An explanation could be, that selling financial catastrophe insurance demands especially high risk premia, because extraordinarily large losses come at the worst times. Investor demand for catastrophe insurance (in indices) as well as lottery tickets (in individual securities) is high and they systematically overpay for them – just as people play the lottery or buy fire insurance for their homes even if it will cost them money on average.
This passes the base rate test of delivering sufficiently long term positive returns in the strategy´s least sophisticated, undiversified form even after a devastating crisis in 2008. The CBOE has indices for different strategy variations on their website – e.g. CBOE S&P 500 PutWrite Index (PUT) or CBOE VIX Premium Strategy Index (VPD).
- Volatility always returns to its long-term mean (mean reversion effect).
- Volatility tends to spike briefly (usually when the stock market slumps), followed by lengthier downward trends.
- Volatility forms volatility clusters (regimes), the best predictor of future volatility is current volatility.
- Volatility strategies manifest a tendency to rebound very quickly after drawdowns, because of rising premiums in bear markets. That implies, that the returning calm after a severe storm is the most lucrative environment for being short volatility, but also the hardest to stomach.
- Selling out of the money put options on index ETF (insurance) and selling far out of the money call options on individual securities and ETF (lottery tickets). These carry the highest premia as investor demand for these options is highest and they systematically overpay for them. Studies show that it also works well to combine index short puts and short calls into systematic strangles, that make a portfolio largely market neutral. This type of strategy captures the volatility risk premium while avoiding to make a directional bet.
- Trading volatility directly through VIX futures, options, ETN, ETF and their options. Volatility ETP like VXX are some of the most efficiently value-losing securities out there and money can be made taking the other side. The danger lies in the vicious spikes these securities can have to the upside.
I´ll tell you a bit about the process of developing the strategy as it stands today – it is a lot more systematic now, albeit with a lot of elements derived by trial and error and a fair bit of discretionary leeway in instrument selection and execution – which helps to make me feel active and doesn’t do much harm.
- I invariably got put the stocks, that I least wanted to own. These underwater positions began to litter my portfolio and were hard to get rid of because of my aversion to realize a loss (loss aversion bias). My stock portfolio was being thrown together by chance, rather than intelligently designed. My solution was to treat my option strategy as separate from the rest of my portfolio with no intention of ever owning the underlying security. This resulted in a much clearer thought process. I cover the option before expiration or sell the position immediately, if I ever get put (which happens rarely as this is usually not in the best interest of the counterparty – they will effectively lose the remaining option premium).
- I also have a strong contrarian streak and was soon attracted by the high premiums found in beaten down value sectors (e.g. natural resources, southern Europe and emerging markets, etc.). Unfortunately the time horizon did not work. I was not willing to stick with a position I was put long enough for mean reversion to take place and at first many of these „valuable” stocks became ever cheaper.
- Reading more academically influenced material, I found out that the best put option premium can be found in index options, because investor´s demand is highest for protective index puts. It only looks as if individual stock options pay higher premiums at first glance. But, because they are much more volatile than indices, their profit probability is also much lower – resulting in a worse risk-adjusted premium.
- Simultaneously I decided to quit investing in individual stocks, because it is a fight against basic probability – about 65% of stocks underperform their index. In practice it turned out to be quite impossible for me to construct a portfolio of diversified global assets as an individual investor using individual stocks and I now base the global asset allocation part of my portfolio only on ETF.
- Trading universe: all global asset ETF with liquid options including equities, fixed income, real estate, commodities and currencies, plus individual securities that are doing badly as underlyings to sell lottery-type calls on. Finding suitable ETF is still done by manually looking for option availability and tolerable bid-ask spreads.
- Basic entry rules: to sell puts (for short calls use reverse criteria) do a monthly check: if ETF price is above its long term moving average (150 to 300 days, I use a 275 day SMA to be a bit on the longer side from the commonly used 200 day SMA) and 12 month momentum has risen to the top 20% in the last 1-3 months (this screener works well), write puts on all ETF passing the screen, checking for diversification, liquidity and capacity of portfolio allocation.
- Adaptive portfolio allocation: Calculating with the effective exposure to the underlying, I allocate between 50% and 150% of capital (NAV) to short options (this includes direct volatility trading described below), which will lead to a maximum leverage of the entire portfolio of 2,5 times – with hedging in place to neutralize some market direction. I´m scaling down exposure in bear markets and high volatility regimes and cap the amount of option writing at my current maximum allocation. The more positive trend and momentum candidates pass the screens, the higher my overall allocation and vice versa.
- Position size, strikes and time to expiration: Each position is calculated by writing option premium for 0,5% of capital, which automatically results in scaling positions approximately by the underlying´s volatility (the underlying´s volatility determines option prices). Strikes are 2% – 5% OTM for puts and around 5% OTM for calls. Expiration dates are spread equally from 2 to 4 months to diversify across time, new positions are placed in the slots, that are opening by exiting existing positions.
- Diversification and market neutrality: ETF are selected by liquidity and diversification across sectors, countries and asset classes, avoiding concentration in any particular area. When allocation capacity is full, no additional options are written until the next month. The market´s direction is hedged by writing calls on downtrending securities, depending on the current trend (conceptually this results in a strangle spanning different, correlated securities): the more ETF show a positive trend, the more the option portfolio will be positively tilted. When more markets trend downwards short call exposure is scaled up and overall leverage scaled down.
- Exit rules: option positions are exited at a 50%+ profit or via stop loss at -100% or at the break of the long term moving average of the underlying.
- Strategy statistics: I have made a lot of changes, but since late 2015 the win rate was 85% with an average loss at -39% and an average win at 17,5%. Typical for a negative skew strategy is the large amount of small wins with few, larger losses, but because of the benign market environment and absence of major adverse events these statistics are not representative of a full cycle.
- VIX futures contracts began trading in 2004
- VIX options began trading in 2006
- VIX Short-Term Futures ETN VXX was launched in 2009, its inverse counterpart XIV in 2010, the 2x levered version UVXY and the inverse ETF counterpart SVXY in 2011 as well as many other products.
- Options on VXX were introduced 2010, on UVXY and SVXY in 2012
- The Vix Futures Term Structure adds an additional source of return, it provides a considerable roll yield that is positive for a short position about 80% of the time and a part of which can be harvested.
- We can derive different trading signals with important market information contained in the term structure.
- Historical performance shows different return distributions for VIX derivatives and S&P 500 options – it will add diversification.
- The basic risk characteristics are the same however, therefore I trade volatility directly, but put it in the same portfolio allocation bucket as short option strategies.
Edit February 2018: An unprecedented volatility spike (VIX up 115.6% on February 5th) has triggered a discontinuation of XIV after falling more than 90% a day after the Term Structure signaled to exit all direct short volatility positions. This stresses the inherent danger and the importance of diligent risk control through moderate position sizes and strict stop losses.
- Momentum and trend: one can compare the price action of volatility ETP as a direct trading signal, using momentum (over a lookback period shorter than the usual 12 months – e.g. 80 days), but I prefer moving average trend indicators over different time frames in combination with term structure signals. As a basic trend filter – as throughout my portfolio – I use the market´s long term moving average, in this case the S&P 500´s. Vix tends to spike to extremes and cluster at high levels when the S&P 500 already trades below its 200 day moving average.
- Roll Yield: two simple methods can be used here: one can look at the current roll yield and the term structure curve visually at vixcentral.com or calculate the ratio between the Vix and its longer term cousin VXV: VIX/VXV for similar signals.
- The Volatility Risk Premium for Vix futures can be estimated directly with very good results, but this approach doesn’t make the same intuitive sense to me and I need to trust the signal to be able to stick to trading it.
- SVXY (XIV) and VXX medium-term trend following. The majority of strategies I found, trade both or one of these ETP. The aim is to reduce the drawdowns and volatility while participating in most of the upside of short volatility ETF SVXY (or near identical XIV). The main reason I use moving average cross over signals here is, that these generate slightly different entry times from the other sub-strategy signals.
- Entry SVXY on moving average cross 9 day SVXY SMA above 60 day SVXY SMA and contango > 0 and S&P 500 > 275 day SMA; exit SVXY on moving average cross 9 day SVXY SMA below 60 day SVXY SMA or contango < -1,5%; position size 10%-15% NAV.
- Long volatility VXX (to hedge tail risk): entry if contango < -3% and S&P 500 < 275 day SMA; position size 10%-15% NAV.
- Long UVXY put option. The advantage of being long puts is the built in maximum downside protection (in contrast to extremely risky short calls), while participating in the upside with leverage (about 4 times SVXY with the strategy parameters below). As the tendency of UVXY to lose value quickly is well known, the puts unfortunately demand a very steep premium. UVXY has to fall considerably for the put to become profitable, but nonetheless I consider this the best risk-reward strategy when looking at my backtests. Long puts have the highest exposure in the direct volatility trading part of my portfolio.
- Long UVXY put rules: buy UVXY put when Vix term structure returns to contango > 0 after being in backwardation, expiration in about 5 months, strike OTM at last UVXY low; exit after two months (if UVXY should be at a relative high then, exit after three months); position size 5%-10% capital (put premium).
- Weekly UVXY short calls. UVXY calls command very high premiums mirroring their crazily high volatility (about 10%-15% premium for an ATM call 3 weeks to expiration at the moment) and they have the very strong directional UVXY bias working against them – resulting in a high probability trade when we are short. These calls lose more than 50% of their value (our profit) over the course of a week or two most of the time, but can spike up a multiple of that within a day or two every once in awhile. The aim is to create a high weekly income stream and avoid lethal spikes without getting whipsawed too much. A possibility is using call spreads for protection, but I found the trading costs getting very high in practice and decided to use a stop loss rule on a naked call instead. This leaves the strategy exposed to extreme black swan events and overnight gaps, a risk I mitigate through relatively small position sizes.
- Selling UVXY calls weekly rules: the idea is to sell a call each friday to earn the premium, when conditions are favorable. I start the strategy, when the Vix term structure returns to contango > 0 after being in backwardation; sell one third position size call, three weeks to expiration, strike 2%-5% OTM, repeat each friday – the strategy will accumulate three open positions with staggered expiration dates; exit at expiration or at emergency stop loss at -200% or exit and stop trading the strategy when contango < -1,5%; position size for 3 call positions 0,75%-1,5% NAV (call premium).
- At the stop point (contango < -1,5%) a considerable amount of the earned premium will be given back – the rules aim to keep about 50% of the premium on average over time. If results deviate from this goal too much, I will change or discontinue the strategy. I posted a case study and update with several adjustments in the strategy´s rule following a strong double volatility spike in August 2017.
- Overall position size and exposure. In combination these strategies use a maximum of 15% to 25% of capital, but often only a part of the strategies is in the market simultaneously. Because of the inherent leverage in the options (the puts used are about 4 times, the calls about 12 times levered compared to SVXY), this will translate to a maximum exposure of approximately 50% to 100% NAV. I cap my maximum exposure at 75% NAV and only use full short call position sizes, when put and SVXY positions are so far in the green, that I can set a break even stop loss and remove them from the equation or if they are already closed.
The position sizes on the high end are the maximum growth exposure (using the Kelly criterion) – I use a mid-level exposure at the moment. With a growing account size or growing skepticism about the market, I plan to move towards the position sizes at the low end or scale down even further.
- Strategy statistics: I closely observe real time trading data, but so far the strategies have only been active for a couple of months – with very good results. Backtesting the combination of strategies from the inception of UVXY (which excludes the very negative 2007-2009 period) yielded 39% annual return with 32% volatility, a Sharpe ratio of 1,2 and a maximum drawdown of -23% – in line with outside sources, but I expect future drawdowns to double easily given the volatility.