We share the Weekly Gamma Bands Update by Viking Analytics. The report uses options gamma to help you better manage risk and your equity allocations.
Gamma Band Update
The S&P 500 (SPX) moved above the Gamma Flip level on Monday of last week, spent the rest of the week trading in a fairly narrow range, and closed the week just above 4,200. We agree with many others that options and VIX order flow have become one of the primary “fundamentals” of the market, and as long as the SPX remains above its Gamma Flip levels, we will expect declining volatility and a continuing grind higher.
Our daily Gamma Band model[1] moved to a 100% allocation to SPX on Monday and remained at that level throughout the week. When the daily price closes below “Gamma Flip” (currently near 4,180), the model will reduce exposure in order to avoid price volatility and sell-off risk. If the market closes on a daily basis below the lower gamma level (currently near 3,950), the model will reduce the SPX allocation to zero.
Investors who keep an eye on various gamma-related levels are more aware of when market volatility is expected to increase. One application of Gamma Bands is to maintain high allocations to stocks when risk is expected to be lower. For investors who have been conditioned to “buy low and sell high,” it is counter-intuitive to increase allocations when the market rises, but this approach has shown to increase risk-adjusted returns in the back-test.
The Gamma Band model is one of several indicators that we publish daily in our SPX Report. With stocks continuing to extend historically high valuations, risk management tools are more important than ever to manage the next drawdown, whenever it comes.
A sample of the SPX report can be downloaded from this link. Please visit our website to learn more about our daily reports and quantitative algorithms.
The Gamma Flip – Background
Many market analysts note that daily volatility in the S&P 500 will change when the value of the SPX moves from one gamma regime to another. Some analysts call this level the “gamma flip.” The scatterplot below shows how price volatility (on the y-axis) is increasingly lower as the value of SPX rises higher above the Gamma Neutral level (on the right side of the chart). When the value of the S&P closes lower than Gamma Neutral (to the left of the chart), volatility increases.
Gamma Band Model – Background
The purpose of the Gamma Band model is to show how tail risk can be reduced by following a few simple rules. The daily Gamma Band model has improved risk-adjusted returns by over 60% since 2007. The graph below demonstrates how this approach can limit drawdowns while maintaining good returns. A quick video introduction of the Gamma Band model can be seen by following this link.
Disclaimer
This is for informational purposes only and is not trading advice. The information contained in this article is subject to our full disclaimer on our website.
[1] The Gamma Band model in our SPX Market Report adjusts position size DAILY based upon the daily closing levels of SPX value and calculated Gamma Neutral. The Weekly Gamma Band model is shown for illustrative purposes only.
Authors
Erik Lytikainen, the founder of Viking Analytics. He has over twenty-five years of experience as a financial analyst, entrepreneur, business developer, and commodity trader. Erik holds an MBA from the University of Maryland and a B.S. in Mechanical Engineering from Virginia Tech.
Rob McBride has 15+ years of experience in the systematic investment space. He is a former Managing Director at a multi-billion dollar hedge fund. Furthermore, he has deep experience with market data, software, and model building in financial markets. Rob has a M.S. in Computer Science from the South Dakota School of Mines and Technology.
Erik Lytikainen, the founder of Viking Analytics, has over twenty five years of experience as a financial analyst, entrepreneur business developer and commodity trader. Erik holds an MBA from the University of Maryland and a BS in Mechanical Engineering from Virginia Tech. You can learn more about his work on his website: www.viking-analytics.com.