“Payback Time” Analysis for GOOG

Image representing Google as depicted in Crunc...I still own a few shares of GOOG. It’s felt overpriced recently, but I’m holding onto a minimal amount at all times and trying to add more over time. So I’m hoping the price drops a bunch so I can pick up more cheaply.

Do a search here for GOOG for my previous thoughts (years old), but I basically think that the world will continue to be drowned in data. Google’s goal to organize the world’s information and their expertise at scaling Internet apps puts them in a great position to be a contender in just about any future technology.

Phil Town Payback TimeAnyway, I’ve recently read Phil Town’s new book Payback Time. The title there, like most investing books lately, takes advantage of the recent drop in the stock market to entice readers. However the content and tone of the book isn’t as whiny as you might think, and is generally applicable to investors in all markets.

We were big fans of the first Phil Town book, Rule #1, mostly because it described things in layman’s terms and gave readers a clear method for putting the books theories into practice.

Payback Time works the same way and repeats a lot of the ideas in Rule #1. There are still the 4 M’s (Meaning, Moat, Margin of Safety, and Management) for example, but instead of using technical analysis (in the form of Rule #1’s red/green arrows) Payback Time recommends a form of dollar cost averaging, Town calls “stock piling”.

Of course, Town has a section in the book titled “Why This Isn’t Dollar Cost Averaging” that I’ll try to summarize here. Town says (emphasis his), “DCA means investing a fixed dollar amount at fixed intervals no matter what the price of a given stock.” He then goes on to list the numerous flaws and criticisms of dollar cost averaging.

For further reading, Christian writes why you should consider “Averaging Down“, and here Steve “The Undertrader” describes his stockpiling-like investing style.)

So Town calls stockpiling “DCA with a brain”. You don’t buy any time or on predefined schedules. You buy when the stock price is within your Margin of Safety. And you don’t hold indefinitely. You sell if the stock price goes about your Margin of Safety.

I’ll buy that. And I like this a little better than using “the tools” or “the arrows” or technical analysis to judge a stock because it’s one less thing to calculate. If you are calculating a “sticker price” and MOS price anyway, might as well use them to trade. If you thought of stocks as commodities or discounted dollars, this kind of trading would make even more sense. I value $1 at $1. If the market is pricing it at $0.80, I buy. If the market is calculating it at $1.10, I sell. Sure I could have waited for the price to drop to $0.70 before buying, or $1.20 before selling. I would have made a better trade, but I’m always making a winning trade if I buy when the price is lower than what I value it at (plus my MOS) and sell when the price is higher than I value it at.

So the Payback Time strategy should be a little easier to follow than the technical analysis from Rule #1. Well, to a certain extent. Town introduces another calculation called “the payback time” (maybe that’s the true meaning of the title) to pretty much calculate the MOS from a different angle. And he brings technical analysis back in, talking about support and resistance levels. Here’s a good recent analysis from Hipegg on Google.

Alright, so that out of the way, let me share some of my calculations on Google stock (GOOG). I’m basically running through the Payback Time Spreadsheet found on the Payback Time website. It’s a handy tool.

Here I would want to do a large Google Moat analysis, but I’m lazy. So I’ll say hey, they have a huge margin and virtual monopoly in search. And while there stance is vulnerable (MSFT is gaining ground lately), this moat is fairly stable because (1) it takes a lot of knowledge and investment to serve billions of searches a day quickly and (2) advertisers and publishers benefit from consolidation and drive the market towards one winner.

Charlie Munger and Warren Buffet at Berkshire Hathaway like Google’s moat. Not sure if they are investing. Buffet shies away from tech.

Here I would want to do a large Management analysis, but I’m lazy. I’ll say hey, these guys strive to do no evil. Page and Brin seem like great folks who are in it for the long term. They are standing up to China vs. going for short term profits. They don’t fudge their numbers (other than tweaking the Adsense lever). They don’t mess around with finance gimmicks like splits, etc. They are smart and clearly have a better understanding of the future than the average C-Level exec.

Some numbers:
* 5 year EPS Growth has averaged 34%.
* 3 year OPS (operating cash flow per share) Growth has averaged 17%.
* 5 year Sales Growth has averaged 40%.
* 5 year BVPS (book value per share) Growth has averaged 58%.

Nice all around. You usually want to go as far back as you can on these numbers. We can’t go much further back than 5 years because Google only started trading in 2004. If you wanted to be more conservative, you could use more recent (last 2-3 years) numbers since Google basically went from nothing to a top 10 company in 2 years and since then has grown a little slower.

Some more numbers:
* ROIC (Return on Invested Capital) = 18%
* ROE (Return on Equity) = 18%

Nice again. BTW, you can get some of these numbers in chart and spreadsheet form at YCharts.

Google has no debt!

Now, let’s calculate a sticker price and MOS.

* EPS = 21.97 (according to Yahoo)
* Earnings Growth = 14% (That’s my number. Historically we’re looking at 34%, and analysts are estimating 19% for next year. Should do more “main street” analysis of this considering how large Google is.)
* Future P/E = 24 (that’s about average for Google. 2x earnings would be 28)
* MARR = 15% (This is my “minimal acceptable rate of return, i.e. I want to make at least this much per year)
* MOS% = 25% (Ideally you would want 50%, but that is hard to get with GOOG and I’m pretty confident in them.)

I get MOS numbers then like:
* EPS = 21.97
* EPS in 10 Years = $81.45
* Stock Price in 10 Years = $1,954.74
* Sticker Price Today = $483.18
* MOS Price = 3/4 = $362.39

So according to this, I am a seller above $483.18 and I am a buyer under $362.39.

For completeness, here is the Payback Time Analysis using these numbers. To recoup my investment in 8 years, I’d want to buy GOOG at $331.43. That basically means that if you bought all of GOOG at $331.43, you would earn that back in Revenues (assuming our growth numbers) in 8 years. That would be a good investment if you were buying a franchise, and should be a good investment when buying stock as well.

I hope this was informative. Feel free to pick apart my numbers. In particular, I am always interested in pondering what a company that grows at 14%+ for 10 years would look like in the future. I’ll do that in a future post.

Reblog this post [with Zemanta]

Goldman Sachs Traded Profitably EVERY DAY Last Quarter

From DealBreaker.com (via CrossingWallStreet):

Goldman Sachs just revealed in an SEC filing that its traders made money on every single trading day last quarter, a record for the firm. Net revenue for trading was $25 million or higher in all of the first quarter’s 63 trading days with 35 of those days bringing in more $100 million, according to the filing.

That’s pretty amazing. They didn’t have ANY down days? How is this possible? Is the new Goldman Sachs playing it safe? I thought they were doing high risk trades? Were they just lucky? Do they have one big positive trade making up for the losses? Are they rigging the game?

I think this is the graph from the filing that the original posters are referring to.

The following chart sets forth the frequency distribution of our daily trading net revenues for substantially all inventory positions included in VaR for the quarter ended March 2010:
gs-trading-revenue

As part of our overall risk control process, daily trading net revenues are compared with VaR calculated as of the end of the prior business day. Trading losses incurred on a single day did not exceed our 95% one-day VaR during the first quarter of 2010.

I had forgotten what VaR stood for; it’s “Value at Risk”. Thanks, Wikipedia.

Also of note to me is how pro-Goldman the comments seemed at the end of the DealBreaker post. There are likely a lot of traders/investors in the mix who seem to think that if you are smart enough to make money, you deserve it… perhaps a little naive (even at this time?) that people in power wouldn’t take unfair advantage to make money.

I don’t want to imply that Goldman is for sure doing something illegal or immoral, but I think it is okay to be a little skeptical and think about it. I do think it is also very possible that Goldman Sachs is just doing well like most other people’s portfolios were before last week.

But I would be interested in hearing people’s intelligent thoughts on how their trading activities could go 90 days without a single down day.

Reblog this post [with Zemanta]

NASDAQ Cancelling Trades After Crazy Day in The Market

Trying to figure out what to think about this: (from BusinessWeek)

The Nasdaq said after markets closed that it will cancel all trades of stocks that moved more than 60 percent from their price at, or immediately prior to, 2:40 p.m., when the slide started. The cancellation applies to trades executed between 2:40 p.m. and 3 p.m.

Were there true “errors” leading to these trades (e.g. running trades that weren’t placed, or trades triggered because a stocks price was listed incorrectly)? Or were there just a bunch of people with stop losses and automated programs setup to sell sell sell?

I get the sense that some folks with trigger fingers on the sell button are getting a chance to renege since the market ended up down “only” 3.2%. If I was one of those guys with a standing order to buy QQQQ when it was down 30% or whoever was on the buying end of things as the market tanked… and NASDAQ reversed my trades… I’d be pissed.

Should we have a market that steps in and slows things down or puts a halt on things when there is a panic? Maybe. I guess these things are almost due to an “error” and we don’t want to compound misinformation. But part of me things we’re letting some folks off the hook when stuff like this happens. You shouldn’t be able to have it both ways… have your automated algorithms buying and selling, but then vrwvrwvritvrit-reverse when you accidentally sell too soon.

Reblog this post [with Zemanta]