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We provide investment advice for the VIX futures market and related exchange traded products (ETPs). The VIX futures market is a growing derivative market with over $4 billion in average daily trading volume in 2016. Volatility ETPs are composed of VIX futures which are based on the CBOE S&P 500 Volatility Index (VIX) or otherwise widely known as the "fear index". On this website, you can will be provided with the tools and knowledge to trade popular volatility ETPs like SVXY and VXX for profit. Long volatility strategies are used for protection against market turmoil while short volatility strategies are used as "yield enhancers".
A short volatility strategy is similar to being leveraged long the stock market while a long volatility strategy is similar to being leveraged short the stock market. The VIX has a built in leverage: historically, the VIX moves +4% for every -1% move in the SPX. Thus a short volatility strategy enables to you to achieve higher than market returns. In addition to the leverage, one of the most attractive features of a short volatility strategy is its ability to generate returns when the market is rangebound, thus making it an excellent "catchup" trade. However, periods of market beating performance come with a substantial cost. When adverse market conditions strike, losses in short volatility strategy can be catastrophic while gains in a long volatility strategy add up to big numbers. Moves of +/-40% in a month can happen once or even a few times a year. Buy and hold is not an option for any volatility strategy or any VIX ETF. Any exposure to this asset class must be actively managed and this is where we can help you.
Our subscribers get daily updates and weekly newsletters with analysis of the VIX Futures Curve, the VIX and various other volatility indices as well as the S&P 500 index. You will be better informed than ever about what moves the market and what comes next. You will have access to live and historical volatility data, real-time dashboards, daily reports and many customized volatility analytics that help you succeed as a trader. We track over 20 signals in the following categories:
Our proprietary "ace-in-the-hole" indicator - the VIX Contango Oscillator (VCO) - aggregates volatility expectations across different options and futures markets and helps you identify opportunities to exploit VIX futures convergence for profit. It also does a great job of spotting market turns. We run proprietary systematic algos and discretionary signaling strategies that provide well-timed entry and exit points into the most popular volatility ETPs like SVXY and VXX.
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Algorithmic Short VIX strategy
Take advantage of SVXY whenever it goes on a multi-week positive run. This swing trade strategy maximizes returns and aims to stay in SVXY as long as possible.
Learn more »
Take advantage of SVXY whenever it goes on a multi-week positive run. This swing trade strategy minimizes drawdowns and cuts exposure as soon as trouble in SVXY surfaces.
Algorithmic Long VIX strategy
Take advantage of VIXY whenever it goes on a multi-week positive run. This strategy is invested only when the VIX Futures Curve is heavily inverted which happens rarely.
Discretionary savings strategy
Risk-averse low-volatility ETF savings strategy that applies volatility inspired market timing principles to the Permanent Portfolio. Main investments are SPY (stocks), SVXY (short vol), GLD (gold), TLT (bonds), HYG (junk bonds) and NEAR (high yielding cash) depending on market and economic conditions.
Discretionary growth strategy
High risk growth strategy. Take advantage of our technology expertise in selecting an eclectic group of recent IPOs operating in secular high-growth areas that are poised to dominate the future of technology and finance. Cloud, distributed software, social networks and online video education.
General Description The strategies are built with the goal of preventing the biggest drawdowns in the underlying Volatility ETFs. In most years, our strategies will outperform their underlying simply by avoiding the drawdowns and participating in the rallies. The strategies generate frequent trades near the tops of the underlying in order to prevent a big drawdown. Getting out in time is very important as the drawdowns in Volatility ETFs can be quite quick and quite large. The strategies will not participate in the initial recoveries of the underlying as we were unable to find a set of parameters that would enable us to do that. Generally speaking, our trading strategies try to capture the middle part of the volatility cycle when there is an established trend. The SmartXIV tends to be invested about 50% of the time and usually after volatility conditions truly stabilize. The SmartVXX strategy is invested only about 5% of the time as over the past few years the long bull market has put the long volatility trade in a funk.
Backtests The systematic trading strategies were developed using an iterative backtesting process that tested over 10 volatility signals against a set of core backtesting algorithms. We utilized Simple Crossover, Dual Threshold First Cross, Dual Threshold Hold, Average True Range and Moving Average backtesting strategies. We ran each volatility factor against all strategies using a variety of thresholds to determine the best performing combination of thresholds and signals. Strategies were evaluated not only for their best return profile, but also for their ability to minimize drawdowns and trading frequency. Once the appropriate signals and thresholds were determined, we utilized a combination of the best signals to further minimize drawdowns and trading frequency without sacrificing performance. The SmartSVXY and SmartVXX have a better MAR ratio (Measurements of Returns Adjusted for Risk) than any individual strategy we tested. While there were a couple of better performing strategies, the SmartShortVIX and SmartLongVIX were selected for their ability to produce the best risk-adjusted returns. We went into the backtest without prejudice with regards to the factors.
The volatility indexes and VIX futures data used by the backtests is readily available on widely-used popular websites such as Yahoo and CBOE. We have not used phantom calculated values for XIV and VXX prior to 2009 to backtest all the way to 2004 when VIX futures started trading. In addition, only daily closing data was used for the Volatility ETFs and daily settlement values were used for VIX futures.
The backtests targeted a basic 401(k) trading account without margin. As a result, buys were delayed 3 days after a sell to ensure that the account can actually perform the buy. We assumed a 0.1% slippage during the trade execution (price above 0.1% of the close price was used to buy and price below 0.1% of closing was used to sell). A trading fee of $7.50 per transaction was assumed. The initial amount for the strategy portfolios was $100,000 and when buying, as close to 100% of the portfolio balance as possible was invested. The cash was assumed to generate 0% return.
Disclaimer Black Peak Ventures does not provide professional financial investment advice specific to your life situation. Black Peak Ventures provides investment analysis of the CBOE VIX futures market and related exchange traded products using algorithmic and discretionary signals derived from proprietary indicators, measurements and analytics. Prior performance of these strategies does not guarantee future returns. We were only able to backtest during the 2009-2015 period as the underlying Volatility ETFs did not exist prior to 2009. In addition, the 2009-2015 period features an unprecended intervention in the capital markets by the Federal Reserve and other central banks via Quantative Easing, Zero Interest Rate Policy and other measures. The backtests reflect the market conditions during that period of time which are unprecedented in history. These conditions resulted in an 6%+ average contango between the front 2 futures thus greatly enhancing the performance of XIV (Short Volatility ETN) and greatly hindering the performance of VXX (Long Volatility ETN). Whether these market conditions will persist in the future is unknown and any change in market conditions in the future may affect the performance of the strategies going forward.