Weekly Volatility Tracker: Implied Correlation as a Reflation Proxy

The CBOE Implied Correlation Index spiked to its highest level last week since the beginning of the rally that began this spring. [10] In a healthy, normally functioning market, companies that succeed will see their stock prices rise, while the stocks of failing companies will fall. In a healthy, normally functioning market, the stocks of winners and losers alike won’t rise or fall together in lock step; but the increase in [10] denotes increased expectations of just such a phenomenon. There’s an old adage that, in a crisis, all correlations go to 1. As the implied correlations of S&P 500 stocks push toward crisis levels, momentum- and sentiment-based long positions should be watched carefully. It is intuitive that, as we watch “junk” and quality stocks both rise week after week, expectations of high correlation are just a proxy for the efficacy of reflation efforts. But indiscriminate reflation is no more a sign of a healthy economy than are falling stock prices.

Following up on last week’s discussion of price distributions and kurtosis, I ran a simple strategy test beginning in 2000 that buys the S&P 500 when its one year kurtosis is above a 200-day simple moving average, and moves to cash otherwise. Returns weren’t outstanding, but still beat the market handily, and (more importantly) the strategy was in cash about half the time. Accounting for returns on cash would obviously improve results. I don’t have any broad lesson to extract from this, except perhaps that no expensive analytics software package can remove the need for a basic knowledge of statistics.

I still like a long orientation on oil volatility; another round of straddles may be in order. [16,17]

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1. Comment. Highlights items of note in the data below along with our short-term volatility bias and any trading theses. The Expected Daily Move table displays the de-annualized price and percentage change in each underlying asset as implied by its volatility index, within one standard deviation. The Forward Bias table displays my bias for the movement of the price and implied volatility of several assets for the coming week.

2. Weekly Change. Tracks the weekly percentage change in the assets listed and in their implied volatility indexes.

3. Implied Volatility Indexes. A one year chart of the implied volatility indexes for the S&P 500, gold, oil, and USD/EUR. Indexes for the Nasdaq 100 and Russell 2000 are omitted because of their tight correlation with VIX.

4. S&P 500 Price and Bollinger Bands. Tracks daily closing prices in SPX with an overlay of one and two standard deviation 50-day bands.

5. S&P 500 Implied and Realized Volatility. Tracks the 21-, 60-, and 90-day realized (or “historical”) volatility of the index and the21-day lagged CBOE Implied Volatility Index (”VIX”). Realized volatility is displayed as the annualized standard deviation of lognormal returns over the period specified, and may be thought of as a backward-looking measurement of price behavior. Implied volatility is the annualized standard deviation of returns implied by option prices, and may be thought of as a forward-looking measurement of expected price behavior.

6. S&P 500 Implied/Realized Volatility Ratio. Tracks the ratio of 21-day lagged implied volatility (IV) to 21-day realized volatility (RV). This ratio asks how well IV from one month ago predicted the RV over the next 21 trading days (roughly, 30 calendar days). When IV correctly anticipates RV over the period, the ratio will hover near 1; we regard the area near 0.9 –1.2 as normal, given the persistence of a volatility risk premium in equity market derivatives. A ratio less (greater) than 1 indicates that the price behavior of the underlying asset was more (less) volatile than anticipated.

7. Volatility Futures Term Structure. Tracks the Friday closing prices of the Volatility Futures complex (VIX, VXD, RVX) for the two weeks prior, along with the spot levels for reference.

8. VIX Premium Ratio. Tracks the ratio of rolling three-month (VXV) to one-month (VIX) implied volatility. Periods in which one-month readings persist at an extreme premium or discount to three-month levels have tended to coincide with major market moves.

9. S&P 500 Daily Return Distribution (3 month). Histogram plotting the frequency of daily percentage returns over the prior 63 trading days.

10. Implied Correlation Index. Reflects the market-capitalization weighted average correlation of the 50 largest components of the S&P 500.

11. Gold Price and Bollinger Bands. Tracks daily closing prices in GLD with an overlay of one and two standard deviation 50-day bands.

12. Gold Implied and Realized Volatility. Tracks the 21-, 60-, and 90-day realized (or “historical”) volatility of the ETF and the 21-day lagged CBOE Gold Volatility Index (”GVZ”).

13. Gold Implied/Realized Volatility Ratio. See #6 above; given the novelty of the VIX-style gold volatility index (GVZ) and the characteristics of the underlying, we do not yet have a range we regard as normal.

14. Gold Daily Return Distribution (3 month). See #9 above.
15-18. Oil charts correspond to 11-14 above.

Comments

[Baboon:]

How to calculate the realized volatility of SPX? Is there a symbol for it?

Sep 01 08:07 AM

[Condor Options:]

For annualized realized volatility: calculate the standard deviation of log returns over the period required, multiplied by the square root of 252. This can be done easily in a spreadsheet.

Sep 01 02:34 PM