Shorting Daylight

The longest day of the year has arrived but most of Europe has already been sizzling for the past few weeks. Down here in Spain we regularly have been touching the 35 Celsius scale which is about 95 Fahrenheit for all you metricphobic North Americans. Although I love to bitch about the cold during the winter what really irks me the most is the insufferable summer heat here in Valencia which unfortunately comes with a ton of humidity  – we’re talking 80% plus at times. Which is quite different from the dry desert like heat I had gotten accustomed to living in California for about 20 years.

From here on out every day will be about two and a quarter minutes shorter than the previous one – on average. As you can see the gradual change roughly works out to be a sinus curve in most of the U.S. and European territory. Scott meanwhile down under is enjoying the beginning of winter which in his parts is actually quite tolerable. It’ll be about 75 Fahrenheit (i.e. 24 C) in Brisbane later today and that’s the type of winter I could get used to 

Cycles Are A Natural Phenomenon

Now it’s not the slow summer participation that’s leading me to talking about the weather. Whenever I ponder about the seasons and thus planetary and astronomic cycles I am reminded why human beings have a tendency to expect cyclic behavior in all things including of course the markets. And to some extend they are right in that every financial market seems to have its own inner clock and thus oscillates between selling and buying cycles. The problem is that unlike planetary movements those cycles are a lot more opaque and thus very hard to predict. But that of course hasn’t stopped us from trying.

Predicting Volatility

Realized volatility (RV) is easier to predict than signed returns, as every finance student has also been taught. But how does predicting volatility help us? Would it be useful for example for options traders, who then go and trade implied volatility (IV) instead of directional returns? Ernie Chan was curious about just that and decided to look into that. The answer is yes: predicting RV is useful for IV prediction, but not in the way you would expect.

If our GARCH model tells us that the RV will increase tomorrow, most of us would instinctively go out and buy ourselves some options in order to benefit from a jump in IV. In the case of SPY, we would probably go buy some VXX. But that would be a terrible mistake. Remember that the volatility we predicted is an unsigned return: a prediction of increased volatility may mean a very bullish day tomorrow. A high positive return in SPY is usually accompanied by a steep drop in VXX. In other words, an increase in realized volatility is usually accompanied by a decrease in implied volatility in this case. But what is really strange is that this anti-correlation between change in realized volatility and change in implied volatility also holds when the return is negative (57% of the days with negative returns). A very negative return in SPY is indeed usually accompanied by an increase in implied volatility or VXX, inducing positive correlation. But on average, an increase in realized volatility due to negative returns is still accompanied by a decrease in implied volatility. The upshot of all these is that if you predict the volatility of SPY will increase tomorrow, you should short VXX instead.

I actually looked at several algos replicating some of Ernie’s work on GARCH over on Quantopian. They all seem to work fairly well but IMO suffer from massive standard deviation, which clearly affects the Sharpe ratio. A 37% max drawdown is simply not an option in my book.

Here’s a run of a VIX/VXV rebalancing algo I’ve been looking into, it’s not using GARCH but relies on mean reversion. Sharpe ratio is minimal and the max drawdown is still way too deep at -19.4%. Generally there seems money to be made and it’s definitely an area to which I will devote a lot more time and energy. However at this time it’s still in the experimental stage.

By the way, if you want to learn more about predicting volatility then go and watch Ernie’s QuantCon talk right now – well, after reading the rest of my post of course. In summary I think I should have become a meteorologist and learned how to predict the weather, seems much easier than predicting either price or volatility. Unfortunately it doesn’t pay as well, so let’s get to the goods:

Talking about cycles. The E-Mini seems to oscillate between buy and cell cycles recently and apparently yesterday it was the bear’s turn. I could get interested in a long position if it drops to about ES 2430 during today’s session and IF the Zero is looking positive.

In order to increase my odds I’d probably split my exposure between the ES and the YM shown above, mainly because the latter has been the most bullish as of late.

Quick update on soybeans which suddenly turned on a dime yesterday. Although the campaign survived that first dip down it looks like as if we may be looking at another leg to the downside. Which of course was the risk to begin with and why I only took out a very small position.

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