Daily Commentary - Posted on Saturday, November 15, 2014, 7:35 PM GMT +1
DDN’s Volatility Risk Premium Strategy Revisited (3)
A couple of weeks ago I started a series of postings, all dealing with trading volatility ETNs / ETFs like XIV® (VelocityShares Daily Inverse VIX Short-Term ETN) and VXX (iPath® S&P 500 VIX Short-Term Futures™ ETN) and respective trading strategies. One of those strategies was DDN’s VRP Strategy (Double-Digit Numerics , Volatility Risk Premium) due to its exceptional performance – at least until December 2012 – and its compelling approach (from the paper Easy Volatility Investing from Double-Digit Numerics).
In my last posting DDN’s Volatility Risk Premium Strategy Revisited (2) I introduced the CBOE Mid-Term Volatility Index (Ticker: VXMT®) as a proxy for implied volatility (expected volatility of the S&P 500 Index over a 6-month time horizon), which shows much better results than using the CBOE Volatility Index (Ticker: VIX®). But there is a catch: the VXMT® ‘s outperformance ended in June 2013 (more on that below).
But first of all the original Volatility Risk Premium (VRP) Strategy rules (always market on close):
- Long XIV: 5-day average of [VIX® or VXMT® – (2-day historical volatility of S&P 500 * 100)] > 0
(Please note: Before 2008, VIX® instead of VXMT® is used)
- Long VXX: 5-day average of [VIX® or VXMT® – (2-day historical volatility of S&P 500 * 100)] < 0
- Hold until a change in position.
Image I shows the respective equity curves, DDN’s VRP (original strategy) (red line, using a 10-day historical volatility), the VIX® index version (blue line) and the VXMT® index version (black line). The yellow area shows the VXMT® ‘s index version percentage-wise outperformance compared to the VIX® index version.
Please note: The CBOE provides VXMT® historical data back to 1/8/2008. Before 2008, VIX® has been used instead (therefore both strategies do not differ before 1/7/2008). The VXMT® index version outperformed it’s counterpart by a wide margin (topping out in June 2013), but has given back half of its percentage-wise outperformance since then. The question is: What is the reason behing the VXMT® ‘s index version decline in performance relative (not in absolute terms) to the VIX® index version ?
Image I – Total Equity and Drawdown Curve(s)
(03/25/2004 – present)
(slippage, fees and transaction costs are assumed to total 0.1% per trade)
The reason for the breakdown in performance ( DDN’s VRP Strategy ) and the out-/underperformance of the VXMT® ‘s index version relative to the VIX® index version imay be many-faceted, e.g. changes in the relationship between VIX® and VXMT® (ratio and/or premium, backwardation and contango, …), the relationship between implied and realized volatility, premium of VIX front and second month futures (as a basis for VXX® and XIV® ), among others.
Image II may present some insights and a first indication and shows:
- relationship/delta of VIX® and VXMT® strategy triggers (for going long or short volatility):
5-day moving average of [VIX® – 2-day historical volatility of S&P 500 * 100] –
5-day moving average of [VXMT® – 2-day historical volatility of S&P 500 * 100]
- Volatility Risk Premium (potential gain):
1-month moving average of [VX1|VX2 (30-day const. maturity) – 2-day historical volatility of S&P 500 * 100]
- the S&P 500®Index
Image II – Volatility Risk Premium and VIX® vs. VXMT®
(01/07/2008 – present)
Right at the start of the bull market in 2009 (at the end of the financial crisis), VIX® front and second month futures (Ticker: VX1|VX2) (merged into a continual time series as a 30-day constant-maturity futures prices, as they are the basis for VXX® and XIV®) were trading at a huge premium to the then current realized (2-day historical) volatility, but as investor complacency grew into the ongoing bull market, the delta between realized and implied volatility faded and is now merely at half the levels of 2009.
The same reason, but a different effect: While at first (2009) the VIX® index came down from historical high levels back to historically normal levels (from backwardation into contango), 6-month looking forward implied volatility (VXMT®) remained relatively flat, reverting a positive spread between VIX® and VXMT® into a widening negative one. But that trend was reversed in 2012. As investor complacency grew, 6-month looking forward implied volatility (VXMT®) was (and still is) on the wane. (Looking forward) Volatility slumps as complacency regains the upper hand.
Between 2009 and the end of 2012, every up-move in the markets was accompanied by a widening spread (regularly up to -7 – -8 percentage points) between VIX® and VXMT® (investor scepticism remaind relatively high), but since January 2013 the (averaged) spread between VIX® and VXMT® has remained well below -5 (percentage points). For examplary purposes: With VIX® at or around 13, it is like VIX futures with a 6 month maturity would’ve been trading at or around 21 in 2009, while they’re trading below 18 today. Means investor fear looking 6 month ahead is currently at significantly lower levels than it had been in 2009.
Image III now shows the relationship between implied (VXMT® index as expected volatility of the S&P 500 Index over a 6-month time horizon) and historical (annualized, 2-day realized) volatility. Since 2013, the gap has remained flat (constant) at historically low levels at or around -15%.
Image III – VXMT® and Historical Volatility
(01/07/2008 – present)
Due to the fact that the gap between implied volatility and historical (realized) volatility remained constant/flat over the course of the last year and a half, the Volatility Risk Premium Strategy utilizing the VXMT® index was at a disadvantage compared to it’s VIX® counterpart : With volatility of volatility dwindling away, the “5-day average of [VXMT® – (2-day historical volatility of S&P 500 * 100)] > 0” remained almost constant/flat in positive territory and closed below ‘0’ (trigger value for going long volatility) less often than before June 2013 (to be exact: now in 1 out of 30 sessions only instead of 1 out of 10 sessions before), means it mimics more or less a Buy&Hold XIV® strategy instead of taking benefit of both sides of the trade (assumed going long volatility after 6/30/2013 had been as profitable as it had been before 6/30/2013). By contrast the VIX® based strategy remained (almost) unaffected (because the VIX® is trading a couple of index points below the VXMT® index), still going long volatility in approximately 1 out of 10 sessions.
Image IV shows the distribution of the results of the formula “5-day average of [VXMT® – (2-day historical volatility of S&P 500 * 100)] > 0” , overall, before and after 6/30/2013.
Image IV -Distribution of Trigger Values
(01/07/2008 – present)
Possible solutions to fix that problem:
- using a different cutoff (other than ‘0’),
- using a different x-day historical volatility and/or y-day moving average,
- making the system adaptive (incorporating a learning curve, from my perspective the most interesting approach),
to be continued … (means more on this to come, stay tuned)
Have a profitable week,
Disclosure: I’am long/short XIV, and long/short VIX, RVX and EURO STOXX 50 volatility futures.
Remarks: Due to their conceptual scope – and if not explicitly stated otherwise – , all models/setups/strategies do not account for slippage, fees and transaction costs, do not account for return on cash and/or interest on margin, do not use position sizing (e.g. Kelly, optimal f) – they’re always ‘all in‘ – , do not use leverage (e.g. leveraged ETFs), do not utilize any kind of abnormal market filter (e.g. during market phases with extremely elevated volatility), do not use intraday buy/sell stops (end-of-day prices only), and models/setups/strategies are not ‘adaptive‘ (do not adjust to the ongoing changes in market conditions like bull and bear markets). Index data (e.g. S&P 500 cash index) does not account for dividend and cash payments.
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