The holy grail of investing is a market timing method that gets you out of the market on bad days and gets you in for the good days. There are innumerable methods for doing this, ranging from slogans, “Sell in May and Go Away” to closely guarded multi-factor proprietary algorithms.
The worst methods have no apparent causal relationship between the predictor and the thing being predicted. A non-stock market example is the “Redskins Rule.” Between 1940 and 2008 if the Redskins won the Sunday before the election the party that won the popular vote in the prior election won the presidency—17 out of 18 times. After Obama’s re-election this rule is now 17 of 19. These non-causal rules are just coincidence, if you look at enough data you will find them everywhere—and they mean nothing.
Most stock market timing methods are based on price action—things like moving averages, technical chart indicators, price/earnings ratios, or pattern recognition. At least they have some sort of connection to the stock market.
Recently I’ve been looking at volatility metrics for predicting market action. The CBOE’s VIX index gets a lot of attention, but using absolute values of the VIX to trigger investments is almost certainly useless. On the other hand, volatility prices over different time frames, often called the term structure, does show significant predictive value.
In a truly bearish market the short term expected volatility, typically cheaper than longer term volatility, climbs higher than the longer term value. This behavior is shared between flavors of VIX (e.g., the one month VIX & its three month version VXV), VIX futures, and the implied volatility of same strike options of different months. The chart below from VIX Central shows the progression in VIX futures prices from before the May 6, 2012 Flash Crash through the 7th.
A simple metric that captures this behavior divides the short term volatility number by a longer term number. If the ratio is below one the market is relatively calm, if above one the market is especially nervous. I’ve been using the CBOE’s VIX & VXV indexes as a convenient way to implement this volatility metric.
I’ve been running simulations using the VIX/VXV ratio as the entry / exit trigger point for market positions. The chart below shows the price performance of the speculative bond fund JNK, since its inception in 2008 compared with SPY, which tracks the S&P 500.
JNK’s performance would be disappointing if it wasn’t for its high dividend payouts, averaging 10% (!) per year. This next chart shows JNK’s performance if you had closed your JNK position whenever the VIX/VXV ratio at market close was greater than 0.917, re-entering when the ratio at close was below that level.
Why 0.917? There’s nothing magical about it. It was just the best compromise choice over the last three years. The chart below shows the performance for JNK for all realized VIX/VXV levels for 2010, 2011, and 2012.
Eventually, perhaps tomorrow, this heuristic will stop working, but for the time being it’s a good tell for the market.
- Protecting Junk Bond Principal With a Volatility Hedge
- Monthly ETF Dividend Amounts
- Dividend History
- 2017 Dividend, Ex-Dividend, and Paydate / Distribution information for ETFs
- 2017 Ex-Dividend: JNK, SJNK, BIL, ITE, TLO, IPE, LAG, TFI, CXA, INY, SHM, BMX,WIP, MBG, ITR, MWZ, LWC, CWB, VRD, and Others
Monday, February 27th, 2017 | Vance Harwood