Use Your Extraordinary Edge With These 2 Investment Strategies

by: Ruerd Heeg

Summary

Researchers find returns of between 20% and 30% for net-nets. James Montier published similar returns for international stocks ranked on 5 value criteria. I will describe these results below.

In addition, I describe other statistical results for avoiding frauds and value traps related with these stocks.

Finally, I describe how you can invest in net-nets and in ranked low EV/EBIT stocks similar to those investigated by James' Montier.

Professional investors cannot implement these 2 strategies because of their size. Use them with your edge of being a small investor.

For more diversification I describe 2 value/momentum strategies with more liquid stocks. They are based on the best performing strategies in What Works on Wall Street.

Author's update, dated December 10, 2017 and December 28, 2017: This article has been updated with information on 2 great statistical momentum strategies, see last bullet point above. Positions have not been updated.

Professional investors have a disadvantage: being BIG. Certain very profitable investments will not move the needle for them. For them, investing in illiquid small caps does not make sense, for example. To overcome this disadvantage they have designed and researched complicated strategies. These strategies are not easy to implement for small investors. Only a few are excellent on a statistical basis. Most strategies have just nice stories around them, like trend-investing, technology, dividend-growth investing, macro-investing, and to some extent, even special situations investing and event-driven investing.

All these strategies have created their own buzz or even marketing hypes. Don't let them fool you. Instead use your natural advantage: being SMALL. Many of you have given it away to a professional investor. Large caps also operate similar to investment funds. So even if you invest yourself but invest in large caps you are giving your edge away.

I have been reading much to get my edge back. Below you will find the results. This article describes the results of many papers and books on statistical investing. I will only discuss the most important results for deep value investors. My search resulted in 2 excellent investment strategies that are easy to implement for small investors. In the second half of this article, I discuss statistical results for these 2 investment strategies: investing in net-nets (stocks trading below liquidation value) and global stocks with among others a low multiple Enterprise Value/EBIT. Then I will show how deep value and momentum can be combined with 2 complementing strategies. Also for these 2 extra strategies there is solid research pointing to very high returns with relatively low risks.

Some company names are in bold. That means I have a position in it. What kind of position, long or short, should be clear from the article.

Investing under extreme uncertainty

I like statistical investing. But often there are no statistics. One of the best papers on investing is Investing in the Unknown and Unknowable by Richard Zeckhauser (2006). This paper attracted comments that are also worth reading: here and here.

Under extreme uncertainty investments can often be bought for less than their true value. People overprice risk and underestimate the range of possible outcomes. I only realized this after I read this paper and thought about an attempt to buy stocks of Argentinian banks. These banks grew fast and were looking really good investments. What hold me back was the Argentinian peso was not freely convertible. The Argentinian economy was in a really bad state as well. In fact, nobody really knew how much their peso was worth. So I thought it was overvalued. After a new low I took a deep breath and placed an order. Unfortunately, the order did not get filled because the stock moved up a bit. I did not succeed in buying the stock. Within a few months that stock almost tripled.

That many investors only invest in their own country is another example of investors trying to reduce uncertainty. Unfortunately, this home bias increases volatility and reduces returns. In this case, it added to the mispricing of the Argentinian banks.

British bonds have gone up after Napoleon lost in Waterloo (see the article from Zeckhauser), Argentinian banks have recovered. So those opportunities are gone. But there are still investments with maximum investing pessimism and uncertainty, somewhere, if we keep our eyes open. Sorry for investors with a home bias: nowadays it is difficult to find maximum pessimism in developed markets.

Sometimes there is maximum pessimism in certain sectors, such as iron ore. There could be maximum pessimism with Australian iron ore mining companies like Grange Resources (OTC:GRRLF), with Chinese owners and management, or Atlas Iron (OTCPK:AGODY and OTC:ATLGF). After all those stories on Chinese ghost towns, how about construction companies, like Baoye Group Company?

Certain countries are also no-go areas for many investors. How about Ukrainian oil company Regal Petroleum (OTCPK:RGPMF)?

Liquidity

Liquidity is not trading volume. Instead liquidity depends on the width of the bid-ask spread and the size of the two quotes, relative to the market cap or the market value of the public float. One could use the bid-ask spread times the size of the 2 quotes times the share price divided by the market cap. With such a definition the metric is independent from the market cap: a large cap can be trading as illiquid as the smallest smallcap.

In practice reliable data for such a definition is not available. However, the simpler trading volume is a good replacement for liquidity. I screen for stocks with low volume relative to the public float. Again, with this definition, a largecap can trade just as illiquid as a smallcap.

Liquid stocks have lower returns than illiquid stocks, independent of size, momentum and value metrics. In practice the screener returns stocks of higher quality when restricting liquidity. A good paper is Liquidity as an Investment Style published in 2013 by Roger Ibbotson and 3 others. Among others they find investing in illiquid stocks combines well with value investing and investing in small companies.

The authors divide the 3500 biggest US stocks in market cap in quartiles. The quartile with the lowest P/E and least liquid stocks has a geometric return of 18.43% per year: more than 8% higher than the quartile with the lowest P/E and the most liquid stocks. Similarly the quartile with the smallest stocks and the least liquid stocks has a geometric return of 15.36%: more than 14% higher than the quartile with the smallest stocks and the most liquid stocks.

So investing in small value stocks combines excellent with investing in illiquid stocks. By the way, they also find low returns for the most liquid growth stocks with high or negative P/E, such as Tesla (TSLA).

Liquid trading often occurs after important events. Do not buy on good news! Instead sell the news (and maybe buy back later). After an announcement trading increases. With (unexpected) very bad news the stock often gets undervalued. With (unexpected) positive news the stock often gets overvalued. If (negative) news is fuzzy (difficult to interpret) often nothing happens. Then, after 2-3 days the market suddenly prices the news into the stock. Such stocks can be good shorts.

An interesting paper is Buy on bad news, sell on good news: How insider trading analysis can benefit from textual analysis of corporate disclosures from Michael Hagenau and 2 others, published in 2012. If even insiders sell the news why don't you?

Volatility and momentum

A good guide into momentum research is the book Quantitative Momentum from Wesley Gray and Jack Vogel. A couple of takeaways:

  • Short term momentum (up to 6 months) is subject to mean reversion
  • 3-year and even better 5-year lows have higher statistical returns. I like 5-year lows. See the paper Return reversal in UK shares from Glen Arnold and Rose Baker (2007).
  • Avoid stocks with sudden large bumps such as Liniu Technology Group (LINU).
  • Best momentum stocks are rising smoothly: with the most days up compared to days down over the past year. Their momentum signal is the past return multiplied with the difference in percentages of days up and down.
  • Momentum investing requires much trading

A very cheap stock close to a 5-year low is Changan Minsheng APLL Logistics Co. This automotive supply chain company is cheap according to multiple metrics, such as P/B, P/E, EV/EBIT and Price/Free cash flow. It is partly owned by the Chinese state but the Chinese state does not have complete control.

Actually Gray and Vogel started looking at smooth momentum after reading Frog in the Pan: Continuous Information and Momentum published in 2013 by Da, Gurun and Warachka. After digesting I think smooth momentum results from informed investors doing their homework. The effect is largest for small caps and stocks with low analyst coverage. Over a relatively long period these informed investors continue buying which causes momentum to be smooth. Smooth momentum is a good measure of quality.

Momentum with many hops and bumps may be event driven, or driven by pump and dumps, bottom seekers, etc. The stocks with the most discrete momentum have negative statistical returns. This is not a good statistical result for many strategies around technical analysis or corporate events. There are exceptions though, such as merger arbitrage plays.

Liniu Technology Group is a stock with sudden pops. The stock might be promoted. Pops seem to occur around news about their new trading platform for the Chinese agriculture sector. The recent pop happened without news. I must say it is very tempting to wait for a low in Liniu Technology Group, invest in it and then sell at a big pop. The pops are almost guaranteed to happen, but unfortunately, you never know when and what is really low. I have done this successfully, but after reading Quantitative Momentum I passed on waiting for the recent pop. I regret that: I should have been more flexible. Maybe there are still good trading strategies with such stocks: more research is necessary.

Another great book is Dual Momentum Investing: An Innovative Strategy for Higher Returns with Lower Risk by Gary Antonacci. The drawback of pure momentum investing is its volatility. Therefore, he suggests choosing between 3 asset classes: bonds, a US stocks index fund and an international stocks index fund. Switch every month to the asset class with the best momentum. See also his paper (updated in 2016): Risk Premia Harvesting Through Dual Momentum. Some of his good results come from declining bond yields over the past 40 years. Some confirmation of the approach is given in Gray and Vogel's book. To some extent, it is also used in one of their funds: Alpha Architect Value Momentum Trend ETF (VMOT). Dual momentum returns seem to be lower, but are much less volatile than returns from pure momentum investing strategies.

Correlation between good momentum and value investments is low. These are different investments. By allocating half of your portfolio to value investments and the other half to momentum investments, you can increase your risk-adjusted returns. See Value and Momentum Everywhere from Clifford Asness and 2 others (2012). This approach is also confirmed in Gray and Vogel's book. Both Gray and Vogel and Clifford Asness investigate the return of a portfolio with 50% of its holdings invested according to a value style and 50% of its holdings invested according to a momentum style. They find such a portfolio has the same or better returns than just a value portfolio or a momentum portfolio. I also use that correlation between value and momentum is low in my currency articles.

Momentum is a good example of a great strategy for professional investors but less so for small investors. Initially, I thought I could not use momentum for 2 reasons. First, because it is difficult to measure how smoothly stocks have gone up. I cannot exclude "bump stocks" like Liniu either. At least I thought I could not exclude them with an automated process because of insufficient data. For the same reason, I cannot (systematically) use 5-year lows.

Second, recall value investing combines very well with investing in illiquid smallcaps. Momentum also combines well with illiquid stocks but involves more trading. This extra trading may eat too much into returns, especially for illiquid stocks. Moreover it might be too time consuming for small investors.

But then I discovered O' Shaughnessy's Trending Value strategy. This strategy mixes value with momentum resulting in very high returns with low risk. The advantages are diversification from just value stocks and that it also works for more liquid stocks. Practical advantages are that it needs very few price points and it only rebalances once per year. That makes it suitable for an international version, which I implemented. More on this at the end of this article, after explaining the necessary concepts.

Better than Price/Book: Price/Retained Earnings

Instead of using Price/Book or Price/Tangible Book, it is better to use Price/Retained Earnings. See Book-to-market, retained earnings, and earnings in the cross section of stock returns from Ray Ball and others published in 2016.

This result makes a lot of sense to me. Capital raised from investors is often wasted on low returning investments. Many of such projects are quite different from the existing business. Capital earned by the company itself is usually reinvested in more profitable projects. Most of these projects have strong similarities with the existing business, making it easier to get high returns.

This metric is not available in most screeners. Instead I compute it manually for the EV/EBIT stocks and net-nets I discuss on Seeking Alpha. I also use the sum of retained earnings over the last 8 fiscal years as a proxy for retained earnings. This sum can be computed in an automated way.

China Advanced Construction Materials Group (CADC) is an example of a company with a low ratio Price/Tangible Book but with accumulated losses instead of retained earnings. It is also satisfies 5 of the 7 criteria for identifying distressed stocks as I will discuss below. It has too much debt for the company's limited cash flow. Therefore, I am short.

China Recycling Energy Corp. (CREG) is a very illiquid and small net-net with an extremely ratio Price/Tangible Book and an extremely low ratio Price/Retained Earnings. The stock is also a net-net. The company has financed projects for its clients. In return clients have bought shares of the company. If only half of this book value will be converted into cash, the stock will go up much.

Smallcaps or largecaps?

Smallcaps and microcaps perform better than largecaps, at least statistically. Numerous studies find this effect but some studies contradict this. It seems that the difference between smallcaps and largecaps got smaller since the discovery last century. Though I invest mostly in small companies I am not selecting my stocks based on this. The effect is not so big and I think it cannot be completely separated from other value factors. The effect is not as robust as, for example, with Price/Retained Earnings. I prefer to use value multiples to get an idea of cheapness. If the price goes up, a smallcap usually stays a small cap but multiples immediately get worse.

In 2015, Clifford Asness and 3 other authors published a paper Size Matters, If You Control Your Junk. They find investing in smallcaps still works when combined with value. In their definition of value, multi-year earnings and payouts play a prominent role. Not all excess returns can be explained by the value factor alone, and some of it can be attributed by the size factor. Their finding is consistent with my previous point on low P/B investing.

A problem with many other studies is they compare indices or index funds. Such instruments mostly invest in the largest smallcaps. That means you miss the most of the smallcap premium if you invest in ETFs. Smallcap ETFs such as EES, DES, DLS, DFJ, DGS, and GSD invest mostly in the largest smallcaps. These smallcaps have market caps of about $2 billion. As a result these WisdomTree funds do better than a comparable broad index but not much better.

My most promising microcap is Denge Yatirim Holding. This small Turkish financial is also trading much below liquidation value. It is cheaper than my screener tells me because it also counts the treasury shares.

By the way, this is a good example of how net-net investors need to make it happen. Not so many people can trade in the Turkish markets. But I need to make it happen so I took an extra broker just to be able to trade there. Surprisingly I could not find Denge Yatirim in their trading platform. So I complained, they fixed it and a couple of days later I bought it.

Strong balance sheets

I used to invest in low EV/EBIT stocks with strong balance sheets. That low EV/EBIT stocks perform better is a solid statistical fact. See Wesley Gray and Tobias Carlisle's book Quantitative Value. But how about low EV/EBIT stocks with strong balance sheets? Let's first determine what we mean with strong balance sheets. For a strong balance sheet, Total Assets is less than twice Equity. Gray and Carlisle confirm good results for low low P/E stocks with strong balance sheets from the US in their book. However, in certain years, this strategy was only invested in a single stock.

Belgian value investor Steven de Klerck has done research on this for Asian stocks. His data set is from 1995 to 2012, and covers stocks with a minimum market cap of 100 million USD in 12 Asian countries. Good statistical studies span at least 20 years, so the time frame is a bit short. He found low P/E stocks with strong balance sheets ("value+" stocks) perform slightly better than just low P/E stocks. He also found similar results for the US for a much longer period. See also his blog (diagrams missing).

Steven de Klerck's results are for the combination of low priced stocks with strong balance sheets. In What Works on Wall Street, Fourth Edition James O'Shaughnessy does not find strong balance sheets alone increase returns. Instead he finds the least leveraged stocks have lower returns. Because studies are contradicting each other the case for strong balance sheets is weak.

More research is necessary. Strong balance sheets might increase risk-adjusted returns, for example. What intrigues me is that many successful old-school value investors avoided companies with leveraged balance sheets. For example, Walter Schloss, Benjamin Graham and Warren Buffett. You would think it makes sense what they were doing.

What are Enterprise Value and EBIT?

The Enterprise Value of a company is simply the market cap plus the debt minus the cash. It is roughly equal to the price of the company for an acquirer, apart from a control premium. An acquirer can take out the surplus cash minus debt after obtaining control over the company. There are even companies with a negative enterprise value. That means an acquirer can take out more than the full purchase price. Stocks of companies with negative enterprise value have high returns but the strategy does not work always. For details see here.

EBIT is Earnings before Interest and Tax. This number does not depend on local tax percentages. It makes it easier to compare companies in different countries. Like Enterprise Value EBIT also takes out the effect of the capital structure of the company. A company can be financed with few debts and much equity or with much debt and minimal equity. In both cases the enterprise value is the same but the net profits are not. The difference is debt holders get more money in the latter situation.

The multiple EV/EBIT gives an acquirer a rough idea of the number of years it will take to earn his investment back. He can do that in several ways: he can keep the capital structure as it was before acquisition, he can leverage up the company or he can refinance the company with cheaper debt.

Low P/E, low EV/EBITDA or low EV/EBIT?

Is low P/E better than low EV/EBIT? Again, have a look at Gray and Carlisle's book, page 139. They find low EV/EBIT is the winner. It is better than low P/E and also better than low EV/EBITDA, on a risk-adjusted basis. Low Price/Free cash flow is about as good as low P/E. Low Price/Free cash flow and low P/E are also worse than low P/B and high Gross profit/Price.

In What Works on Wall Street, Fourth Edition James O'Shaughnessy also finds low EV/EBITDA works better than low P/E. On average low EV/EBITDA performs worse than low EV/EBIT because usually depreciation and amortization is a real cost.

As a rule of thumb I also think Enterprise Value multiples are better than market cap multiples. For example, I think EV/Sales is better Price/Sales, just as EV/EBIT predicts returns better than P/E. By the way, I also think EV/Gross Profit predicts returns better than EV/Sales.

Concentrated portfolios

Statistical stock research usually takes a property, like P/E or P/B, and then looks at the cheapest 10% of the stocks based on that property. Statistical research determines what the cheapest stocks are, based on past prices. For example, research could consider the cheapest stocks based on P/B from 1960 to 2000. In such a paper every year, a virtual portfolio is composed with the 10% cheapest stocks based on P/B, for 40 years. If such research is done for US-listed stocks, these portfolios contain hundreds of stocks.

But what would the return be if multiple value factors were used? And what would the return be when the virtual portfolios only contained the best 30 stocks?

I call such a portfolio of 30 positions with approximately the same size a concentrated portfolio. This is different from what other investors call a concentrated portfolio: usually they are talking about a portfolio with at most 20 positions and they invest more in what they consider the best stocks among these 20.

In his book, O'Shaughnessy also investigates combinations of multiple value factors. He finds this increases returns but more so decreases volatilty. James O'Shaughnessy also gives examples of great returns obtained by investing equal amounts in the 25 best stocks according to a combination of metrics, such as P/E, P/B and P/Cash flow. We are talking about returns of about 17%. International evidence for his results is given by James Montier in chapter 21 of his book Value Investing: Tools and Techniques for Intelligent Investment. The title of the chapter is Going Global: Value Investing without Boundaries. A concentrated portfolio of the 30 cheapest stocks ranked on EV/EBIT, P/E, P/B, Price/Cash flow, and P/S gives a return of nearly 25% per year. The minimum market cap of these stocks was $250 million.

ETFs cannot really invest in the smaller companies considered by James O'Shaughnessy and James Montier. So certain ETFs implement equal weighted concentrated investing with mid- and largecaps. For example, these mid/largecap ETFs from Alpha Architect: QVAL, IVAL, QMOM and IMOM. Their statistical results claim returns of about 18% for QVAL and QMOM investing in US-listed stocks. This is much less than the returns Montier found but about as good as O'Shaughnessy with his much simpler strategy. That strategy also invests only in US-listed stocks. Considering the current high valuation of US stocks, it is unlikely these backtracked results will be achieved going forward.

So you need to do it yourself if you want to achieve average returns of more than 20%. Consider, for example, my newsletter on Seeking Alpha. There I discuss the cheapest global stocks found ranking with several value factors like Montier did. But keep reading here first.

Value traps

A problem with deep value investing is that it is more volatile than the S&P 500. And investors are more sensitive to losses than to gains. No matter how good the average returns are, losers are remembered for much longer than winners. Therefore, scientists have investigated and designed several ways for avoiding value traps.

Avoiding value traps: Piotroski score

There is good statistical research on the Piotroski score. The higher the better the returns, on average. It is designed to increase returns for low P/B investing. See Piotroski's paper Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers from 2002. Charles Hyde confirmed these results for emerging markets in his 2014 paper An emerging markets analysis of the Piotroski F-score.

Much research still needs to be done. In particular there is not so much research on the combination of using Piotroski score and metrics like EV/EBIT, size, liquidity or momentum. in 2017 Turtle and Wang investigate a number of combinations in their paper The Value In Fundamental Accounting Information. A high Piotroski score works better with smaller, less liquid and more volatile stocks and especially well with stocks with good momentum.

Avoiding value traps: Campbell's 7 criteria

See the paper from John Campbell and others (version 2008) with title In Search of Distress Risk. Another useful paper of John Campbell and 2 others is Predicting Financial Distress and the Performance of Distressed Stocks published in 2010.

These 2 papers describe the failure probability of stocks. In other words: the chances a stock goes to zero. The predictive power of their research is much better than the Altman Z-score! These are good shorts. They satisfy the following 7 criteria:

  1. Last quarter's profit divided by the market value of total assets is below -0.023. The market value of the total assets is the market value of the company plus the book value of all liabilities.
  2. Liabilities divided by the market value of total assets is higher than 0.75.
  3. High volatility during the last 3 months (higher than 0.86). Since this data is not published it can only be determined qualitatively. Look for strong negative momentum. The best negative momentum is a gradual decay.
  4. Low stock price (around 2 USD or lower)
  5. Lack of cash: cash divided by the market value of the total assets is low.
  6. Small cap: market cap less than 1 billion USD.
  7. Low or negative return on equity. Negative equity should satisfy this condition as well.

Such stocks are easy to find using a screener, such as screener.co. I regularly screen for them. Look for hidden assets like real estate before shorting them. When reading short pieces on such stocks commenters often point to strong cash flows. But the market is efficient. Usually these cash flows are not enough to pay off the debts or to avoid a big diluting restructuring.

There are many strategies for shorting stocks but unlike with longs there are not many statistical shorts. I think shorting financially distressed companies based on these 7 criteria is the only statistical short strategy working in practice.

Shorting financially distressed stocks might be a good strategy for small investors. It has been very profitable for me at least. These stocks are usually illiquid and so small that it won't move the needle for professional investors. Even for small investors it might be too time consuming to analyze them. In fact, I should not do it for that reason. A good example of a distressed stock is Sphere 3D (ANY). This stock has been discussed at length on Seeking Alpha. Contributor Keubiko still keeps me up to date on Twitter.

Value traps: external financing

A useful takeaway from James O'Shaughnessy's book is to avoid stocks with negative cash flow from operations that got external financing in the past 12 months. It may not matter whether the company has borrowed more or has raised money by diluting shareholders. These stocks have negative returns. Also the 10% stocks with just the most external financing has slightly negative returns.

A related result is to avoid stocks with large increases in Total Assets. There are 2 papers. In 2009 Michael Cooper and 2 others published The Asset Growth Effect in Stock Returns. In 2011 Xi Li and 2 others published Asset Growth and Future Stock Returns: International Evidence.

It is best to compare Total Assets from last annual report with Total Assets from 2 years ago: (Total Asset{A} -Total Assets(A-2)) < 0.5*Total Assets(A-2).

As I pointed out, a good example of a company with lots of external financing and asset growth is Tesla (TSLA). Since I wrote that article last year, asset growth and external financing has even increased at Tesla.

An interesting observation from the international paper is the effect is largest in countries where issuing new shares is the easiest. These countries are Hong Kong and the US. The effect is the smallest in Singapore, where it is pretty difficult to dilute. Other countries with a weak asset growth effect are Switzerland, Canada, Greece, France and Belgium. Other countries with a strong asset growth effect are Australia, New Zealand, Norway, Denmark, Finland, Portugal and Ireland.

When you use Total Assets in a screener, you will see a restriction increases the quality of the companies returned. This metric has enormously increased the returns of my deep value investments, especially those listed in Hong Kong.

In Hong Kong, many companies take external financing to the extreme. Often, such companies are in the financial services business. They take small stakes in each other. People related to insiders may be front-running these transactions. Of course, such holdings are vulnerable to losses. Therefore, these companies have to raise new equity very often. Because the small stakes add up their proposals are approved in shareholders' meetings. See also David Webb's blog.

Not every increase in total assets may decrease statistical stock returns. Ultimately an increase in total assets is preceded by an increase in cash (or a decrease of debt). It depends on where this cash comes from. Increases in retained earnings (or decreases in accumulated losses) will increase statistical returns despite increasing total assets. Raising money from new equity decreases statistical returns.

There is also a case for avoiding companies having increased total assets much because they are very profitable. Profits often mean revert because of competition. That might be the reason why 5-year winners under-perform on average. See again the paper Return reversal in UK shares from Glen Arnold and Rose Baker.

Sometimes, these mean-reverting competitive forces are not so strong. In Quantitative Value Grey and Carlisle recommend looking for companies with increasing or stable Gross Profits/Total Assets, a high 8-year geometric average of Return on Assets, a high 8-year geometric average Return on Capital and/or good 8-year free cash flow relative to Total Assets. In particular, I like companies with a high stable or increasing Gross Profit/Total Assets. It seems Carlisle has the same opinion: see this recent interview.

Comparing this ratio for different companies in the same sector can also give much insight into competitive forces and profitability. I have done that for car manufacturers in this article.

Avoiding value traps: frauds and lies

Seeking Alpha articles often feature stocks accused of irregulaties or fraud. But such analysis is not based on statistical research. According to statistical researchers, it is not really possible to spot lies with certainty. But based on statistics, good bets can be made. Chris DeMuth explained it very well on his blog, don't skip the comment section. I can recommend Albert Vrij's book Detecting Lies and Deceit: Pitfalls and Opportunities. Among others, watch out for unnecessary statements, especially if they are formulated negatively: "I'm not a crook", "Read my lips: no new taxes", "I did not have sexual relations with that woman, Miss Lewinsky".

That people are lying does not necessarily predict any outcome. Nixon had to leave and Bush Sr. was not reelected but Clinton survived impeachment procedures. In the midst of the Greece crisis in 2014 Dutch finance minister Jeroen Dijsselbloem was negotiating with Greek finance minster Yanis Varoufakis. Unnecessary statements were released: "We are doing everything to reach a mutually beneficial agreement. Our aim is to conclude this agreement soon." and "We are trying to find the common points." In reality an agreement between these two was just not possible. There were no common points, period. But European leaders wanted an agreement whatever it took. So they told Greece to replace Yanis Varoufakis which they did. After that negotiations progressed much smoother and were concluded with an agreement.

Other strong warning signs are content free denials and not answering obvious questions. During conference calls sometimes there are questions about financing. Vague answers ("we are looking into various options") or simply no answer means the company will probably dilute soon.

It can be difficult to act on it. For example, a couple of years ago. I read a conference call from patent troll Crossroads Systems (OTCPK:CRDSQ). During the call, an analyst asked the dilution question. No answer. I should have sold the stock for a loss but did not do it because I did not want to take a small loss.

A recent example is Eros International (EROS). This company sold shares of its main asset: Eros International Media in India. Short sellers think Eros International sold these shares to repay debt. An analyst asked a question about it. The answer was somewhat vague: a sentence does not seem to be formulated well mentioning opportunistic selling, whatever that may be. My interpretation of the answer is indeed there is a liquidity issue. They have admitted it. Even though management also said "we have enough cash on our balance sheet" and was in "advance stages with a couple of [indiscernible] banks to refinance this amounts pretty quickly" last July. Recently Eros International said the short-term debt was extended but did not answer the question what the new deadline was. Furthermore Eros is suing short sellers, which also increases the chances something is wrong. Eros' management does not want to discuss certain things, otherwise they would not be suing short sellers.

In general people tend to believe "authorities" like CEO's more than independent short researchers. That is a bias. So fraud risk could be systematically underestimated. Short sellers like Jim Chanos mention fraud stocks together with cheap looking stocks as the best short ideas.

An interesting paper on fraud involving Chinese companies: Cheating in China: Corporate Fraud and the Roles of Financial Markets stocks published in 2014 by Minwen Li and 2 others. Factors increasing the chances of fraud are CEO ownership and short-term debt. State and foreign institutional ownership reduces (but not eliminates) the probability of fraud. Probability of fraud with companies in the western provinces is higher. Long term loans reduce the probability of fraud.

Note this paper is not about Chinese stocks trading in the US. Such stocks are even worse because insiders do not face justice if the fraud is exposed.

My personal impression is that it pays off to avoid Chinese stocks with a combination of high cash balances and (short-term) debt. In the PRC, cash balances can be easily faked. It is also wise to avoid Chinese companies whose Chinese subsidiaries are controlled via legal contracts (variable interest entities) instead of direct ownership. What I saw with dividend-paying Chinese cheap-looking stocks listed abroad is not so good either. Often, the dividend is used to pump the stock a little bit up just before the trust in the stock fully fades. Another one is what happens if the auditor resigns and accuses the company of fraud. If the company then hires a new auditor again and the new auditor signs off the annual report, that may restore confidence temporarily. But often this does not last long; see, for example, China Ceramics Co. (CCCL). And finally, watch out for large prepayments on the balance sheet, and in particular when these prepayments suddenly increase much. They may not be frauds, but stock returns are usually low.

I found a paper on the 100 largest listed companies in Italy: the more related party transactions the lower the returns. The title is Revenues From Related Parties: A Risk Factor In Italian Listed Company Financial Statements. The paper is from Fabrizio Bava and Melchiorre Gromis di Trana and was published in 2015. I think this research should be repeated with a much larger data set. The results are consistent with the well known phenomenon of the so-called control premium. An early paper was published in 1981 and also deals with the Italian stock market: The price of control in Italy. Unfortunately, this paper is behind a paywall. A free paper is Stock Market Prices and the Market for Corporate Control from John Armour and Brian Cheffins published in 2015.

Often fraud and lies are detected by looking at inconsistencies, notable changes and things that just do not make sense in financial reports. See the book Quality of Earnings by Thornton O'glove published in 1987. Another good book is Financial Shenanigans: How to Detect Accounting Gimmicks & Fraud in Financial Reports by Howard Shilit and Jeremy Perler, published in 2010.

Increases in accruals (Inventory, Accounts Payable, Accounts Receivable, Prepayments) are warning signs. The statistical relevance of accruals is again confirmed in James O'Shaughnessy's book. Also the Beneish number uses this. See Messod Beneish' publication from 1999: The Detection of Earnings Manipulation.

High Beneish numbers indicate an increased probability of fraud but they are pretty rare. So do watch out for illogical transactions: when a customer is also a seller or a supplier is also a customer. Or dilutions or acquisitions paid in shares that do not make sense when looking at the cash balance. And watch out for hidden liabilities and for intangible assets, or assets that could be worth much less than book value.

Another warning sign is consistently lower cash flows than profits. Or interest that does not match bank balances. And tax payments that are too low compared to the reported profit.

Insider trading

Insider buying is a good sign. Insider selling is not. Watch out for insider selling by the CEO or the CFO. They are supposed to know how much their shares are really worth. Also watch out for (insider) selling by value investors. For example, a couple of years ago, a director of EZCORP (EZPW) left. Shortly after, he sold out. This director was also a value investor, and a good one. He sold for a very good price. Also, in 2014 and 2015, insiders of Micron Technology (MU) sold for good prices. Then, the stock price declined. The CFO then bought for about 15 USD and later again for about 10 USD. Today, the shares are just below 40 USD.

Numerous short articles at Seeking Alpha mention the combination of weak corporate governance and insider selling. Did I mention Tesla yet? Another example is Cemtrex, see here. Indeed, this signals overvaluation. Hollis Skaife and 2 others have investigated the profitability of insider trades at companies with a material weakness in internal control. In their paper Internal Control Over Financial Reporting and Managerial Rent Extraction: Evidence from the Profitability of Insider Trading from 2011, they show those trades are more profitable than insider trades at companies with effective internal control.

Discover pumped stocks on Seeking Alpha

Many ideas take a long time to work out. How can readers decide whether the idea is valid? Of course the short thesis itself is important, but we can also get information from the comments. Look for commenters having commented only a couple of times on Seeking Alpha. Or commenters that have commented only on bearish articles of 1 or 2 stocks. Their comments are bullish, but they only comment on bearish articles. Their comments dismiss the short thesis without any sound arguments. They personally attack the author of the short piece and other short commenters. These are strong signs a short thesis is sound.

Another good sign for a good short thesis is if there are relatively many articles (bullish and bearish) attracting many comments. This is also a replacement indicator for trading liquidity.

This is not statistically validated. It is not always true either, for instance not with Straight Path Communications (STRP). If it was always true too many investors would always use it and then it would not work anymore. It may still be true with GlobalStar (GSAT). I suppose one day someone will pick up the challenge and do this kind of statistical research.

What if a short thesis does not get confirmed?

Many times a convincing short thesis will not be confirmed with new information from other sources than the short seller. In the mean time the market can make the stock very cheap. I do not know whether it is a good time to get in. But I have done that, for example, with Asian Citrus Holding (OTC:ACTFF) and Gulf Resources (GURE). I have traded these 2 stocks with over 50% profit in less than a year. If you decide such a stock is cheap enough to buy wait at least 3 years after publication of the short thesis.

Application: 7 years , so more than 3 years, have past since Orient Paper (ONP) was accused of fraud. Right now (September 22, 2017 at $0.8) it is extremely cheap: for example, the stock is at a 5-year low. But it still has a VIE structure as well, so do not buy it!

OTC stocks

OTC stocks are bad stock bets. See this paper: Asset Pricing in the Dark: The Cross Section of OTC Stocks published in 2012 and updated in 2013 by Andrew Ang and 2 others.

Stocks that were once listed on a regular exchange perform better than stocks that were not. There is much less liquidity in OTC stocks than in stocks traded on regular exchanges. Watch out for the more liquid OTC stocks, according to this paper. Furthermore momentum does not work as well for OTC stocks as for other stocks. I guess for OTC stocks momentum is rarely smooth. Just as on regular exchanges low volatility, small size and low P/B stocks perform better on the OTC.

The study excludes the stocks with the lowest prices (below $1) and with the least liquidity. The study also excludes stocks that do not publish their financials anymore. According to my very limited experience non-publishing stocks are also bad bets. Of course that may suddenly change once they start publishing financials again.

For example, DAC Technologies Group International (OTCPK:DAAT) does not report with the SEC. As a shareholder, I enjoy the privilege of getting their financials once per year in my email box. They are great, but unfortunately, no movement in the stock price. It has been a long wait so far.

BTW, it is impossible to exclude nonsense OTC-stocks in statistical research. See here for commentary going beyond statistical results.

Net-nets

Net-nets are stocks with a market cap less than their current assets minus all liabilities, or shorter said less than NCAV. The current assets mainly consist of cash, receivables and inventory. The book value of these assets minus all liabilities is a rough indication of the liquidation value. Common sense says the more a stock trades below liquidation value, the better the returns, at least on average.

Stocks trading below liquidation value have great average returns but are emotionally not the nicest stocks to invest in. You can apply everything I just told you about value traps, pumped stocks, frauds and lies. But even if you don't I expect your returns to be high.

Victor Wendl wrote a good book on the statistics of investing in net-nets: The Net Current Asset Value Approach to Stock Investing: A Guide to Purchasing Stocks Trading below Liquidation Value published in 2013. According to this book, one can expect between 20% and 30% return per year. Dividend paying net-nets have lower returns but are better investments on a risk-adjusted basis. The bigger the difference with the liquidation value the better. Net-nets with P/E below 10 perform also better than other net-nets.

A great article on net-nets is Ben Graham's Net Nets: Seventy-Five Years Old and Outperforming from Tobias Carlisle, Sunil Mohanty and Jeffrey Oxman. The same authors published a related paper in 2012: Dissecting the Returns on Deep Value Investing. Among others they also find dividend paying net-nets have lower returns. In addition, they find net-nets with negative earnings outperform profitable net-nets. They also find returns get better with higher multiples NCAV/Market cap, with one exception. The 20% of net-nets with the highest multiples performs worse than the other 80%.

In his book Deep Value: Why Activist Investors and Other Contrarians Battle for Control of Losing Corporations (2014), Carlisle shows us again that losing net-nets perform much better than profitable net-nets. In his book, he uses a longer period for back-testing than in his paper. Victor Wendl confirmed his result with a long study period also in 2014.

According to Wendl, the optimal holding period is 1 year but 2 years is almost as good. The optimal holding period of 1-2 years is confirmed by Ying Xiao and Glen Arnold in their paper Testing Benjamin Graham's Net Current Asset Value Strategy in London published in 2007. Alternatively, investors can follow the selling strategy suggested by Benjamin Graham: sell at 50% or 100% gain and otherwise wait and sell after 2 calendar years at market price. This selling strategy uses the power of momentum and takes advantage of irrational pops. Unfortunately, there is no research supporting it. All we know is Graham's own returns were around 20%, which is below what can be expected from statistical research. His returns could also be lower because he might have preferred profitable and dividend paying net-nets.

Another interesting open access paper is Testing Benjamin Graham’s net current asset value model from An Chongsoo and 2 other authors published in 2015. Unfortunately their study period from 1999 to 2012 is too short for firm conclusions. They investigate holding periods shorter than a year and find holding one-year provides the best returns.

They also confirm net-net investing performs much better than the S&P 500. In addition, this paper confirms Wendl's finding that returns from net-net investing are more volatile than investing in the S&P 500. When the market is up net-net investing outperforms the S&P 500 by a big margin. When the market is down net-net investing underperforms the S&P 500. They also study a hedging strategy: getting out net-nets when the yield on long term bonds is higher than the earnings yield of the S&P 500. Such conditions might predict a down market. This is also similar to dual momentum investing. They find this hedging strategy much increases returns and decreases volatility. Is that a free lunch? No: this kind of hedging is impractical and expensive because these stocks are very illiquid.

In their papers Carlisle, Mohanty and Oxman discuss the underlying reason for the great returns with net-net investing. Among others they found (financially) distressed net-nets perform much worse. This confirms Campbell's results summarized above. Two other important success factors for investing in net-nets are looking for low trading liquidity and long term reversion (5-year lows). Low beta (low correlation with the market) is also an important success factor but is more difficult to use in practice.

Lots of questions about net-nets still need to be answered: Does it make sense to use better approximations of liquidation value than NCAV? Is it better to invest in net-nets with high Piotroski numbers, and if so, how much better? Adjusting for risk could investing in profitable net-nets with a high Piotroski number be better than investing in loss making net-nets? I have learned not to invest in net-nets satisfying 5 or more Campbell's failure prediction criteria, but I would like to see more research into this as well.

At the moment, a very cheap and extremely profitable net-net is China Green Agriculture (CGA), almost for nothing because of fraud allegations. Do avoid China Ceramics Co. (CCCL) because this is a distressed net-net and therefore has lower returns. Polish Solar Co. not only has a high Piotroski number but is also a loss making net-net, with a high multiple NCAV/Market cap. At the moment Solar Co. is one of my most promising net-nets, but only on a statistical basis. You can buy it for about 20% less than my purchase price.

Always be flexible: I am shorting one net-net. I have shared it with my subscribers but am waiting for certain events to occur before sharing it in a regular article.

Quality

Remember, I started this article discussing investing under extreme uncertainty. Mathematicians and physicists try to understand the world by looking at extremes. Looking at returns from net-nets they might think the less quality the better the returns. How about the other end of the spectrum? Is it possible to get high returns from high quality investments? And what is quality anyway?

Quality can mean different things. Most importantly, there is assets quality, earnings quality and corporate governance quality.

During the last decade, people have taken asset and earnings quality to the extreme. After the financial crisis people became afraid of investing in stocks. Instead they have been investing in the very safest government bonds. As a result, these bonds now have extremely low yields. That was OK, as long as interest rates continued to go down. Of course, this could not go on forever. In fact, interest rates are going up and people got appetite for stocks again.

I am telling you this to make you aware how important quality nowadays is in investing. Looking at the low yields on many government bonds, there is still a bull market in quality. At the same time, quality is difficult to define, and therefore difficult to use for statistical investors.

Corporate governance quality I have discussed already above. I would like to add that bigger companies usually have higher corporate governance standards. To grow companies need trust. Without some minimum ethics standards a company does not get trust from its investors, customers and suppliers. It also works the other way around. Small companies sometimes try to get bigger to gain trust. This was the case with Amazon (AMZN) in the early days ("get big fast"). This is what certain Chinese smallcaps are trying. At least the CEO of Gulf Resources (GURE) pointed at this during one of his conference calls. However, Gulf Resources is different from Amazon in the nineties: for Gulf Resources it makes much more sense to buy back shares and pay a dividend, just as Sino Agro Food (OTCQX:SIAF) just announced. You never know whether such promises will be fulfilled, by the way.

Of course, there are exceptions. Big companies can also make extremely bad decisions. Take, for example, Verizon (VZ). They bought a useless 5G frequency for about $3 billion. Verizon also acquired Yahoo for $4.5 billion despite massive security breaches. Will Verizon follow HP (HPE, HPQ)? Last decade HP did so many value destroying transactions that it attracted the attention of short sellers like Jim Chanos. The stock cratered and a restructuring was necessary to get trust again.

Asset quality is very difficult to judge. A first step to safety is neglecting intangible assets. I recommend avoiding patent trolls, companies with lots of goodwill from acquisitions (Verizon?) and mining companies with large explored but undeveloped assets. If you want to find undiscovered intangible assets it is better to look for research intensive companies. Their research expenses normally do not end up as intangible assets on the balance sheet. Instead these expenses are treated as costs. Of course watch out for hidden liabilities as well, such as building obligations at Omagine (OTCQB:OMAG).

Valuable intangible assets can be found at technology companies. I own 2 such stocks: Micron Technology and Perma-Fix Environmental Services (PESI). When I bought Micron in 2013, I looked into new technologies for producing memory chips. Then, I looked into how far Micron was with developing phase change memory. My conclusion was they were definitely an important player in this area. They also were ahead in adding processing capabilities to memory cells: their Automata chip. Unfortunately, I experienced such developments take a long time. The show has just started. In the mean time, I cannot complain, since the stock almost tripled.

Super investor Warren Buffett mainly looks at earnings quality. I consider him a growth investor looking for long-term earnings growth. He looks for strong balance sheets and stable earnings growth. He tries to find cheap stocks with huge growth potential, such as The Coca-Cola Company (KO) in the '80s of the last century. He also tries to influence management to improve corporate governance.

In general, earnings quality seems to be important for stock returns. Combinations of low earnings related multiples such as Price/Sales, EV/EBITDA, EV/EBIT, Price/Retained Earnings and Price/Free cash flow increase statistical returns. But most important for Buffett is high margins are not going to be competed away. One of the best books explaining this is Value Investing: From Graham to Buffett and Beyond from Bruce Greenwald and 3 others, published in 2004.

They explain growth only adds value in combination with a franchise, so only if it cannot be computed away easily. They also give examples. For example, they describe Intel's (INTC) economies of scale. Only the chip company with the largest revenue can afford to do enough research to stay ahead.

Now, after over 10 years, the competitive landscape for manufacturers of micro-chips has changed. I am saying this without having done a detailed analysis. Instead, I just looked at the numbers of the past 7 years. What did I find? As Wesley Gray and Tobias Carlisle's explain in their book Quantitative Value a growing or constant ratio Gross Profits/Total Assets is an important signal for having a "moat". Maybe this ratio used to be great for Intel, but now it is just not anymore. It may improve again, especially since Intel also owns new technology for producing better memory chips.

Earnings quality through ranking stocks

Apart from the ratio Gross Profit/Total Assets Gray and Carlisle use 8-year geometric averages of return on assets and return on capital and the 8-year sum of free cash flow divided by total assets in their definition of quality. They rank stocks on low EV/EBIT and these quality parameters and then compute the combined rank.

Another quality strategy is described in Quality minus Junk by Clifford Asness and 2 others published in 2014. This strategy is a combination of good earnings (according to 6 parameters), payouts, volatility and 5-year earnings growth (again according to 6 parameters).

With so many parameters these 2 quality strategies cannot be replicated by do-it-yourself investors. I do not think it can be replicated by marketplace authors either.

Fortunately, there are 2 simpler alternatives. The easiest is buying one of Gray's Quantitative Value funds. I have not done that because the returns are much lower than those from investing in net-nets. I think this is because these funds invest in mid- to largecaps. I also suspect largecap quality might still be overpriced.

The second alternative is using a simpler definition of quality. In the paragraph Concentrated Portfolio's I already mentioned Montier's ranking strategy using 5 parameters. When applied to stocks with a minimum market cap of $250 million this strategy has an average return of 25% per year. From research it is clear earnings multiples are the most important factor for predicting returns. Therefore, I have replaced the Price/Sales multiple in Montier's ranking with Enterprise Value/Gross Profit. I rank global stocks on EV/EBIT, P/E, Price/Tangible Book, EV/Gross Profit, Price/Free cash flow and 3-month average volume/Public float.

Unlike Montier I do not limit my stock universe to stocks with a minimum market cap of $250 million. Scientists get their results easier accepted if they do that. But as a small investor I will get better returns with a minimum market cap of only $4 million. Slightly less than half of the ranked low EV/EBIT stocks has a market cap above $250 million. But very few of them have the best combined ranks. So it makes sense to lower the minimum market cap.

Unlike Montier, I use a liquidity parameter in the ranking. Recall what you read in my discussion on liquidity above. Ranking also on liquidity should increase returns for smallcap and low P/E investing, which is essentially what I do.

Before I started this ranking I thought the best ranked stocks would be as ugly as many net-nets, or even worse. But many of them turn out to have reasonable quality. For example, Grange Resources is such a stock, which has been discussed here. Grange Resources is not only one of the best-ranked stocks, but it is also a net-net. Among the cheapest stocks are even stocks with metrics suggesting high quality: Nansin Co. and Hengxin Technology. These 2 companies have a constant or growing ratio Gross Profit/(Total Assets - excess cash).

So this strategy nicely complements the famous net-net strategy: quality stocks combined with low quality stocks. I expect this combination to be less volatile than just investing in net-nets, while delivering similar returns.

(Update 12/10/2017 and 12/28/2017)

Momentum, again

James O'Shaugnessy investigated several variants of Montier's international value strategy just for US stocks. He reports geometric returns of about 17%. In his book What Works on Wall Street, he combines such a strategy with momentum. First, he ranks all stocks with positive 6-months and 3-months momentum on several value metrics and takes the 10% with the best combined ranks. Then, he ranks these 10% on momentum. He calls it Trending Value. The best 25-50 Trending Value stocks compound at around 21%, rebalancing every year. Moreover this is a low risk strategy with Sharpe ratio around 0.9.

Since this strategy seems to have great statistical returns I wondered whether I could do something similar, with the limited price data I have. Basically I take low EV/EBIT stocks with positive 12 and 6-months momentum. I take the 10% stocks with the best combined value rank. Then I should rank these stocks on momentum, et voila, I have an international version of Trending Value.

The very limited number of available price points includes the 52-weeks high and low. That allows me to create a new measure for smooth momentum instead of raw momentum. The details of this method have been published by Andreas Clenow in his book Stocks on the Move: Beating the Market with Hedge Fund Momentum Strategies in 2015. So, instead of ranking on raw momentum, I rank on smooth momentum.

Recall smooth momentum has much better returns than raw momentum. This is another reason why my international version of Trending Value will perform much better than the 21% found by O'Shaughnessy. Also, because I start with more liquid stocks this strategy is better actionable than just value ranked low EV/EBIT stocks.

I like symmetry. Therefore I also looked at a momentum strategy complementing my quantitative net-net investing. However with net-nets we are investing in the cheapest and least liked stocks. So there we cannot expect great and smooth momentum. Fortunately O'Shaughnessy found good returns combined with relatively low risk with microcaps (50-250 million USD) with low P/B and strong momentum. At least from 1965 to 2009. Actually this is the very best performing investment strategy in his book What Works on Wall Street. It does not always work though: results from before 1965 are not so good. Like the net-nets but unlike the low EV/EBIT stocks these microcaps do not need to be profitable. So this strategy indeed complements the net-net strategy.

I am replicating this momentum strategy with smooth momentum and low Price/8-year Retained Earnings instead of P/B. Again this strategy should perform much better because of the P/B replacement and the use of smooth momentum instead of raw momentum. In addition I also combine my rankings with liquidity which should also increase returns. Because of these differences I am not concerned about long periods of under-performance before 1965 for low P/B microcaps.

Final words

With investing there is no strategy that always works. New opportunities only arise again because other investors have been burnt before. If you invest according to multiple strategies however you spread your risks. Losses from an under-performing strategy are compensated by profits from other strategies. Therefore I have implemented 4 great international strategies.

These are statistically validated investing strategies with the highest returns. My 2 main strategies are investing in net-nets and investing in ranked low EV/EBIT stocks. I also rank net-nets by the way. Not only I rank them on NCAV/Market cap and liquidity but also on financial distress using Campbell's metrics. I implement both strategies globally. Both strategies have annual returns of about 25%.

Metrics for quality are often difficult to use in practice. These metrics are often incomplete as well: no metric covers all quality stocks. However I don't doubt investors can get extraordinary returns with chasing quality for good prices. Furthermore portfolios combining value and momentum stocks have lower risks. As I explained above smooth momentum is a good proxy for quality. Therefore I have implemented 2 extra strategies combining smooth momentum and value.

The ranked low EV/EBIT strategy combines well with momentum. Returns should be excellent at relatively low risk. In the US O'Shaughnessy found returns of around 21% with a Sharpe ratio of 0.9. My ranking on smooth momentum instead of raw momentum improves this strategy further. Because these stocks trade more liquid this strategy is even suitable for bigger portfolios. So that is the third strategy I research stocks for.

In my fourth strategy I look for microcaps with high retained earnings over the past 8 years relative to their market cap and smooth momentum. Risks and returns are similar to my low EV/EBIT strategy with momentum. Because these stocks do not need to be profitable this strategy complements my net-net investing.

I had to do something to make it happen, such as changing brokers, writing software to compute the rankings and doing the research on all these stocks. I had to learn what is important for these stocks (see above). This is typical for high returning investments. It takes effort to execute.

But fortunately, your life is easier. You can copy several steps from me. Such as reading this article. And getting access to international stocks, most importantly US, UK, Hong Kong, Japan, Singapore, Australia, and Canada.

You don't need to do the ranking and the research every month since I do it for you, if you take a subscription. All you need to do is reading my research, decide which stocks you like most and finally invest and receive the highest returns. Your return could be higher than mine: since you spend much less time researching stocks you have more time to reinvest your profits.

Disclosure: I am/we are long MU.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

Additional disclosure: Positions disclosed in the article text (company names in bold)