissemination of the news will have on the stock.

In my experience, the first of these is the easier task.  Also, the answer to the second problem will likely be imprecise.  In most cases, “The stock will go up a lot when people understand x” is good enough.

examples

In the early days of the Apple turnaround, the company launched the iPod, which ended up doubling the company’s size.  So the key to earnings growth for AAPL was the rate of increase in iPod sales.  The heart of the iPod back then was a small form factor hard disk drive.  There were only two suppliers of this component, Hitachi and Seagate (?), so publicly available information on production of the small HDDs had some use.  Much more important, however, was that there was only one supplier of the tiny spindles the disks rotated around.  And, unknown to most on Wall Street, that small Japanese firm published monthly spindle production figures, which basically revealed AAPL’s anticipated sales.

Same thing in the early 1980s.  Intel chips ran so hot that they had to be encased in ceramic packaging–for which there was only one, again Japanese, source, Kyocera.  Again, monthly production figures, in Japanese, were publicly available.

In both cases, the production figures were accurate predictors of AAPL (INTC) unit sales a few months down the road.  Production ramp-up/cutback information, again public–though not easily accessible–data, was especially useful.

Third:  Back in the days before credit card data were widely available, retail analysts used to look at cash in circulation figures that the Federal Reserve published to gauge the temper of yearend holiday spending intentions.  The fourth-quarter rally in retail stocks sometimes ended in early December if the cash figures ticked down.

In all three cases, clever analysts found leading indicators of future earnings.  As the indicators became more widely known, Wall Street would begin to trade more on the course of the indicators rather than on the actual company results.

today’s world

Withdrawal of brokerage firms from the equity research business + downward pressure on fees + investor reallocation toward index investing have made traditional active management considerably less lucrative than it was during my working career.

A common response by investment firms has been to substitute one or two economists and/or data scientists for a room full of 10k-reading securities analysts who developed especially deep knowledge of a small number of market sectors.  As far as I can see, the approach of the algorithms the economists/programmers employ isn’t much more than to react quickly to news as it’s being disseminated.  (They may also be looking for leading indicators, but, if so, I don’t see any notable success.  Having seen several failed attempts–and having worked at the one big 1950s -1970s  success in this field, Value Line–I’m not that surprised at this failure.)

My thoughts: 

–there’s never been a better time to be a contrarian.  Know a few things well and use bouts of algorithmic craziness to trade around a core position

–For anyone who is willing to spend the time watching trading during days like Wednesday there’s also lots of information to be had from how individual stocks move.  In particular, which stocks fall the most but barely rebound?   which fall a little but rise a lot when the market turns?  which are just crazy volatile?

the stock market cycle–where are we now?

May 12, 2017 By in Discounting, Strategy, Uncategorized Tags: , , , Leave a comment

As I wrote yesterday, stock market price-earnings multiples tend to contract in bad times and expand during good.  This is not only due to well-understood macroeconomic causes–the effect of higher/lower interest rates and falling/rising corporate profits–but also from psychological/emotional motivations rooted in fear and greed.

(An aside:  Charles McKay’s Extraordinary Popular Delusions and the Madness of Crowds (1841) and Charles Kindleberger’s Manias, Panics and Crashes (1978) are only two of the many books chronicling the power of fear and greed in financial markets.  In fact, the efficient markets theory taught in business schools, which denies fear and greed have any effect on the price of financial instruments, was formulated while one of the bigger stock market bubbles in US history, the “Nifty Fifty” years, and a subsequent vicious crash in 1973-74, were taking place outside the ivory tower.)

Where are we now?

My take:

2008-09  PEs contract severely and remain compressed until 2013

2013  PEs rebound, but only to remove this compression and restore a more typical relationship between the interest yield on bonds and the earnings yield (1/PE) on stocks.

today  The situation is a little more nuanced.  The bond/stock relationship in general remains much the way it has been for the past several years, with stocks looking, if anything, somewhat undervalued vs. bonds.  But it’s also now very clear that, unlike the situation since 2008, that interest rates are on an upward path, implying downward pressure on bond prices.

In past plain-vanilla situations like this, stocks have moved sideways while bonds declined, buoyed by an early business cycle surge in corporate profits.

Since last November’s presidential election, stocks have risen by 10%+.  This is unusual, in my view, because we’re not at the dawn of a new business cycle.  It comes from anticipation that the Trump administration will introduce profit-boosting fiscal stimulus and reforms.  The “Trump trade” has disappeared since the inauguration, however.  Our new chief executive has displayed all the reality show craziness of The Apprentice, but little of the business acumen claimed for the character Mr. Trump portrayed in the show–and which he asserts he exhibited in in his long (although bankruptcy-ridden) career in the family real estate business.

Interestingly, the stock market hasn’t weakened so far in response to this development.  Instead, two things have happened.  Overall market PE multiples have expanded.  Interest has also shifted away from business cycle sensitive stocks toward secular growth stocks and early stage “concept” firms like Tesla, where PEs have expanded significantly.  TSLA is up by 76% since the election and 57% so far this year–despite the administration’s efforts to promote fossil fuels.  So greed still rules fear.  But animal spirits are no longer focused on beneficiaries of action from Washington.  They’re more amorphous–and speculative, as I see it.

Personally, I don’t think we’re at or near a speculative peak.  Of course, as a growth stock investor, and given my own temperament, I’m not going to be the first to know.  It does seem to me, however, that the sideways movement we’ve seen in the S&P since March tells us we are at limits of where the market can go without concrete economic positives, whether they be surprising strength from abroad or the hoped-for end to dysfunction in Washington.

 

discounting and the stock market cycle

May 11, 2017 By in Current Market Thoughts, Discounting, major changes in market direction, market bottoms, market tops, Strategy, Uncategorized Tags: , , , , , , , Leave a comment

stock market influences

earnings

To a substantial degree, stock prices are driven by the earnings performance of the companies whose securities are publicly traded.  But profit levels and potential profit gains aren’t the only factor.  Stock prices are also influenced by investor perceptions of the risk of owning stocks, by alternating emotions of fear and greed, that is, that are best expressed quantitatively in the relationship between the interest yield on government bonds and the earnings yield (1/PE) on stocks.

discounting:  fear vs. greed

Stock prices typically anticipate or “discount” future earnings.  But how far investors are willing to look forward is also a business cycle function of the alternating emotions of fear and greed.

Putting this relationship in its simplest form:

–at market bottoms investors are typically unwilling to discount in current prices any future good news.  As confidence builds, investors are progressively willing to factor in more and more of the expected future.

–in what I would call a normal market, toward the middle of each calendar year investors begin to discount expectations for earnings in the following year.

–at speculative tops, investors are routinely driving stock prices higher by discounting earnings from two or three years hence.  This, even though there’s no evidence that even professional analysts have much of a clue about how earnings will play out that far in the future.

(extreme) examples

Look back to the dark days of 2008-09.  During the financial crisis, S&P 500 earnings fell by 28% from their 2007 level.  The S&P 500 index, however, plunged by a tiny bit less than 50% from its July 2007 high to its March 2009 low.

In 2013, on the other hand, we can see the reverse phenomenon.   S&P 500 earnings rose by 5% that year.  The index itself soared by 30%, however.  What happened?   Stock market investors–after a four-year (!!) period of extreme caution and an almost exclusive focus on bonds–began to factor the possibility of future earnings gains into stock prices once again.  This was, I think, the market finally returning to normal–something that begins to happens within twelve months of the bottom in a garden-variety recession.

Where are we now in the fear/greed cycle?

More tomorrow.