Sneak-Peek: Historical Series Metrics

Historical Data is difficult. It’s big. It’s often messy. It’s cumbersome to deal with more than a handful of series at a time. Price-histories are pretty well-handled in most financial information systems, but historical series data for Price/Earnings, EBITDA, 30, 60, 90-day implied volatility are usually a bit harder to get to.

Unless, of course, you have Bloomberg.

Bloomberg has one of the most impressive historical data systems on earth. Not many people realize this, but chances are good that if there is a metric (mnemonic) that yields a numeric data point for a security, Bloomberg keeps historical data on that metric. PE_RATIO, for example, can be tracked as easily as price-history. As can complex metrics like Volatility skews (1M_CALL_SKEWNESS).

As is so often the case, however, looking at one historical series can yield only so much information. What we really want to do is compare the properties of one series to another. For example, we may see that the P/E ratio of AMZN is at a historical high, but what of its peers in the sector (GOOG, SYMC, EBAY, MFE, YHAOO, EXPE)? Are their P/E’s also at historical highs? Does AMZN stand out?

We’ve been quietly developing some new tools to help answer questions like this for the next-release of AlphaVision™ for Bloomberg. We call this new functionality “Historical Series Metrics”. Today, I’m going to give you a sneak-peek.

The process for creating a Historical Series metric is similar to creating a filter metric or a calculation metric. Inside the Custom Metric Editor (Tasks -> Open Custom Metric Editor) you will find a new button labeled “New Historical Series Metric”.

Clicking this button will bring up the Historical Series Metric Dialog.

The historical Series Metric Dialog allows you to select the Bloomberg Metric (Mnemonic), the Date Range, and the series calculation type (Min, Max, Mean, Standard Deviation, Decile Latest, Percentile Latest). Above, you can see that I’ve selected PE_RATIO, I’m going to look at the historical time period from 8/4/2007 to 8/4/2009, and I am after the Percentile Latest, which will tell me what percentile of the last 2 years of data the latest value falls within. Let’s have a look.

Below is a screenshot of the Internet sector. AMZN clearly stands out. Why? AMZN’s P/E Ratio today (8/4/2009) is about 69.2. Our Historical Series Metric tells us that AMZN’s P/E Ratio today is in the 73^rd percentile of all of it’s closing P/E ratios over the last two years.

What is even more interesting about this picture, however, is that AMZN is the only firm in the internet sector, whose P/E so high on a historical basis. Let’s look at this another way – what if we switch and look at the GICS Industry Group to which AMZN belongs: Retailing.

Whoa! That’s a surprise. Virtually the entire Retailing group is trading at its highest P/E’s in the last two years. Did you know that? I certainly didn’t. Right now, earnings in retailing companies are as expensive as they have ever been over the last two years.

PE_RATIO is quite interesting fundamental research data-point. But what about something a trader might look at day-to-day: Implied Volatility – Specifically CALL_IMP_VOL_30D.

In this image of all firms contained in the S&P 500, I’ve created a new Historical Series metric by cloning the PE_RATIO one and simply changing the metric to CALL_IMP_VOL_30D. I’ve set the color-bar to highlight the firms with the highest (green) and lowest (red) historical 30-Day Call Implied Volatility leaving those firms trading near their medians white. In general, one can see that very few firms are trading at historically high volatilities. Given the historic volatilities in the market a year ago, I think this makes good sense. If you are buying Vol today there’s a lot less out there to pick from. From this image, DYN, PCS, WPO, & CFN look like ones to keep an eye on.

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IV90 Lows in ETF Market

Written By: Andrew Giovinazzi


Monitoring IV90 Lows in the ETF market and what that means for the broader Equity Market

Before the Meltdown of the last two days the major ETF Classes made IV90 (implied volatility of 90 days) lows or was within a few days of making those lows. The Equity markets are currently very close to year highs. The Implied Volatility in the market had gotten exhausted as the realized market volatility (HV) was underperforming on a broad basis. This pressure keeps pushing the IV90 lower as Implied Volatility comes in across the board. How does a trader or PM see that?

Earlier in the week the landscape looked like this…

On this landscape we are looking at several things- First each building represents an ETF (the landscape shows all ETF’s with traded options) and the footprint of each ETF is the end of day (EOD) volume with the SPY leading. The colorfield from red to green shows IV90 trading close to its lows (dark red with the SPY only .73 away from its IV90 lows of the year) and moving farther away from those lows from white to green. Of note is most of the heavily traded (large buildings) are very close to their IV90 lows signaling a new bottom across most of the ETF landscape. The active volume counts the most.

A new picture emerges as the market declines and IV90 starts to bounce off of its lows. This is the exact same landscape 3 days later.

Today, three days later the landscape looked like this….



Note here that the SPY HV90 is now 2.7 points away from its lows (about a 10% increase). The landscape is much “less red and more green” indicating that the market decline pushed IV90 up across the entire ETF universe as IV90 moves away from the yearly lows. The combination of short term Equity highs and IV90 lows is a signal to stay away from selling volatility in the farther out months until a move in the Equity markets occur.

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It's All About the Consumer

Written by: Andrew Giovinazzi

Consumer spending comprises approximately 70% of GDP
The unemployment rate remains high and continues to grow
Personal savings as a % of disposable income is high, but for how long?

I started with an idea on consumer spending and let AlphaVision™ show me how the market reacted to the sectors shown below after the recently updated Chain Store Sales[1] report. Sometimes simple investment concepts require simple analysis. The investment community has been focused on financial institutions (rightfully so, I might add) and the end of civilization as we know it; however, the truth is, it’s all about the consumer. Overall, financials have made sharp gains in 2009, most of them after investors digested news on banks’ stress tests and Bernanke’s optimistic expectation that the economy would recover late this year. Since short-term financial plays have been realized, what’s next? To answer this, let’s focus on consumer spending.

To see potential consumer targets (and investment targets) I looked at two sectors: Retail - Discount Stores and Retail - Drugs, the two largest outliers responsible for improvement in the Chain Store Sales report. Using AlphaVision™, I scaled these two sectors for YTD price % changes.


The metrics reveal that Wal-Mart’s (WMT) price is down nearly 7% YTD while Family Dollar (FDO) has gained over 25%. Relative to the S&P 500, FDO has gained over 38%. In the retail drugs sector, Rite-Aid (RAD) and Walgreens (WAG) seem to be making the most noise. RAD gained about 29% and WAG is up 11% YTD. Using AlphaVision’s Metric Scout [see screen shot below], I pulled a side-by-side view of YTD, YTD relative to S&P500, and month-to-date price % changes. Looking at month-to-date percent changes, it appears the retail drugs sector has made impressive gains recently and therefore, does not look as attractive[to buy] as the retail discount stores.



If the economic recovery isn’t realized as soon as Bernanke thought, consumers could continue to substitute large scale discount retailers with dollar stores. Perhaps going long FDO (and/or DLTR, Dollar Tree) and shorting WMT is a good strategy. If the worst is over and the bottom is struck, consumers will “gradually” make their way back to WMT – remember to keep an eye on personal savings and unemployment. This scenario would suggest going long WMT and short FDO. In either case, consumers will never completely stop shopping at retailers such as WMT. While I am not as optimistic about the recovery as the Federal Reserve, I believe FDO is poised for a pullback given its YTD upswing relative to other stocks in its sector. Shorting FDO and going long DLTR could be a good relative value play, or for the long-term value investor, simply going long WMT could make sense.

[1] Source: Moody’s Economy.com and the International Council of Shopping Centers

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