Nanex Research

Nanex ~ 31-Aug-2012 ~ SPY Intraday Volatility

Since 2005, there were 3.9 billion quotes and 579 million trades in SPY (an ETF that tracks the S&P 500). One billion of those quotes affected the NBBO (National Best Bid and Ask) resulting in 44 million NBBO price changes. We then use those NBBO price changes to compute a ratio called the Relative Intraday Volatility or RIV by dividing the number of NBBO price changes in a day by that day's price range ((high - low)/close).

The charts below show the RIV (and its 20 period moving average) for each trading day from January 2005 through August 30, 2012. Notice how the RIV was quite steady up to the start of 2007 which coincided with the final roll-out of Reg NMS and the birth of High Frequency Trading (HFT) as we define it. Since then, the average intraday volatility in SPY has more than doubled, and was nearly six times higher in August 2011, and the peak intraday volatility in August 2011 was 10 times higher than it was in 2006. The second chart is scaled to the 20 period moving average to show detail. Note that the RIV already includes a volatility component (the daily trading range).

1. SPY Relative Intraday Volatility from January 2005 through August 30, 2012. 2. Same as Chart  1, but scaled to the 20 period moving average to show detail.

3. Apple (AAPL). Similar to SPY, volatility explodes after 2007.

4. IBM. Similar to SPY, volatility explodes after 2007.

5. Berkshire Class A (BRK.A). Surpisingly, Berkshire Hathaway, an extremely high priced stock, experiences significantly higher intraday volatility..

6. Berkshire Class B (BRK.B). Somewhat similar to Berkshire Class A but with a lower peak in 2010. Note that BRK.B split 50 for 1 in early 2010, which didn't seem to make a difference. 

7. Microsoft (MSFT). Curiously, the stock of Microsoft does not follow the same pattern of higher volatility as the stocks shown above.

The next 2 SPY charts illustrate why NBBO prices are far superior to trade prices for clean, accurate data input. Trade price spikes are a common occurrence and can greatly skew results, especially when looking at volatility. Price spikes occur because trades with different conditions or from different exchanges and reporting facilities are rarely synchronized in time (timestamps are added after the SIP queues exchange input, consolidates, and then queues again for transmission). Compounding to this problem:
8. SPY NBBO Spread (gray shading) and trade prices (red line).

9. SPY NBBO Spread (gray shading). The NBBO is much cleaner and mostly free of price spikes.

10. SPY Daily Close and Percent Daily Range.

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