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Investing in net nets was my bread and butter back in 2008-2010.
I call it the glory days.
Everything was so darn cheap, it was like taking candy from a baby. Not that I would know.
The glory days are long gone and I eagerly wait for the next.
I love net nets because they are easy to invest. It’s an objective approach to investing. You don’t have to think about a narrative or future earnings power. Barely have to do any complex valuation or what if analysis like what we do with EBIT multiples valuation.
Focus on strong balance sheets, low cash burn rates, somewhat decent management and trust that the sentiment will go from pessimistic to average. I listed 7 things to look at when analyzing a net net.
Then buy a basket of the “safest” and walk away.
The US net net arena has dried up like sour anchovies – but there are always net nets lurking around.
But what I want to cover here is to use net nets as a way of gauging market sentiment.
Note that I say sentiment and not market valuation. Market valuation is useful when used correctly, but rarely is.
On the other hand, sentiment is broader but helps you see the forest.
First, let’s put net nets into perspective.
The Net Net Report
Back in 1986, Henry R. Oppenheimer wrote a paper titled Ben Graham’s Net Current Asset Values: A Performance Update.
The paper studied the number of net nets that existed from 1970 to 1982 and its performance. The main objective of Oppenheimer was to see how NCAV stocks performed. To verify whether Ben Graham was telling the truth.
(Net Current Asset Value is defined as Total Current Assets minus Total Liabilities)
The stocks used for testing and performance were based on those that met the core Graham criteria of being priced below 2/3 of NCAV. NCAV is a very conservative measure even back then, today, it’s even more stringent.
Historical performance isn’t what I’m interested in because I know that NCAV stocks beat the market, but I have included it to provide a bigger picture.
What I do want to focus on is the number of net nets in any given year.
Time the Market like Ben Graham
The performance table is hard to understand at a glance so here’s a better view.
Look at the NYSE and AMEX columns first.
Under the NYSE totals, 1973, 1974 and 1975 were clearly the cheapest years.
As I look at this table, a new revelation is that looking at the NYSE stocks makes for a better indicator of market conditions.
If larger stocks are suddenly becoming net nets and the number of such stocks are increasing, that’s a clear sign of market cheapness.
Despite the savage beat down of large retail stocks in Q1 of this year, such stocks don’t show up because their debt levels are too high. One of the reasons why I take fancy to net nets because tangible assets set the floor.
When it comes to smaller stocks, there are always going to be cheap OTC and small caps. But when the number of large cap net nets increase, it’s time to jump in.
The table isn’t obvious though. Under AMEX and OTC, from 1973 to 1979, it’s difficult to figure out which year was cheap or cheaper. The sum of NYSE and AMEX totals provide mixed results, making some years hard to figure out.
Here’s a better chart to get a sense of the number of net nets.
For extra reference, here’s information of USA recessions between 1969 to 2009.
Compare the recession time periods with when the market was cheap according to Graham.
The 1973 to 1975 market is the only one that syncs up with the Oppenheimer report.
What this shows is that a recession does not equate to a cheap market.
Sounds counter intuitive, but a recession doesn’t necessarily equate to a market crash. Markets are forward looking and resilient. The current bull market is a reminder of this.
For a market to be cheap, there has to be a stock market crash, and that’s what happened during 1973 – 1975.
The Vietnam war and 1973 oil crisis only heightened the severity.
Graham Created a Market Timing System Using Net Nets
Maybe I should credit Oppenheimer.
Seeing how the data ends at 1982 with Oppenheimer, what about today?
That’s what I wanted to figure out.
The results I showing you is not scientifically or systematically accurate as Oppenheimer. I’m eyeballing it here with standard data sets.
However, you should be able to see what I’m trying to prove.
I ran some numbers to calculate the number of true net nets (2/3 of NCAV) and net nets where the NCAV was greater than the market cap.
The number of nets nets in this table include all sectors – financials, miners and utilities which I normally exclude for investment reasons.
The pink rows are recessions. To make it quick and easy, the totals are taken at the beginning of each year.
When you put this all together, you get a graphical picture of when markets were cheap.
The clear signal is that 2001 – 2003 and 2009 were the best years in the past 20 years to be
It was also the scariest.
When I originally wrote this article many years back, I was able to break down stocks by the index. Unfortunately, no longer able to do that, so the two categories are either OTC or non OTC. Previously, what I saw was that there were literally zero stocks from the NYSE that met the 2/3 NCAV criteria, even during the cheapest years.
What this says is that the information and tech we are surrounded by helps the market to be more efficient and the inefficient areas cloud over small caps.
So the next best thing I came up with is to simply count the number of companies trading at less than NCAV.
Not 2/3 of NCAV, just < NCAV.