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The Beginner’s Guide To Volatility: ZIV

Summary We will cover the basics of ZIV. Examples of trading strategies for the mid-term futures. Current advice on ZIV. Welcome to the final part of The Beginners Guide to Volatility. I highly encourage you to view the two articles below, unless you have already read them. Some terms in this article were previously explained in the first two parts. Part One: The Beginner’s Guide To Volatility: VXX Part Two: The Beginner’s Guide To Volatility: XIV VelocityShares Daily Inverse VIX Medium-Term ETN (NASDAQ: ZIV ) This article will focus on the mid-term VIX futures. To be clear, these products are not the same as the short-term futures products we have discussed before. Some things are similar and others are very different. As a basis for discussion, we will use the inverse product ZIV. I really don’t recommend any other mid-term futures products. What are the mid-term futures? How would an inverse fund operate in the mid-term futures? See below: (click to enlarge) The mid-term futures span months four through seven. An inverse fund, which means in reverse order, sells short month seven’s contract. The fund will hold that contract (short) until selling it when it reaches month four. This process typically takes about 90 days depending on the month and expiration date of the VIX futures. As you may recall from the previous two articles, VIX futures are not the VIX Index and they trade independently of the market and level of stock prices. If you are on vixcentral.com, below the individual months you will see the month seven to four contango box. I have edited this into the above graphic. The first box represents the total percentage of contango or backwardation from month seven to four. For more on these terms, please view the first two articles in this series. The second box represents the estimated amount of contango or backwardation you could expect to profit/loss from during the next 30 days. It takes the first box and divides it by three. Again this is just an estimate. Contango/Backwardation in Mid-Term Futures Charts above and below made by Nathan Buehler using data from The Intelligent Investor Blog . Below, you will see an overlay of ZIV using the same time values to give you a clearer view of the data: Context It is important to view the above chart to put the mid-term futures into context. Although the data is back-tested, it is still relevant and useful. Had you viewed the current data alone (see below), it would appear mid-term future rarely go into backwardation. For the most part, this is true; however, you should be aware of negative economic events that would cause a deeper and more prolonged trek through backwardation. (click to enlarge) Why Consider Inverse Mid-Term Futures? Inverse mid-term futures provide a less volatile bet on decreasing volatility and/or sideways to rising markets. The best reward for your risk would be investing in these products after a dramatic and prolonged spike in the mid-term VIX futures. Historically, investing in mid-term futures now would give you a high risk and minimum reward scenario. See below for an example of a winning strategy: Winning Strategy: Let’s review two strategies that would work well. Buy ZIV once futures re-enter contango from backwardation. Risk of backwardation reappearing. Wait for backwardation and buy ZIV once 5% contango is reached. Visual (click to enlarge) Let’s go over the positives, negatives, and key takeaways with this strategy. Positives: Mid-term futures are already less volatile and less risky than short-term futures. This strategy, especially strategy two, is conservative in managing risk. Negatives: With strategy one, futures could reenter backwardation causing large losses. This opportunity will only occur once a year on average. Some periods may go longer without seeing backwardation present in the mid-term futures. It has been almost four years since the mid-term futures were in backwardation. Takeaways: Your focus on this decision should be in the strength of the U.S. economy and the ever more important global economic impact on the U.S. You need a positive economic outlook and improving or stable economic conditions for this to work as intended. Liquidity One thing you will notice about ZIV in comparison to short-term futures products is the drastically lower volumes. Average volume over the past three months is about 62,000, representing around $2.5-$3 million in transactions per day. As of writing, the fund has $123 million in assets under management (AUM). This represents about 2% of the fund being traded per day. When compared with the ProShares Ultra VIX Short-Term Futures ETF (NYSEARCA: UVXY ) that fund had about $342 million in AUM, and with its near-term average volume of 12 million shares, that represents around $360 million or over 100% of the assets in the fund being traded per day. ZIV will attract investors that are not looking for a day trade and have more of a buy-and-hold or longer-term view of the market. The low volume does not make this an illiquid investment. Conclusion The inverse mid-term VIX futures offer you another way to invest in volatility. It is a much slower pace than the short-term futures but also carries a more moderate level of risk if backwardation persists for a long period of time. Should things turn south, this product is much more forgiving in allowing you to exit a position. Short-term products often react much worse to immediate events. Now is not an opportune time to invest in the mid-term futures, but this article should have given you a good indication of what conditions would look like when the opportunity arises. I appreciate you reading this series, and I hope it continues to serves as a foundational education piece for volatility investors for years to come. My best advice is to fully educate yourself before investing in any VIX-related products. Knowledge is power and very important with this asset class. 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.

Rounding Up The Top International Equity REIT ETFs

Summary TAO has delivered the strongest total returns, but when it outperformed the pack in the past it usually fell right back within a year. My favorite international equity REIT ETF is VNQI primarily due to the substantially lower expense ratio. While VNQI is offering the best expense ratio here, there are options for international equity without the REIT structure that offer much lower expense ratios. International equity REITs offer investors a compelling opportunity for portfolio diversification, but high expense ratios limit the long term potential returns. To help investors identify which funds might work for them, I’m performing a quick comparison on several of the most liquid options. The ETFs I’m comparing in this piece are: Vanguard Global ex-U.S. Real Estate ETF (NASDAQ: VNQI ) iShares International Developed Real Estate ETF (NASDAQ: IFGL ) SPDR Dow Jones Global Real Estate ETF (NYSEARCA: RWO ) SPDR Dow Jones International Real Estate ETF (NYSEARCA: RWX ) Guggenheim China Real Estate ETF (NYSEARCA: TAO ) Comparing Returns Out of the 5 ETFs, VNQI is by far the youngest. That is a little disappointing because I would love to have a longer period for measuring returns. Since I had to limit my assessment of historical performance to the period in which VNQI was a viable investment, my sample size was reduced to only about three and a half years. The chart below shows the total returns earned for each ETF using dividend adjusted closes since the start of 2012. TAO was the clear winner for the period, but it also shows less correlation with the other ETFs. The weaker correlation should be expected since TAO is investing in China and the other four are showing a great deal of international diversification. In my opinion, TAO is the most dangerous due to the very high volatility of monthly returns (about twice the volatility of the SPDR S&P 500 Trust ETF ( SPY)), but the price charts also indicate that TAO seems to be risky when it deviates from the rest of the pack. The next chart uses those dividend adjusted closes and standardizes for share prices by charting returns over time as a percentage of their starting values. (click to enlarge) The real reason to use a chart like this is to be able to do a quick eyeball check for correlation. When I run correlation statistics, sometimes the values appear to be more correlated than they do when I just eyeball the chart. At a glance we can see that TAO and RWO seem more prone to deviating from the rest of the pack. However, we have also seen that the deviations from the pack are reversed within a year or less. At the moment, TAO is still above the other options and expecting international REIT valuations to stay strongly correlated would suggest it may be moving a little too high unless it is actually breaking out of a very long term connection to the other international REIT markets. Comparing Expense Ratios Remember that over the long term a buy and hold investor will see a meaningful part of their total return determined by the expense ratio. In a period of 3 or 6 months the expense ratio won’t make a large difference in the total returns but a difference of .5% in the expense ratio becomes very meaningful if it is allowed to compound for 30 or 40 years. Even without compounding, a difference of .5% in the expense ratio would devour 20% of the portfolio value over 40 years. The next chart compares the expense ratio for each ETF. Since TAO was the only ETF with a different gross and net expense ratio, I’ve included both in the chart. As you might guess from my feelings about expense ratios, my holding for the exposure is the Vanguard Global ex-U.S. Real Estate ETF. As I’ve been digging into the returns for international equity REITs, I’m finding that I’m less than impressed with the risk to return ratio. Within my portfolio the highest expense ratio comes from VNQI and I’m contemplating if I may want to sell off from the sector all together and just use the Schwab International Equity ETF (NYSEARCA: SCHF ) for my international exposure. I love the REIT structure for investing, but I’d rather see lower levels of volatility and lower expense ratios. The expense ratio on SCHF is only .08%, which thoroughly beats even VNQI. Do I want international equity REIT exposure enough to keep holding VNQI over SCHF? I’m not sure. I want my equity holdings to be long term allocations and if I was going to buy one international equity investment and then not touch it for 40 years, I think I would lean towards SCHF. At the moment, I’m out of my position in SCHF because I liquidated the position to fund a limit-buy order on a microcap. If you’re looking for that international REIT exposure as part of the portfolio, my favorite is VNQI. I’m just starting to question whether it offers enough risk adjusted returns to be worth the allocation I’ve given to it. A Note on RWO RWO holds international REIT investments, but it is really a global REIT ETF. It was holding around 55% of the portfolio in domestic equity REIT investments. The internal diversification is great for an investor that is seeking to get their diversification with as few tickers as possible, but I see no reason to pay .50% on RWO when an investor could pay .24% on VNQI and .12% on the Vanguard REIT Index Fund (NYSEARCA: VNQ ). Conclusion There are a few options for international REIT investing through ETFs. In my opinion, VNQI offers the most compelling option but I’m starting to question whether the sector is worthy of allocation when the expense ratios and level of volatility throughout the industry are so high. If I was holding TAO, I would contemplate selling it whenever it moved meaningfully above the other international equity REIT investments. Since I’m bearish on China and prefer to make long term investments, the strategy doesn’t work very well for me. If I sell out later in the year, I would probably swap to an international ETF with a lower expense ratio. I might also put part of the cash into a short term bond fund to reduce my total exposure to international equity since I am concerned about the correlation between international equity investments. Even if I’m not holding shares in China, if my concerns come to pass I would expect most international ETFs to take a hit even if there was no direct exposure to China. Disclosure: I am/we are long VNQ, VNQI. (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. Additional disclosure: Information in this article represents the opinion of the analyst. All statements are represented as opinions, rather than facts, and should not be construed as advice to buy or sell a security. Ratings of “outperform” and “underperform” reflect the analyst’s estimation of a divergence between the market value for a security and the price that would be appropriate given the potential for risks and returns relative to other securities. The analyst does not know your particular objectives for returns or constraints upon investing. All investors are encouraged to do their own research before making any investment decision. Information is regularly obtained from Yahoo Finance, Google Finance, and SEC Database. If Yahoo, Google, or the SEC database contained faulty or old information it could be incorporated into my analysis.

Freeport-McMoRan: A Lesson In Listening To The Model

Summary After I designed a model that was surprisingly effective at predicting movements in Freeport-McMoRan, I stopped listening to it. The model was clearly predicting the latest crashes in Freeport-McMoRan. As bad as things are for Freeport-McMoRan, the commodities suggest current pricing is pretty fair. Freeport-McMoRan (NYSE: FCX ) has been in freefall for the last month or so. There have been great opportunities to get out, but I missed them because I was focused on doing analysis on other parts of the market. This is a story of the massive mistake I made and how easily it could have been prevented. Predicting Commodity Prices From the start, I’ve said that my goal is not to predict commodity prices because predicting which way the prices will move is not within my skill set. When I make investing decisions, I want to be functioning within my area of expertise. When it comes to Freeport-McMoRan my area of expertise was building a model that was vastly better at predicting returns than I could be relying on any other tool. Despite knowing that my area of expertise was in building the model, I allowed myself to be swamped with work and didn’t return to regularly run my model the way I did during my first stint investing in Freeport-McMoRan. How I Should Have Done It The best method for me would have been to write it into my schedule that at least every week I had to completely rerun my model and decide if the stock was worthy of investment at that point given the results. Unfortunately, I didn’t do that. I ran the model around June 7th, decided it was getting risky and posted my downgrade and intent to keep running the model and watching for strong indicators to get out. The proper choice, clearly, would have been to sell out immediately rather than looking to get a tiny bit of extra return relative to my index by holding the position. Let this be a lesson to all investors to keep a close eye on those volatile investments. At the same time, it would have been wise for me to make some improvements to make the model easier to update. That may have encouraged me to keep checking it every day rather than allowing my early summer days to become swamped with other activities. I’ve taken both of those lessons to heart. The saddest irony, as you’ll see, is that the spread widened further, precisely as I predicted over the next couple weeks. Part of that time was when I was out of the state and away from my model. Clearly, I should have closed out the position before I left. Getting Up to Date I reran my model which uses the opening values for shares of Freeport-McMoRan along with the opening values for different ETFs that track 4 of the 5 commodities Freeport-McMoRan produces. I use those ETFs to track the estimated price change in futures contracts on the commodities as a way of seeing where commodity prices are going. Occasionally Freeport-McMoRan will move before the futures prices on the commodities but a large divergence has been a clear sign that a correction is coming. In using those commodities I built my model to predict average annual EBITDA for FCX over the next couple of years and then set a standard deduction from that value to estimate the other necessary cost implications because interest, depreciation and amortization are very real costs. Taxes is also a real cost, but will generally scale in such a way that it is automatically accounted for in my model. That should sound very complex to readers that didn’t see my previous work on Freeport-McMoRan, but the charts are easy enough to read. The chart below shows the values for EBITDA minus the static. As you can see, the lines show a very strong connection. (click to enlarge) While I like that method for looking at the correlation over the long term, I prefer to actually read the output using bar charts. The following chart shows the values for the last seven months: (click to enlarge) I designed these charts using the opening values for each ticker. We don’t have the opening value for Monday, so I inserted the closing prices for Friday, July 24th as “July 25th”. As you can see, over the last couple months the shares have fallen significantly but not by near as much as the expected earnings. Contrary to popular belief, Freeport-McMoRan stock was actually holding up well if we compare it to the fundamental earning power of the company. You may notice the left side of the chart is done in percentage terms. I standardized all the values in that chart based off the values from the start of 2014. There is no reason to think that the values from the start of 2014 were perfectly aligned, but it made it possible to reliably get both bars onto the same scale to compare relative strength. Relative Strength I put together another chart that makes it even easier to read. This chart standardizes based off percentage change from the values on May 20th. (click to enlarge) Had I been disciplined enough to force myself to update the spreadsheet more regularly, I would have been out without a problem. I’m providing an even larger version of the very clear “Get the **** out” signal: By the middle of June the model was sending off extremely strong sell signals. When I tried to do an eyeball test of the movement by simply looking at price charts in early July, I thought the commodities were moving before Freeport-McMoRan and started to doubt my model. If I had updated it completely, I would have seen that Freeport-McMoRan was simply catching up with the losses the model was predicting and I would’ve got the heck out. What Does It All Mean for Freeport-McMoRan? Based on my model, the closing values put us fairly close to fairly priced. That makes decisions to buy or sell fairly neutral. The biggest concern on buying is that the volatility is enormous. I’ll be putting in some work to make the model easier for me to update and then I’ll be watching for another one of those clear buying or selling signals. At the moment the model is quite neutral since the red line is only mildly taller than the blue. This wasn’t a case of my model failing me, it was me failing the model and paying dearly for it. I designed my system around having an index of ETFs that I could use as my benchmark. This is the same batch of ETFs that I use in estimating EBITDA based off commodity futures contracts. Relative to the benchmark, I’m “winning”. The benchmark is down 52.4% and FCX is down 48.4%. Somehow, this doesn’t feel like winning. Disclosure: I am/we are long FCX. (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. Additional disclosure: Information in this article represents the opinion of the analyst. All statements are represented as opinions, rather than facts, and should not be construed as advice to buy or sell a security. Ratings of “outperform” and “underperform” reflect the analyst’s estimation of a divergence between the market value for a security and the price that would be appropriate given the potential for risks and returns relative to other securities. The analyst does not know your particular objectives for returns or constraints upon investing. All investors are encouraged to do their own research before making any investment decision. Information is regularly obtained from Yahoo Finance, Google Finance, and SEC Database. If Yahoo, Google, or the SEC database contained faulty or old information it could be incorporated into my analysis.