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Free Bitcoin/Bitcoin Futures Quotes, Charts, & Historical Data

 
Thursday, December 14th, 2017 | Vance Harwood
 

Finding quotes and historical data for Bitcoin and Bitcoin futures can be an adventure.  Below I’ve assembled links to the online resources that I’ve been able to find.

In many cases, data is available from multiple sources.  I did not attempt to list all of them.

BTC Quotes

BTC Charts

 BTC Historical Prices

BTC Futures

  • CBOE/CFE  Symbol: XTB
    • Quotes
      • Spot: Gemini exchange
      • Cboe (including bid/ask)
        • Use “Enter Symbol” Field
        • Ticker construction:  XBT/ followed by month-year code (e.g, XBT/F8 = January 2018 expiration)
          • F=Jan, G=Feb, H=Mar, J=April, K=May, M=June, N=July, Q=Aug, U=Sept, V=Oct, X=Nov, Z=Dec
      • Cboe/CFE  (all months)
    • Historical Data  CBOE
    • Term Structure  Chart:  VIX Central/bitcoin
    • Reference exchange:  Gemini
    • Contract Size:  1 Bitcoin, cash settled  (Contract Specifications)
    • Initial customer margin 44%
      • Brokers may require much more margin ( e.g., Interactive Brokers is requiring $40K per contract–around 130%–on short contracts)
    • Trading Hours (USA Central Time)
      Type of Trading Hours Monday Tuesday – Friday
      Extended 5:00 p.m. (Sunday) to 8:30 a.m. 3:30 p.m. (previous day) to 8:30 a.m.
      Regular 8:30 a.m. to 3:15 p.m. 8:30 a.m. to 3:15 p.m.
    • Future settlement quote (once per day)
    • Option availability:  Earliest probably around March 2018

 

  • CME  Symbol: BTC
    • Quotes
    • Reference exchanges:  Bitstamp, GDAX, itBit, Kraken (combined into a composite quote via BRTI & BRR)
    • Contract Size:  5 Bitcoins, cash settled  (Contract Specifications)
    • Initial customer margin 35%
      • Brokers may ask for much more than this, especial for short contracts
    • Trading Hours:  Scheduled to start trading 18-Dec-2017
      CME Globex: Sunday – Friday 6:00 p.m. – 5:00 p.m. (5:00 p.m. – 4:00 p.m. CT) with a 60-minute break each day beginning at 5:00 p.m. (4:00 p.m. CT)
      CME ClearPort: Sunday – Friday 6:00 p.m. – 5:00 p.m. (5:00 p.m. – 4:00 p.m. CT) with a 60-minute break each day beginning at 5:00 p.m. (4:00 p.m. CT
    • Future settlement quote: BRR (once per day)  methodology) )   Historical Data

 

A Better Way to Model the VIX

 
Tuesday, November 28th, 2017 | Vance Harwood
 

Models are useful. They help us understand the world around us and aid us in predicting what will happen next. But it’s important to remember that models don’t necessarily reflect the underlying reality of the thing we’re modeling. The Ptolemaic model of the solar system assumed the Earth was the center of everything but in spite of that spectacular error, it did a good job of predicting the motions of the stars, planets, moon, and sun. It was the best model available for over a thousand years. But new data (e.g., phases of Venus as revealed by Galileo’s telescope) and errors in predicting the motions of the planets demonstrated that the sun-centric Copernican/Kepler models were superior.

There are a lot of models for the Cboe’s VIX. None of them are particularly good at predicting what the VIX will do tomorrow but they can be useful in predicting general behaviors of the VIX. The most popular model for the VIX (although people might not recognize it as a model) is simple mean reversion.

 Simple Mean Reversion

Car gas mileage is a good example of a simple mean reverting process.

Over time your car’s gas mileage will exhibit an average value, e.g., 28 miles per gallon. You don’t expect to get the same mileage with every tank because you know that there are factors that make a difference with your mileage (e.g., city vs highway driving, tire air pressure, and wind direction) but over time you expect your mileage to cluster around that average value. If you get 32 miles per gallon on one tank of gas you reasonably expect that next time you check it will likely be closer to 28. If the values start varying significantly from the average you start wondering if something has changed with the car itself (e.g., needs a tune-up)

A mean-reverting random walk is a relatively simple model and fits some of the basic behaviors of the VIX. Specifically, over time the mean value of the VIX has stayed stable at around 20 and the VIX exhibits range bound behavior—with all-time lows around 9 and all-time highs around 80.

However, there are many aspects of the VIX that aren’t well explained by a simple mean-reverting model. For example, a simple mean reverting process will have its mode value (the most frequently occurring values) close to its mean. This is not the case of the VIX; its mode is around 12.4—a long way away from its mean. The histograms below show that difference visually.

 

Another VIX behavior that departs from a simple mean-reverting process is the abrupt cessation of values below 9—almost a wall. For a normal mean reverting process you would not expect such a sharp cut off at the low end.

The Acid Test:  How good is the model for predicting the future?

Having a good model for a process is useful because it can help us predict at least some aspects of the future. For example, we can use our average gas mileage to decide whether we need to gas up before entering a long stretch of highway without gas stations.

A simple mean-reverting model is not particularly good at predicting the future moves of the VIX. If the VIX is low (e.g., 12 or below) a simple mean-reverting model predicts that since the VIX is far from its mean that will likely increase soon. But history shows this is usually not the case. Often the VIX can be quite content to hang around 12. This leads to news stories quoting various pundits stating “The VIX is broken” –when in reality they are just using an inferior model.

 As I said earlier there are VIX models out there that address some of these deficiencies. Unfortunately, the ones I know of are complex and not very intuitive. I believe the model that I describe below can improve our intuition considerably without adding too much complexity.

A Better VIX Model

A better way to view the VIX is that it behaves like the combination of two interacting processes: a specialized mean reverting process and a “jump” process. The jump process captures the behavior that all VIX watchers know—its propensity to occasionally have large percentage moves up and down. Since 1990 there’ve been over 86 times where the VIX has increased 30% or more in a 10 day period. The occurrence of these spikes is effectively random with a probability of happening on any given day of around 1.28%. It’s like a roulette table with 78 slots, 77 of them black and one red. If the ball lands on a black the normal reigns—if red then things get crazy. The graph below shows a histogram of the number of days between these 30% spikes in the VIX since 1990.

There’s nothing that prevents reds on consecutive spins nor is there some rule that reds become really likely if you haven’t had a red in a while. The roulette ball has no memory of where it landed on previous spins.

VIX jumps are generally not just one-day events; subjectively it looks like it takes around two weeks before the market reverts to more typical behavior. The model assumes that when a jump occurs it essentially drives the behavior of the VIX for 10 trading days.

The other process, the specialized mean reverting process, addresses the non-jump mode of the VIX—which is historically around 85% of the time. One of the key behaviors it needs to address is the slow relaxation in the mean value of the VIX after a big volatility spike rekindles a generally fearful attitude in the market. This decay process continues (unless interrupted by another VIX jump) until the average monthly VIX values drop into the 11-12 range.

The chart below illustrates this relaxation process.

 

This characteristic can be modeled by expecting the short term mean of the VIX (when it’s not jumping) to decay exponentially until it reaches its “quiet” mean of around 11.75. It works well to quantify this decay as having a time constant of 150 days.

With this approach, sans jumps, the difference between the current VIX value and its long-term quiet value will decay by 50% in 104 days. So if the VIX is at 30 the model predicts the mean will decline to 20.75 in 104 days [30- (30-11.5)*0.5=20.75].  If there are no jumps for the next 104 days the VIX’s mean would decline to 16.13. If a jump occurs in the interim the short term mean is reset to the VIX’s value at the end of the jump.

The other part of the specialized mean reverting process mimics the day-to-day volatility of the VIX. I used a formal mean reverting diffusion process (Ornstein-Uhlenbeck) to accomplish this. Despite its scary name, you can think of it as a random walk with the thing “walking” being attached to the mean with a spring—similar to walking a dog with a springy leash. The further the dog gets from you the larger the force pulling the dog back to you.

Unlike the simple mean-reverting model often used for the VIX, this process has a much tighter distribution, with the extreme values effectively limited to around +-20% from the mean. When the VIX is quiet this process replicates the firm lower limit on the VIX, a VIX of 9 is -21.74% lower than a quiet mean of 11.75.

Simulating the Model

 To implement/validate this model I estimated the key input variables and then used Excel to simulate 20-year volatility sequences. I then compared these time series to the actual VIX history and tuned the model’s parameters such that the key characteristics (e.g., volatility, mean, mode, decay rates) were similar to the VIX’s historic values.

Resulting histogram of historic VIX values vs the simulated combined process

 

The next chart shows an example 20 year time series of the simulated VIX combined process compared to the historic VIX. The two series aren’t time synchronized; my intent is to show how the simulated VIX time series has the same visual feel as the real VIX.

 

Conclusion

This improved model is not a path to riches. It isn’t any better than other models at predicting when VIX jumps will occur. However, this model does help us understand how the VIX behaves over longer time spans. In particular, during times of sustained low volatility, it predicts that the VIX will tend to stay low until the next significant VIX spike and not trend up like the simple mean-reverting model demands.

 

 

 

Quant Corner

  • The mean-reverting diffusion process used is an Ornstein-Uhlenbeck mean reverting diffusion process using a log-normal distribution. The volatility was set at an annualized 112% and the return to mean strength parameter ETA set to 0.3. The mean of the process is determined by the previous day’s VIX value minus the exponential decay factor that will decay the mean down to 11.75 over time if there are no additional jumps (Tau of 150 days). If the mean has decayed down to 11.75 the process acts very similarly to the VIX’s low volatility regimes (e.g., 2004-2006, 2016-2017) with the “return to mean” factor effectively acting to keep the VIX  higher than 9.0
  • The Jump process used (with a few small tweaks) is a compound Poisson process where the probability of a jump sequence is random with a probability of a jump being 1.28% per day. The jump sequence and its daily amplitudes are determined using a technique borrowed from rappers called sampling. Instead of trying to recreate the decidedly non-Gaussian distribution of VIX jumps I reused historic VIX jumps by randomly selecting, and replaying one of the more than 85 jump sequences since 1990 where the VIX jumped more than 30% in 10 days. Each jump sequence is 10 days long, with the first 2 days being the behavior before the jump.

How do VelocityShares’ EVIX and EXIV Work?

 
Thursday, September 21st, 2017 | Vance Harwood
 

In May 2017 VelocityShares introduced two new volatility funds, EXIV and EVIX, which track European volatility futures.  In digging into these funds I’ve encountered a dense mashup of the familiar and the foreign.  The differences between European Volatility futures and VIX futures are relatively small so it’s reasonable to view EXIV and EVIX as close cousins of VelocityShares’ XIV and Barclays’ VXX, however, these funds depend on a set of securities and processes with subtle and not so subtle differences with the mainstay USA volatility funds.

If you are not familiar with VIX futures based volatility Exchange Traded Products (ETPs) then I recommend you first take the time to read these posts on VelocityShares’ XIV and Barclays’ VXX before you tackle these new arrivals.

Some Basics

  • EVIX is a short-term long volatility fund that will tend to go up if European stocks go down significantly.
  • EXIV is a short-term inverse volatility fund that tracks the opposite of EVIX’s percentage moves on a day only basis. Because EXIV adjusts its assets at market close to achieve its daily tracking goal it does not behave like a true short of VIX—which can be a good thing or a bad thing depending on the market moves.
  • The Swiss bank, UBS AG, is the issuer of both of these Exchange Traded Notes (ETNs). They are structured as unsecured long term debt securities.  As of August 2017, Moody’s rating of UBS’ long term debt was: “A1 Not on Watch.”  The investor fee charged by UBS AG is 1.35% annualized for EVIX and EXIV, this compares to 1.35% for XIV and 0.89% for VXX.
  • The European Volatility futures that these funds track settle at expiration to the European volatility index VSTOXX. VSTOXX uses a methodology very similar to the CBOE’s VIX but instead of being based on the prices of S&P 500 (SPX) options the VSTOXX is based on STOXX option prices.
  • The STOXX index is comprised of 50 of the largest companies in the Eurozone and is capitalization weighted like the S&P 500. It does not include companies from the UK. These 50 stocks represent around 60% of the Eurozone stock market value. In comparison, S&P 500 represents around 80% of the total USA stock market capitalization. Similar to the S&P 500 index, the STOXX index does not include dividends, so the returns of actually holding the constituent stocks would be higher than the index indicates.  For the last 5 years, the STOXX dividends have averaged 2.5% vs 1.9% for the S&P 500.
  • EVIX and EXIV track indexes (VST1MSL & VST1MISL respectively) that theoretically hold a mixture of the two VSTOXX futures nearest to expiration. The mixture gives an expiration horizon of 30 days, similar to the VIX future based short term volatility funds like VXX and XIV.  These funds are fully divested out of expiring futures the day before their expiration/final settlement.
  • Both funds effectively do a daily end-of-day rebalance that adjusts the number of volatility contracts that they hold in order to maintain a 30-day average horizon. At the same time EXIV also does an asset rebalance such that its daily percentage move will closely match the opposite of EVIX’s next day daily percentage move (see How Does XIV Work? for more on this).

 

  • Standard processes and rough equivalences in key securities

 

Generic Securities

Categories

European Version USA Version Standard Processes
Volatility Futures VSTOXX futures VIX futures Settlement
30-day Volatility Index VSTOXX VIX Index calculation
Large Cap Stock Index STOXX 50 S&P 500 Stock index selection
Large Cap Stock Options OESX SPX Settlement, Cash Settled, European exercise

 

    • The key European securities and processes are similar to the USA markets but in no case have I found a pair of processes that are identical. For example, VIX futures settle to a special opening quotation of the CBOE’s VIX® soon after market open on expiration days whereas VSTOXX futures final settlement price is determined by the average VSTOXX index level between 11:30 and 12:00 CET on the day of expiration.
    • A significant difference between the VIX and the VSTOXX index is that the VSTOXX calculation does not incorporate options with bid prices below 50 Euro. This contrasts with the VIX’s calculation which uses options with bids as low as $5—which increases the chances that an institutional player might attempt to influence the VIX’s settlement value in their favor by buying or selling cheap out-of-the-money puts.
  • Quotes / Historical Data
    • While free quotes for EXIV and EVIX are easy to get with the usual sources (Online brokers, Yahoo, Google), obtaining quotes for the underlying securities/indexes is tougher. The ones I’ve found so far are:
    • STOXX
    • VSTOXX (ticker V2TX or DVY00)
    • VSTOXX Futures
    • VST1MSL (EVIX’s dollar denominated index)
    • VST1MISL (EXIV’s dollar denominated index)
    • Intraday Indicative value (IV) quotes for EXIV and EVIX are available from some brokers and Yahoo Finance. The symbols within Yahoo are ^EXIV-IV and ^EVIX-IV

 

  • Hours
    • Typically the European continent is 6 hours ahead of USA Eastern time. Standard closing time on the European continent exchanges is 5:30 PM, so they are closing at 11:30 Eastern time. The IV values for EXIV and EVIX don’t update after 11:30 ET because the OESX options used to compute VSTOXX are not trading past then. The Yahoo finance chart below illustrates EXIV’s IV value flat-lining during the afternoon.
    • The VSTOXX futures referenced by these funds trade from 7:30 to 22:30 CET.

 

  • Termination risk
    • Along with XIV and ProShares’ SVXY, EXIV will terminate if there is a large enough volatility spike. The funds are guaranteed to not go below zero and the issuers will not commit extra capital to meet margin calls in that sort of extreme situation.  In EXIV’s case, the fund will be automatically terminated if the drop in the intraday IV value is 75% or more from the previous day’s close.  For the USA markets, historical data suggests it would take a VIX intraday spike of at least 166% to result in a 75% drawdown in the inverse volatility funds and I suspect that the VSTOXX/ VSTOXX futures sensitivities are similar. In the case of termination, shareholders would receive the net value of the fund after the transactions settle from that event.  The value is not guaranteed to be 25% of the previous day’s value, it is only guaranteed to be zero or higher.


Comparing Markets—and Indexes

The chart below compares the historical values of the S&P 500 and the STOXX as well as the VIX and VSTOXX since January 1998.

  • A few things stand out when looking at the STOXX (red line)
    • The STOXX fully participated in the 2000 dot com crash and the 2008/2009 bear markets
    • The STOXX is still well below its 2000 highs—the lack of recovery in the STOXX after the 2008/2009 financial crash is striking
  • Looking at VSTOXX (purple) vs the VIX (black) above:
    • The VSTOXX shows mean reverting behavior similar to the VIX. Sharp spikes up are followed by fairly rapid decays towards the mean values.
    • Periods of low volatility can persist for a long time but eventually, the VSTOXX reverts back to values closer to the mean
    • Generally, the VIX and the VSTOXX are closely correlated
    • The VSTOXX value is almost always higher than the VIX’s value
  • Some statistics for the S&P 500 and the STOXX, January 1999 through July 2017:
S&P 500 STOXX
Compound Annual Growth (dividends not included) 3.75% -0.25%
Annualized Volatility (365 day year) 23.4% 28.1% (20% higher than S&P 500)
Worst Case Drawdown -56% (2009)

 

-65% (2003)
Correlation of % moves 0.54 (moderately high) between S&P 500 and STOXX

 

  • Statistics for the VIX and the VSTOXX, January 1999 through July 2017
VIX VSTOXX VSTOXX compared to VIX
Average 20.36 24.85 22% higher
Median 18.52 22.89 23% higher
Low 9.75 11.16 14.5% higher
High 80.86 87.51 8% higher
Annualized Volatility

(365 Day Year)

111.4 126.2 13% higher
Value Correlation .905 (high) between VIX and VSTOXX values
Correlation of % moves 0.544 (moderately high) between VIX and VSTOXX % moves
Biggest one day drop -29.5%  (10-May-10) Flash Crash aftermath -35.2%  (24-Apr-17) Le Pen defeat
Biggest one day spike +65.2% (27-Feb-07) China scare +38.8% (24-Aug-15)  China scare II
Mode (most common value)  [0.1 pt bins] 13.3 23.1

 

  • Since the STOXX’s historic volatility is about 20% higher than the S&P 500’s it’s not surprising that the VSTOXX’s average and median are around 20% higher than the VIX’s.

The chart below shows a histogram of values for the VSTOXX and the VIX

  • A few observations:
    • The VSTOX distribution is shifted notably higher in value than the VIX
    • While the two index distributions have truncated left “shoulders” and big fat tails on the right the VSTOXX has a significantly more balanced distribution around its mean compared to the bottom heavy VIX.
    • The difference between the mode (the most common value rounded to 0.1 pts) and the record low is only 36% with the VIX compared to 107% for the VSTOXX

 

Historic Performance

  • By using a simulation starting in June 2009 of the indexes that EXIV and EVIX are based on we can get a feel for their performance relative to XIV and VXX. The only difference between the indexes and the EVIX/EXIV ETNs is that the investor fees and treasury bill interest are not included in the index values. The chart below shows relative performance when starting with portfolios of $10K fully invested in each of the funds.

 

  • The two lines starting high on the left (green and purple lines) are long volatility funds that reference the left axis scale. The long volatility funds exhibit the typical long volatility fund race to zero, with VXX slightly better at losing value.
  • The two inverse volatility funds (red and blue lines) referencing the right scale perform much better than the long funds. Overall XIV’s performance dominates with an approximate 40X growth since 2009.

Using a log scale on the vertical axis provides a much more accurate visual way to judge relative performance. The first chart shows VXX index vs the EVIX index

  • The two portfolios begin diverging in early 2010 and don’t return to a similar loss rate until 2016.
  • Over the 2010 to 2015 period EVIX’s decay rate was significantly lower than VXX’s. It’s likely that the VSTOXX futures had considerably lower contango levels during that period compared to the VIX’s futures
  • Looking at the inverse volatility story with a log scale tells a similar tale except that the portfolios diverge almost immediately after the simulation is started.

Similar to the long side of the things, since around January 2016, the performance of the two inverse funds has been pretty close. Starting the portfolio simulation for both the long and inverse funds in January 2016 suggests that the USA and European based funds would have tracked relatively closely since then.  The chart below shows the result of the simulation.

When to Use These New Funds

  • An obvious application for these new funds is placing a bet on an upcoming European event with potentially major impact (e.g., a Brexit vote, or the Le Pen / Macron election). In “known/unknown” cases like this the date of the event is well-known, but the result is uncertain and potentially economically impactful.  It’s certain that the VSTOXX will go up before an event like this, the interesting, and potentially lucrative question is what will happen to volatility after the event—panic/distress or a collapse back to the status quo.
  • Diversification is another application. Obviously, the European markets are not in lockstep with the USA markets and this distance will tend to smooth out some of the volatility shocks.  For example, XIV dropped 17.8% on May 17th, 2017 from its previous close, but EXIV only dropped 9.2%.  A portfolio holding both XIV and EXIV would have some cushioning against these sorts of glitches.
  • Having EVIX and EXIV gives traders a way to profit if they see an upcoming convergence or divergence between the volatility indexes in the two markets. For example, if you believe a recent volatility jump in USA markets will propagate to the Europe you could do a straight EVIX purchase or a pairs trade between EVIX and a long volatility fund like VXX.
  • It might be possible to do some form of contango arbitrage with these funds. It’s certain that the contango losses/gain won’t be identical between the two sets of futures markets, a pairs trade might allow a trader to profit from the difference in contango rates with an overall reduced risk exposure.

Oddities

  • There are differences in the trading hours of these two markets. On the USA side of things, the Intraday Indicative (IV) quotes will be frozen on EVIX and EXIV past the normal close of the European markets, depriving us of an important piece of trading information that’s useful for trading low volume ETPs like these. On the European side, we have times when the volatility securities are trading while the USA markets are closed. For example, you might want to close out EXIV positions if the STOXX was crashing, but if the USA markets are closed there would be no direct way to do that.
  • Since VSTOXX futures are denominated in Euros and EVIX/EXIV are dollar-denominated, exchange rate changes will have effects, although compared to the normal hysteria of volatility markets I doubt it will be significant. Since EXIV is effectively short VSTOXX futures the impact of currency rate changes will be in the opposite direction of EVIX which holds long positions.
  • The EVIX/EXIV calculations assume that cash not needed for margin on the futures will be “invested” in short term German treasury bills—which have been running at negative interest rates (currently -0.734%). Negative rates will result in a minor drag on these fund’s values.
  • Options are available on EVIX, but not on EXIV. You might guess that the CBOE shies away from options on inverse volatility funds because of their termination risk, but options are offered on ProShares’ SVXY so this argument doesn’t hold up.  My understanding is that the SEC has a blanket prohibition on options for leveraged (-1X or 2X on up) Exchange Traded Notes (ETNs).  This seems a bit arbitrary, the big banks that issue the ETNs typically have investment grade credit ratings, but ETFs do have the advantage of transparency into what assets the issuer is actually holding.

Conclusion

It’s head spinning to introduce a whole new set of securities and indexes into the already confusing area of volatility investing but as I reviewed the different ways to use EVIX and EXIV it appears well worth the trouble to learn a few new things. These funds open up new volatility based opportunities in geographic based investing, diversification, and arbitrage style trades.

How Does VMIN Work?

 
Wednesday, July 5th, 2017 | Vance Harwood
 

In May of 2016, REX Exchange Traded Funds introduced two volatility oriented products, VMIN and VMAX.  One is a bet on market volatility staying the same or dropping (VMIN) and VMAX is essentially its mirror image—betting on short term volatility increases. VMIN has some important structural and performance related differences that distinguish it from the other short term inverse volatility funds—VelocityShares’ XIV and ProShares’ SVXY.

In this post I focus on VMIN’s differences from its competitors. If you are new to inverse volatility investing I suggest you review the fundamentals by reading How Does XIV Work? and How does SVXY Work?

For a good understanding of  VMIN (full name: REX VolMAXX™ Short VIX Weekly Futures Strategy ETF) you need to know how it differs from other inverse volatility funds, what it tracks, its risks to the investor, and how well it has performed.

How Is VMIN Different From a Performance / Tax Standpoint?

  • Far from being a “me-too” product, VMIN differs from its SVXY and XIV competitors in a number of important ways. One key difference is that VMIN is designed to track the daily moves of the CBOE’s VIX® better than existing securities. VMIN is an inverse fund, so it generally moves in the opposite direction of the VIX.
  • In addition to this improved tracking, VMIN also outperforms its competitors in taking advantage of the structural drag of VIX futures when their term structure is in contango. Contango exists when longer-dated VIX futures are priced higher than VIX futures that have less time until expiration. The VIX futures that underlie the volatility Exchange Traded Products (ETPs) are in contango around 75% of the time. In the May 2016 to March 2017 time period, VMIN outperformed its completion by 28% due to this characteristic, more than tripling during that period. In fact, VMIN was the best performing fund in the ETP universe in the first quarter of 2017, outperforming all other 23,788 funds, with a 35% gain.
  • While VMIN is an Exchange Traded Fund (ETF) like SVXY, its tax reporting is the same as an ordinary equity investment with your short and long-term capital gains reported via 1099 forms. Because SVXY holds VIX futures directly tax laws require that it be treated as a partnership, reporting gains/losses via Schedule K-1 forms. While not a huge deal; K-1 forms are complicated and always seem to arrive very late in the spring.
  • VMIN will make distributions of any realized securities gains at least once a year. In a good year this special dividend will likely be substantial (for FY 2016 it was $9.92/share). Neither XIV nor SVXY distributes capital gains this way—they have different legal structures (Exchange Traded Note and an ETF structured under the Securities act of 1933 respectively). Special dividends from VMIN or VMAX will be taxed as ordinary income.

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Guest Post: Breath Divergence—Signaling the End of a Bull Market? By Frank Roellinger

 
Wednesday, April 12th, 2017 | Vance Harwood
 

Much has been written since the election about the stock market’s future.  I have long been convinced that certain hard, cold measures of the market are of far more value in estimating the market’s future than qualitative speculation based on political or economic developments.  The most important consideration for a long-term investor arguably is the likelihood of a severe bear market in the near future.  My approach, which I describe in The Modified Davis Method  has revealed some facts that I think have definite value in that regard.

The most important harbinger of danger in the market that I have found is the behavior of the NYSE daily cumulative advance-decline line relative to the S&P 500.  In the early stages of a bull market, both advance dramatically.  Corrections occur along the way, and for a time the recoveries are strong enough to propel both to successive new highs. However, eventually the smaller stocks begin to falter, and the S&P makes a new high while the cumulative a-d line does not.  This phenomenon, which I call “breadth divergence”, has occurred prior to the end of virtually every bull market since 1929, and there is no reason to think that it will be any different this time.

My method doesn’t rely just on breath divergence.  It takes other factors going red before I trigger a short trade.

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