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Pick Your Poison: No Return On Safety Or More Risk On Your Return

Summary Oil price moves and fluctuations in foreign exchange rates have increased the amount of risk associated with financial assets. The tail risk has increased as a result of the need for central banks to respond to oil prices and the performance of their trading partners. The size of the foreign exchange market and the amount of leverage involved make changes in exchange rates far more risky than changes in any other prices. Markets in Motion Lower oil prices are beneficial for oil consumers whether they be oil-consuming countries or consumers in the US filling up at the gas pump. That does not mean they are beneficial to financial markets. The price of a financial asset is determined by the return one expects to earn from holding the asset and the amount of risk or uncertainty associated with that return. A rapid change in any environmental factor increases the uncertainty associated with the return and therefore reduces the value of the financial asset. There have been numerous articles about the falling fortunes of the oil sector. On January 19, 2015 Barron’s presented a summary of one analyst’s estimates of how much the earnings of the S&P 500 would be reduced by the reduced earnings of the energy sector. The estimates do not seem worth quoting since they were developed without addressing the issue raised by the first sentence of this posting. While the energy sector’s earnings will be reduced, earnings in some other sectors will benefit. The net result is the introduction of considerable uncertainty into any forecasts of the profitability of a large number of companies. That uncertainty will repress stock prices. Thus, the uncertainty introduced by rapidly changing energy prices definitely has stock market implications. However, the December 17, 2014 posting entitled “Oil Prices” pointed out that the greatest macroeconomic risk associated with falling oil prices would be their impact on foreign exchange markets: “The foreign exchange markets are so big that a major dislocation there can have all sorts of unanticipated consequences.” Furthermore, it is quite conceivable that foreign exchange markets and oil markets could reinforce each other in terms of their financial market impact even when their macroeconomic impact diverges. By introducing instability, they both could be contributing to lower stock prices by increasing the risk associated with holding stocks. That can be true regardless of whether they have a positive or negative impact on the return. The December 17, 2014 posting went on to note: “One should keep in mind that financial institutions make markets in both currencies and foreign bonds. If a major financial institution gets caught with excess inventory of the wrong currencies or bonds, dislocation to the financial system could be significant.” One could argue that financial institutions also make markets in commodities such as oil, and therefore, that risk should be noted. However, as big as it seems, commodities markets are small compared to foreign exchange markets. On Jan.16, 2015 the Wall Street Journal was full of stories illustrating just how disruptive unanticipated foreign currency fluctuations can be. However, the foreign currency fluctuations were only very indirectly related to oil prices. The topic du jour was an action by central banks, current action taken by the Swiss central bank and anticipated actions by the European central bank and the Fed. Among the following articles: ” Swiss Move Roils Global Markets ,” ” Bankers, Traders Scramble to Regroup After Swiss Move ,” ” Fallout From Swiss Move Hits Banks, Brokers ,” ” Europe’s Smaller Central Banks Likely to Cut Rates After Swiss Move ,” ” Swiss Shock Tarnishes Central Banks ,” ” Swiss Bank Shares Plummet After SNB Move ,” ” Gold Shines as Traders Seek Safety From SNB’s Shock Move ,” ” Swiss National Bank’s Franc Move Buoys Dollar ,” ” U.S. Government Bond Yields Fall for Fifth Straight Session ,” and ” UBS and Credit Suisse Earnings Get a Swiss Finish ,” one gets an idea of just how important foreign currency fluctuations are. The scope includes non-oil commodity prices (e.g., gold), earnings of banks, pressures on central banks in countries like Denmark, impacts on the economies of many nations, government bond yields, stock market prices in some nations, and the reputation of central bankers. The disruption is not just restricted to turbulence in all those markets, it also involves financial institutions closing their doors (e.g., Global Brokers NZ Ltd.) or having to raise additional capital (e.g., FXCM Inc.). On January 17, 2015 the Wall Street Journal reported estimates of the losses of a number of financial institutions. The article entitled “Surge of Swiss Franc Triggers Hundreds of Millions in Losses” included estimates for Deutsche Bank (NYSE: DB ) and Citi (NYSE: C ). While the hundreds of millions of dollars involved might seem significant, for US banks they pale compared to the regulatory risk pointed out in the March 5, 2014 posting entitled “The Widows’ and Orphans’ Portfolio and US Banks.” Nevertheless, they are just one more reason to avoid US banks in a portfolio designed to have a low volatility and a stable return. Even when addressing issues that seem totally unrelated to foreign currency, it is impossible to ignore a market as large as the foreign currency market. A good illustration occurs in an article published on January 16, 2015 in the Wall Street Journal. It was entitled “What’s the Matter With Canada?” The major thrust of the article concerns Canada’s manufacturing sector, but it was impossible for the article to thoroughly address that issue without discussing the impact of oil prices on the Canadian dollar. It may well be that the decline in US stock prices so far in 2015 is an adjustment to the uncertainty introduced by the volatility in oil prices and currency markets. It certainly is consistent with the increase in uncertainty or risk associated with holding stocks. However, when foreign currency fluctuations are involved, there is a significant increase in what is known as “tail risk.” Countries can default, financial institutions can go broke, and governments can be forced to support their financial system and their economies. Such shocks are often viewed as exogenous and therefore impossible to predict. It is true; they are impossible to predict and this posting in no way constitutes a prediction that they will occur in the US. However, they are not totally exogenous and the ground is fertile for them to occur. Just that fact will impact the return on financial assets. The first half of 2015 will provide significant opportunities to investors as companies adjust to the recent volatility in oil prices and currency values. Because currency fluctuations can have large impacts on all variables from interest rates to revenue growth of individual companies, what is apparent is that regardless of what adjustments are made in a portfolio, the risk associated with any asset has increased.

Chart Of The Week: Bonds Versus Oil

Summary Important bottoms in crude oil have often matched important bottoms in Treasury yields. The bond market seems intrinsically stretched in context of its multi-decade progression. Long-term bonds are especially risky during the late stages of oil-market crashes. While many factors influence the bond market, it’s worth noting that cyclical bottoms in oil prices (NYSEARCA: USO ) have often matched cyclical bottoms in long-term Treasury (NYSEARCA: TLT ) yields. The oil crashes ending in March 1986, December 1998 and December 2008 are especially noteworthy. In all three cases, bond holders were severely clobbered after the free fall in oil prices ended. With the long bond currently near six-year-old resistance, it’s worth contemplating the damage that might be inflicted upon a reversal in the price of crude. Chart of the week: Oil prices versus long-term Treasury yields (click to enlarge) The bonus chart below presents a long history of 30-year U.S. Treasury prices expressed on log scale for comparability across time. In addition to the precarious set-up versus oil, the bond market seems intrinsically stretched in context of its multi-decade progression. The rally since December 2013 is “too steep, too fast.” The long bond seems to at least need a breather, and again, please note the tendency for sharp sell-offs following rocket-ship ascents. Bonus chart: 30-year Treasury prices (click to enlarge) Recap Important bottoms in crude oil have often matched important bottoms in Treasury yields. The bond market is currently stretched in context of its multi-decade progression. Long-term bonds are especially risky during the late stages of oil-market crashes. At this juncture, the two markets should not be contemplated independently. Now that you’ve read this, are you Bullish or Bearish on ? Bullish Bearish Sentiment on ( ) Thanks for sharing your thoughts. Why are you ? Submit & View Results Skip to results » Share this article with a colleague

NOBL Looks Solid Despite A Weaker Dividend Yield Than I Would Have Expected

Summary I’m taking a look at NOBL as a candidate for inclusion in my ETF portfolio. For having “Dividend” in the name, the yield isn’t as strong as I expected. The portfolio has been fairly steady, lower deviation of returns than SPY. The expense ratio is my only real concern here, because the gross and net are not the same. I’m hoping the net stays put. I’m not assessing any tax impacts. Investors should check their own situation for tax exposure. How to read this article : If you’re new to my ETF articles, just keep reading. If you have read this intro to my ETF articles before, skip down to the line of asterisks. This section introduces my methodology. By describing my method initially, investors can rapidly process each ETF analysis to gather the most relevant information in a matter of minutes. My goal is to provide investors with immediate access to the data that I feel is most useful in making an investment decision. Some of the information I provide is readily available elsewhere, and some requires running significant analysis that, to my knowledge, is not available for free anywhere else on the internet. My conclusions are also not available anywhere else. What I believe investors should know My analysis relies heavily on Modern Portfolio Theory. Therefore, I will be focused on the statistical implications of including a fund in a portfolio. Since the potential combinations within a portfolio are practically infinite, I begin by eliminating ETFs that appear to be weak relative to the other options. It would be ideal to be able to run simulations across literally billions of combinations, but it is completely impractical. To find ETFs that are worth further consideration I start with statistical analysis. Rather than put readers to sleep, I’ll present the data in charts that only take seconds to process. I include an ANOVA table for readers that want the deeper statistical analysis, but readers that are not able to read the ANOVA table will still be able to understand my entire analysis. I believe there are two methods for investing. Either you should know more than the other people performing analysis so you can make better decisions, or use extensive diversification and math to outperform most investors. Under CAPM (Capital Asset Pricing Model), it is assumed every investor would hold the same optimal portfolio and combine it with the risk free asset to reach their preferred spot on the risk and return curve. Do you know anyone that is holding the exact same portfolio you are? I don’t know of anyone else with exactly my exposure, though I do believe there are some investors that are holding nothing but SPY. In general, I believe most investors hold a portfolio that has dramatically more risk than required to reach their expected (under economics, disregarding their personal expectations) level of returns. In my opinion, every rational investor should be seeking the optimal combination of risk and reward. For any given level of expected reward, there is no economically justifiable reason to take on more risk than is required. However, risk and return can be difficult to explain. Defining “Risk” I believe the best ways to define risk come from statistics. I want to know the standard deviation of the returns on a portfolio. Those returns could be measured daily, weekly, monthly, or annually. Due to limited sample sizes because some of the ETFs are relatively new, I usually begin by using the daily standard deviation. If the ETF performs well enough to stay on my list, the next levels of analysis will become more complex. Ultimately, we probably shouldn’t be concerned about volatility in our portfolio value if the value always bounced back the following day. However, I believe that the vast majority of the time the movement today tells us nothing about the movement tomorrow. While returns don’t dictate future returns, volatility over the previous couple years is a good indicator of volatility in the future unless there is a fundamental change in the market. Defining “Returns” I see return as the increase over time in the value known as “dividend adjusted close”. This value is provided by Yahoo. I won’t focus much on historical returns because I think they are largely useless. I care about the volatility of the returns, but not the actual returns. Predicting returns for a future period by looking at the previous period is akin to placing a poker bet based on the cards you held in the previous round. Defining “Risk Adjusted Returns” Based on my definitions of risk and return, my goal is to maximize returns relative to the amount of risk I experienced. It is easiest to explain with an example: Assume the risk free rate is 2%. Assume SPY is the default portfolio. Then the risk level on SPY is equal to one “unit” of risk. If SPY returns 6%, then the return was 4% for one unit of risk. If a portfolio has 50% of the risk level on SPY and returns 4%, then the portfolios generated 2% in returns for half of one unit of risk. Those two portfolios would be equal in providing risk adjusted returns. Most investors are fueled by greed and focused very heavily on generating returns without sufficient respect for the level of risk. I don’t want to compete directly in that game, so I focus on reducing the risk. If I can eliminate a substantial portion of the risk, then my returns on a risk adjusted basis should be substantially better. Belief about yields I believe a portfolio with a stronger yield is superior to one with a weaker yield if the expected total return and risk is the same. I like strong yields on portfolios because it protects investors from human error. One of the greatest risks to an otherwise intelligent investor is being caught up in the mood of the market and selling low or buying high. When an investor has to manually manage their portfolio, they are putting themselves in the dangerous situation of responding to sensationalistic stories. I believe this is especially true for retiring investors that need money to live on. By having a strong yield on the portfolio it is possible for investors to live off the income as needed without selling any security. This makes it much easier to stick to an intelligently designed plan rather than allowing emotions to dictate poor choices. In the recent crash, investors that sold at the bottom suffered dramatic losses and missed out on substantial gains. Investors that were simply taking the yield on their portfolio were just fine. Investors with automatic rebalancing and an intelligent asset allocation plan were in place to make some attractive gains. Personal situation I have a few retirement accounts already, but I decided to open a new solo 401K so I could put more of my earnings into tax advantaged accounts. After some research, I selected Charles Schwab as my brokerage on the recommendation of another analyst. Under the Schwab plan “ETF OneSource” I am able to trade qualifying ETFs with no commissions. I want to rebalance my portfolio frequently, so I have a strong preference for ETFs that qualify for this plan. Schwab is not providing me with any compensation in any manner for my articles. I have absolutely no other relationship with the brokerage firm. Because this is a new retirement account, I will probably begin with a balance between $9,000 and $11,000. I intend to invest very heavily in ETFs. My other accounts are with different brokerages and invested in different funds. Views on expense ratios Some analysts are heavily opposed to focusing on expense ratios. I don’t think investors should make decisions simply on the expense ratio, but the economic research I have covered supports the premise that overall higher expense ratios within a given category do not result in higher returns and may correlate to lower returns. The required level of statistical proof is fairly significant to determine if the higher ratios are actually causing lower returns. I believe the underlying assets, and thus Net Asset Value, should drive the price of the ETF. However, attempting to predict the price movements of every stock within an ETF would be a very difficult and time consuming job. By the time we want to compare several ETFs, one full time analyst would be unable to adequately cover every company. On the other hand, the expense ratio is the only thing I believe investors can truly be certain of prior to buying the ETF. Taxes I am not a CPA or CFP. I will not be assessing tax impacts. Investors needing help with tax considerations should consult a qualified professional that can assist them with their individual situation. The rest of this article By disclosing my views and process at the top of the article, I will be able to rapidly present data, analysis, and my opinion without having to explain the rationale behind how I reached each decision. The rest of the report begins below: ******** (NYSEARCA: NOBL ): ProShares S&P 500 Dividend Aristocrats ETF Tracking Index: S&P 500 Dividend Aristocrats Index Allocation of Assets: At least 80% (under normal circumstances) Morningstar Category: Large Blend Time period starts: November 2013 Time period ends: December 2014 Portfolio Std. Deviation Chart: (click to enlarge) (click to enlarge) Correlation: 94.40% Returns over the sample period: (click to enlarge) Liquidity (Average shares/day over last 10): Around 178,000 Days with no change in dividend adjusted close: 5 Days with no change in dividend adjusted close for SPY: 0 Yield: 1.6% Distribution Yield Expense Ratio: .35% Net and .70% Gross Discount or Premium to NAV: .08% premium Holdings: (click to enlarge) Further Consideration: Yes Conclusion: For a dividend yield ETF, the yield was lower than I expected. However, the ETF has very strong liquidity which reinforces the correlation. While I’d love to see lower levels of correlation, I don’t expect to see low levels in an ETF designed to invest in several large dividend companies. The cross over between SPY and NOBL is going force correlation to be fairly high. ETF investors may be more impressed with the lower standard deviation of returns. The 5 days in which dividend adjusted close didn’t change were not reflecting any liquidity problems, as volume was not 0 for any of the days in my sample. The Net expense ratio isn’t bad, but I would want to look into provisions that would keep it from increasing. At a .35% net expense ratio I’m interested, but if that were to climb, my interest level would fade pretty rapidly. I have no problem with the holdings, though I prefer a little more diversification. I can’t complain too much though with the positions being around 2%. The standard deviation of returns was fairly interesting to me given how the stock ended up with almost exactly the same gains as SPY and very high correlation. I put together a little bit of theory on that in the section below. Be warned, it’s written for people that are already familiar with statistics and enjoy the theory. I put it after the conclusion because I believe it will confuse many readers and the information is not necessary to understand my analysis. For the statistics lovers The stock trades at around $50.00 rather than around $200 for SPY. The lower share price means smaller deviations in value (by fractions of a cent) may be rounded down to nothing. This could result in a slightly lower standard deviation of returns. Some readers thinking about the bell curve may recognize that this could be a double edged sword for the standard deviation. While rounding towards the mean would reduce the standard deviation, when the scale tips in the other direction the rounding could increase the standard deviation. The reason I expect those factors to not offset perfectly is because the bell curve is tallest in the middle. If the population was a standard normal distribution, the values should be rounded towards the center more often than they would be rounded away. On the other hand, each time that it is rounded away from the mean produces more standard deviation than the times in which it is rounded towards the mean. I don’t expect the factors to offset perfectly, but it is beyond my knowledge to know which way it would tilt the deviation because of the two opposing forces.