Tag Archives: applicationtime

Everyone Should Consider These Crisis-Immune Stocks

Summary After six years of rising share prices in the United States, I start to feel a little uncomfortable with current valuations. In this article I try to find out which companies and industries are likely to do well when the going gets tough in financial markets.. I calculated the share returns of American S&P 500 companies and European Stoxx 600 companies and industries during the financial crisis in 2008. I intend to increase the weights of stocks in my portfolio that are active in defensive sectors like consumer staples, health care, utility and energy. Readers can look for their own crash-resistant company in a spreadsheet list that is provided at the end of the article. My dilemma is simple. Professor’s Jeremy Siegel’s plea that stocks are the best asset class to own in the long run is very convincing (please read his brilliant books Stocks in the long run and The Future for Investors ). However, at the current valuations I strongly believe long run future returns will be low single digit at best for the S&P 500 as a whole, see this previous article of me. The simple answer to this dilemma is that I should look for the right stocks. I argued in earlier articles that I like to invest in companies that have their earnings protected by a wide moat such Wal-Mart (NYSE: WMT ), Nestlé ( OTCPK:NSRGY ) and Unilever (NYS: UN ). In my view these companies will be able to generate handsome returns despite above average valuations, because they can invest every dollar they retain out of profits in a very lucrative way. In previous articles, I reasoned that investors should ignore short term price fluctuations if they are convinced the earnings power – that is the possibility to reinvest retained earnings in a lucrative way – has not changed. As long as the sustainable competitive advantage of the company – or what super investor Warren Buffett calls a moat – is unaltered, there is absolutely no reason to sell your shares. This point of view makes perfect sense in theory. In practice when shares plummet day after day and everybody thinks the end of civilization is near, it is extremely difficult to assess the long term earnings power of a company. Therefore, the purpose of this article is to find companies that are great investments and tend to do well when things get tough in financial markets. Forget useless math If have read dozens of (academic) papers and books on the concept of risk. The trouble is that most of the metrics used in finance – think volatility, beta, Value at Risk, etc – are close to useless in the real world because they explicitly or implicitly assume share returns are distributed according to a so called normal distribution (almost all the returns are close to the average). In the real world investors are faced with outliers, or returns that are light years away from the average. Although the academic world tries to construct models that try to deal with outliers, the approach I use to capture risk of individual shares in this article is extremely simple (the way I prefer things to be). I calculated the returns of stocks in particular sectors and individual stocks in the United States and Europe from top to bottom during the credit crisis. To be honest, the saying ‘financial markets have no memory’ seems applicable to me. I was a little shocked by the returns that were spitted out by my Bloomberg terminal doing the analysis. In the credit crisis the S&P 500 and Stoxx 600 – the 600 biggest European companies by market capitalization – lost 55.2 percent and 58.2 percent respectively of their value from top to bottom during this period. Stomach this! Stocks lost more than half of their value during the credit crisis Index Top Bottom Total Return S&P 500 index 10-9-2007 9-3-2009 -55.2% Stoxx 600 1-6-2007 9-3-2009 -58.2% Source: Bloomberg. Nowhere to hide I suspect that most readers are familiar with the story about the statistician who drowned in a lake with an average depth of six inches. Averages can be dangerous as the distribution around the average can be wide. Therefore, I grouped the companies in industry segments to see how each segment reacted during the crisis. I use the Global Industry Classification Standard (GICs, you can find which industry group belongs to which sector on this wiki page). Which American industry did best and worst during the credit crisis? Returns of S&P 500 Companies Returns of Stoxx 600 companies Sector # Mean Rec. return Sector # Mean Rec. return Consumer staples 33 -33,1% 49,4% Energy 23 -32,7% 48,5% Health care 50 -39,1% 64,3% Health care 36 -33,9% 51,4% Utility 29 -40,9% 69,3% Telecom services 19 -35,2% 54,3% Energy 37 -49,2% 96,8% Consumer staples 44 -36,8% 58,3% Materials 26 -50,5% 101,9% Utility 25 -38,8% 63,3% Information technology 62 -51,2% 105,1% Materials 48 -50,3% 101,1% Consumer discretionary 77 -53,6% 115,4% Information technology 27 -52,3% 109,7% S&P 500 -55,2% 123,3% Industrials 111 -54,7% 120,6% Industrials 60 -55,8% 126,0% Stoxx 600 -58,2% 139,0% Telecom services 6 -56,3% 129,0% Consumer discretionary 81 -60,1% 150,7% Financials 86 -68,1% 213,4% Financials 121 -64,6% 182,1% Source: Bloomberg. Return represents total shareholder return, including dividends. # represents the number of companies within each sector. Recovery return is the return necessary to recover your initial investment. Given the nature of the last big crisis I suspect few readers will be surprised by the worst performing sector: financials. Financial companies lost a staggering 68.1 percent in the U.S. and 64.6 percent in Europe of their market value from top to bottom. Note that in some cases the investors had to deal with the worst thing that could happen to a value investor: a permanent loss of capital. For example Lehman Brothers went bankrupt and both Bear Stearns (JP Morgan) and Wachovia (Wells Fargo) were absorbed by other investment banks. It is good news for investors that the top performing sectors are also fairly similar on both sides of the ocean. The sector consumer staples (mainly food, beverages, tobacco and personal products), Health care (equipment, pharmaceuticals and biotech), Utility and Energy are all represented in the top five in both the U.S. and Europe. The average returns of these sectors are all above the average of the market. Do not get me wrong: the performance was still horrible. This was the scary thing of the credit crisis: every share and asset class – even gold! – collapsed due to the a complete loss of faith in the financial system. But – and this is in my opinion very important – even in the credit crisis it still mattered a lot if the value of your portfolio dropped by 33 percent (fully invested in consumer staples), 55 percent (invested in the index) or 68 percent (fully invested in financials). Let’s do the math. If the value of a portfolio drops by 33 percent an investors needs a return of about 50 percent to get back to where he or she started. But if you lost 55 percent or 68 percent of value an investor needs a return of respectively 123 percent (factor 2.5) and 213 percent (factor 4.3!) to recover you initial investment value. You find the ‘recovery returns’ of each individual sector in the table above. As a side note I like to inform you that I also examined the returns of each industry in the aftermath of the burst of the internet bubble in 2000 in both the U.S. and Europe. In that period the same defensive sectors outperformed the market (most of these sectors even realized positive returns as the loss in market capitalizations was concentrated in internet companies). A quest for cheap crash proof stocks After a 6 year period in which markets have treated us well – again leading to expensive stocks – it makes sense to me to increase the weights in my portfolio to stocks that tend to do well in downturns. Therefore, I am looking for stocks that are active in the consumer staples, health care, utility and energy sector. However, although I favor the simple over the complex, there is always the risk of taking too many shortcuts. An investor always runs the risk that stocks that were resilient in 2007 will prove to be horrible investments during the next crash. The thing I do to deal with this problem is to look at valuations. As a value investor, I believe the price you pay determines the return of a financial asset. This implies an investor can pay too much, even for the most defensive stock. My method to find crash proof shares is fairly straightforward. In this spreadsheet you find the names of the shares of the S&P and Stoxx companies, its sector and return during the credit crisis (source: Bloomberg). Moreover, I added the P/E-ratio in 2007 (pre-crisis) and the current P/E of every share. In my quest for resilient stocks I look for shares in defensive sectors that have P/E-ratios that are similar, preferably lower, than before the crisis. In the last step an investor should investigate if there is a reason for the low valuation. The investors should for instance examine if the nature of the business have changed permanently in the past 6 years due to divestitures or acquisitions. Investors should also try to assess whether the markets for its end products have structurally changed due to disruptive entry of new competitors (although I believe one can find value in oil today, some investors believe this could be the case with oil stocks). I additionally cannot stress enough the importance of a strong balance sheet. In the aftermath of the credit crisis, I have seen billions of shareholder value getting destroyed by overleveraged companies that faced a decline in cash flows and had to raise capital at very unattractive terms for existing shareholders to survive. Wal-Mart as an example It is beyond the scope of this article to examine individual stocks in great detail. For now I only want to have a close look at the best performing sector in the U.S. during the credit crisis: consumer staples. The best performing stock in this sector is retail giant Wal-mart. To me it is absolutely amazing this stock gained 7 percent in the worst investment climate ever. In this long read article, I extensively argue that Wal-Mart is an attractive investment at the current valuation. After my analysis of today, I decided to increase my position in the company. I not only expect attractive long run returns of Wal-mart, I also expect the stock will be resilient in an unfortunate scenario where markets start turning against us. Thanks for reading, and I hope you find some great stocks yourself by scrolling down the list — please let me know which. Editor’s Note: This article discusses one or more securities that do not trade on a major U.S. exchange. Please be aware of the risks associated with these stocks. Disclosure: I am/we are long WMT. (More…) 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.

Does Cotton Correlate To Oil?

Summary We compared the top oil and cotton ETFs; BAL and USO. Updated on global supply and demand. Events that could influence the short-term price of cotton. In this article on cotton we are going to focus on oil prices vs. cotton prices. Polyester is a competitor of cotton and lower oil prices allow for lower polyester prices. How much does cotton correlate to oil prices? That is a hard question to answer, especially given the large swings cotton has seen over the past decade. These swings skew correlation data and are caused by other events, namely China’s build out of cotton reserves in 2011. What I will seek to do is remove those years from the data and see if there is a correlation or not. For purposes of correlation we will take a look at January 2012 to present. Today we will focus our discussion around the iPath Dow Jones-UBS Cotton Total Return Sub-Index ETN (NYSEARCA: BAL ). BAL correlates perfectly to the price of cotton. For more information on BAL and its perfect correlation to the sub index in which it tracks, please view this article . With reasonable fees and proper tracking it is your best vehicle to use when trading cotton. Below is a table comparing BAL to the United States Oil ETF, LP (NYSEARCA: USO ): (click to enlarge) Chart obtained from buyupside.com An even more interesting take on the data is when you compare the two ETFs side by side in a single chart. Notice the large drop in oil prices beginning in July of 2014. Despite the continuing plunge in oil prices, cotton fared well over the last year. The following table from iPath provides other correlations to BAL. (click to enlarge) The results show that cotton correlates to the price of oil more than any other index. There are many variances and the correlation is far from perfect, but significant enough to point out. The Outlook for Cotton In previous articles we reviewed the 2015 outlook for cotton ( see here ). Last month we took a look at how the flooding in Texas was providing temporary price support to cotton ( see here ). I believe the flooding in Texas only delayed planting and shouldn’t cause any substantial decrease in supply. Pricing did respond to this event but has since trended back down. Last week the World Agriculture Supply and Demand Estimates (WASDE) raised their midpoint average price received to 62 cents per pound, with a high of 70 cents and a low of 58 cents respectively. Now this does not provide much of an opportunity for investor as cotton is currently trading at around 65 cents per pound. Global Factors The global supply and demand estimates still indicate lower consumption and higher ending inventory (stocks). China has led the drop in consumption due to strong competition from polyester amid the low oil prices we talked about above. China continues to be a dominate force behind cotton prices. They have the world’s largest inventory of cotton and are the largest consumer followed by India. Both of these countries export the majority of cotton they consume after manufacturing it into various clothing and discretionary items. The global economy, especially that of the United States and other consumer nations, should remain on the watch list of any cotton investor. Consumption aids in the demand for cotton. Production (click to enlarge) Table retrieved from the U.S. Dept. of Agriculture Farmers around the world continue to choose more profitable crops over cotton, especially here in the United States. I predicted this in my 2015 outlook for cotton. It really is a no brainer if you think about it. If you have multiple businesses to choose from, you would pick the one you think would be the most successful; the same thing farmers do. Conclusion I would say the biggest catalyst for cotton in the short-term would be a rebound in oil prices. Other possible events include natural disasters such as a hurricane hitting Texas. On simply a supply and demand perspective current market conditions look slightly weak. I look forward to continuing coverage on BAL and will put together a 2016 outlook within the next several months. If anything changes you can expect an update about it here on Seeking Alpha. I am assigning a neutral rating on BAL going forward and I do not see any reasons, other than those mentioned about, to recommend it as a buy at this time. Going into 2016 I see a slight trend upward as farmers balance stocks and hopefully global consumption picks up. Thank you for reading and I wish you a profitable rest of 2015. Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. (More…) 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.

Improving Basic Structural Arbitrage

Adding long dollar index exposure is highly logical. It reduces the strategy index’s correlation to bonds. And it provides multiple forms of statistical hedging. As long time readers know, the idea behind Structural Arbitrage is that profits are possible by acting as a synthetic insurance company which sells expensive insurance in the volatility market, and then synthetically reinsures that market risk with long duration government bonds. To review, here are the basic strategy index’s rules: I. Buy XIV (NASDAQ: XIV ) with 40% of the dollar value of the portfolio. II. Buy TMF (NYSEARCA: TMF ) with 60% of the dollar value of the portfolio. III. Rebalance weekly to maintain the 40%/ 60% dollar value split between the positions. XIV is the inverse short term volatility ETN. TMF is the 3X leveraged 20+ year government bond ETF. Here are the strategy’s results in a linear scale: (click to enlarge) For those of you who don’t believe that such a simple strategy index could work, I made the strategy public in an ebook back in 2013. If a relationship is robust, it can still make money even if it is widely studied. The potential problem, though, is the correlation of the strategy to bonds, as we can see in the graph below which compares the strategy to its TMF component: (click to enlarge) Even though the R squared value of a 0.61 correlation to TMF isn’t horrible, it’s not great either. And as I’ve said again and again , I believe that the strategy in its original form should be abandoned, due to the risk of a prolonged bear market in bonds. A simple improvement would be to add long dollar index exposure through an instrument such as UUP. The logic is “if then” logic. If interest rates rise, TMF will fall, but the dollar might strengthen, since the higher yield makes dollars more attractive than alternatives. What exactly would an improvement consist of? Here are the improved strategy’s rules: I. Buy XIV (NASDAQ:) with 15% of the dollar value of the portfolio. II. Buy TMF (NYSEARCA:) with 15% of the dollar value of the portfolio. III. Buy UUP (NYSEARCA: UUP ) with 70% of the dollar value of the portfolio. IV. Rebalance annually to maintain the 15%/ 15%/70% dollar value split between the positions. Here are the strategy’s results in a linear scale: (click to enlarge) The strategy now lags the S&P by 1.1% per year, but the drawdown is reduced by almost 8 percentage points, far improving the CAGR/Max drawdown ratio, called the MAR, compared to that of S&P 500. Let’s take a look at the correlation of the strategy to its long bond TMF component: (click to enlarge) The improved strategy index’s correlation to TMF dropped from 0.61 to 0.35. And the improved strategy index’s correlation to the S&P 500 is only 0.13 (pretty amazing) dropping from an already impressive 0.17 level. For the investor who is looking for a return stream which is largely uncorrelated to stocks and uncorrelated to bonds , this improved strategy index is pretty neat. Both long bonds and long dollar index exposure can often statistically hedge short volatility exposure. The lesson here is that multiple forms of hedging are usually better if the goal is robustness and non-correlation. Thanks for reading. Disclosure: I/we have no positions in any stocks mentioned, but may initiate a long position in XIV, TMF, UUP over the next 72 hours. (More…) 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.