I am going to start this Blog by stating that I acknowledge there are literally dozens of ways to make money in markets. Trading, investing, long term, short term, growth, value, trend, low PE, etc. and any combination of the above. Skilled and experienced practitioners of almost any strategy can make money over time, and I have considerable respect for those who do and their methods. I am not making a claim here that any strategy “doesn’t work”.
My second key point, is that for all of the various strategies and time frames, a trader or investor only needs to excel at one method over time to be profitable. I am a firm believer in specialized knowledge and becoming a master at a single endeavor vs being mediocre at many.
My third key point, is to defer to Stanley Druckenmiller and Paul Tudor Jones, two stock market Billionaires, who have publicly said:
Druckenmiller: “Earnings don’t move the overall market; it’s the Federal Reserve Board… focus on the central banks and focus on the movement of liquidity… most people in the market are looking for earnings and conventional measures. It’s liquidity that moves markets.”
PTJ: “…at the end of the day, your job is to buy what goes up and to sell what goes down so really who gives a damn about PE’s? If it’s going up you’re supposed to be long it.”
That being said, I am not an expert on fundamental data or analysis, and I do not hold myself out to be. I do however know enough about it after 20 years to ask some challenging questions. In my
4 1/2 years on Twitter I have asked some very bright people these questions and still to this day have not gotten the answers. Maybe someone will read this and provide concrete facts to refute my points. I remain open minded. With that said, I made the decision to stop paying attention to Fundamental data to make trading decisions consciously in 2009, and here are a few key reasons why:
It is literally impossible to “know everything about everything”. As broad as that sounds, the world of “Fundamental Data” in trading and investing is virtually infinite. So the question is how does one make the determination of what data is important to a trading/investing decision and what data is not? Is it the same for every market, or does it vary? If markets are efficient, isn’t all known data baked into the price? Also, markets are said to be forward looking, so what bearing does today’s data have on the price in 3 to 6 months. What if other “more important data” (macro) changes and overrides this data? As you can see, the questions can go on and on forever. For the last 20 years I have seen charts, graphs and research reports about global debt, margin debt, insider activity, and hundreds of ratios to show why prices aren’t justified, but your P/L is determined by one data point. Price. So, from a fundamental perspective, which data matters?
PE (which one, trailing or forward, GAAP, EBITDA, how about “one time charges” ) – can companies really anticipate what the world will look like in the next twelve months, can anyone, or is this just a guess?
Price to Book – who determines the value of the assets on the books?
Debt to Equity
Free cash flow
Who determines which of these takes precedence and how do we know the numbers are accurate? (Think Enron, Tyco, WorldCom and Adelphia Communications)
I heard a very well known money manager say a few years ago that he spent 75 hours studying a stock to take a position. How much time did he spend studying the exit or the stop loss if the position goes against him? If we put money at risk into a position in anticipation of it going up in value, won’t a price based technical program get into the same position when it breaks out in about 10 seconds?
P/E (Price to Earnings Ratio)
I will start this topic by stating that as of 9/24/2017, the top 20 performing stocks in the S&P 500 YTD are up an average of 67.44% with an average PE ratio of 49.06 (please reference the attached slides from Finviz.com). Two have no PE listed, NRG and FSLR. The #1 performer YTD, VRTX, of which I have been long since February 2017, has a PE of 146. I would say based on the fact that the top 20 performers YTD have an average PE of 49.06 makes it a difficult case to state that PE as a stand alone metric has any meaningful bearing on stock price performance. Maybe someone will provide some academic studies, but I am looking at today’s S&P 500 data. Difficult to refute that.
In my 20 years, I have traded through the Internet Stock mania of 1997 to March 2000 and watched the Nasdaq go from 1,200 to over 5,000 in 3 years. Companies with triple digit PEs, no PE, and in some cases, no revenues, like Corvis Communications, went sky high and people made fortunes off these names. High PE and no PE names (“New Economy” stocks, as they were branded) like Cisco Systems, Oracle, Sun Micro, JDS Uniphase, CMGI, Inktomi, Applied Micro, were minting new millionaires almost daily. Real money and real profits for shareholders, even if the companies themselves were losing money. Wall Street was rolling out tech funds and focused funds daily, CNBC’s New Year’s Special 2000 had strategists naming JDSU as their top pick (the poster child for tech stock mania) and the tech craze was in full effect. Jim Cramer was on TV telling people if their fund manager couldn’t outperform the Nasdaq, they should be fired. Anyone reading this who was in the markets in the late 90s/early 2000s will likely remember all of this.
On the other hand deep value, low PE names were selling off. Procter and Gamble lost 50% of its value in Q1 of 2000. “Blue Chips” like DuPont and Boeing lost over 50% of their value in the late 90’s while companies with no earnings and questionable revenues went up 500%+. Legendary value investor Julian Robertson shut down his fund. The high fliers came crashing down even faster, but the shareholders who sold all the way up had real money in their hands.
As a developing trader, I had questions:
Stocks ran all the way up with no earnings or PEs of 100, 200, 300+, so why didn’t the high PE stop them from going up? That didn’t seem viable.
The internet was a disruptive force, but did that mean people were going to stop buying soap so PG should lose 50% of its value?
Why did high PE or no PE stocks keep going up?
Why did low PE stocks keep going down?
If a low PE stock looked like a buy with a PE of 12, wasn’t it a better buy at a PE of 10, yet it kept going down?
Why was a PE of 15 high for certain stocks but a PE of 20 wasn’t for others? Many will say earnings growth and industry metrics, but who decides which is high and which is low?
If low PE stocks keep going down, where is my exit to protect capital as the position unwinds?
Then, on March 10, 2000, the Nasdaq topped and tech stock and high PE stocks came crashing down. Those who made the argument that PE and valuations took over in March of 2000, could never explain why PE had no bearing at all from 1997 to March of 2000. I will reveal my views about this later.
Which earnings metric should we look at? PE, trailing PE, forward PE, GAAP, EBITDA, one-time charges, (what are those one time charges and why don’t they “count”), etc.
Finally, if my primary goal is to protect capital and limit losses, how do I use PE to get me out of a losing position?
Fuzzy Math – Balance Sheets & Financial Statements
Also in the early 2000s came the great Financial Engineering fiasco. I saw household names, some considered “safe”, like Enron, WorldCom, Tyco and Adelphia literally trade down to zero, and CEOs get jail sentences as it was discovered they manipulated their books, fabricated numbers and hid billions of dollars in expenses and/or debt from investors. Enron was in Fortune’s “Most Admired Companies in America” list in the year 2000. Wall Street loved Enron, in part because their “Fundamentals” were so good. Fundamentals looked great. Balance sheets looked great, and then, zero. We kept hearing from pundits on TV, “oh, [XYZ] is a great company, it will come back”. 15+ years later, those names still haven’t come back and neither have the dollars.
If the Financial Statements could obviously be engineered, how reliable was the data pulled from them and as a result the decisions made from the data?
As a result, I came to a few key conclusions:
Fundamental data is infinite.
Who determines which data is relevant for which market?
If fundamental data gets someone into position and it starts going against them, what tells them to get out?
PE didn’t seem to matter in any consistent way that I or anyone else could quantify.
Balance sheets and financial statements could obviously be manipulated, at least for a long enough time for investors to lose all of their money.
With all of this being said, I was on a search for something to tie it all together. Something quantifiable and consistent, that I could use for entry and exits and something that would give me a concrete strategy to keep losses small. There is also one inescapable fact that to this day no one has been able to refute. The only metric that determines your P/L is price. There is no qualifier on anyone’s brokerage statement for PE, debt ratio, or insider activity. It’s quantity x price.