Archive for S&P 500
Sold off on comments from Fed and then recovered back to crime scene. Gap up and took out Y+1. When stop run actions ended ES dropped back down to below Y+1 and opened the door to week mid. Dropped back down to almost week mid on Friday. Closed the week above Y-0 and midpoint.
Outside week but closed near midpoint. Y-0 and B-0 very close to each other. All points to indecision as oppose to a strong directional suggestion. Need ES to find support at B-0 for a retest of at least Y+1.
A slide below B-0 can easily induce a drop to Y-1.
Not going to be an easy week to trade.
30-minute S&P 500 charts presented without comment.
Year 2000 Jan chart.
Year 2014 so far.
Majority of option traders who understand options tend to focus on the mathematics of VIX while the chart traders who trade S&P 500 Index futures tend to focus on the chart patterns and confirmation signals from VIX.
Who is right?
Who understand VIX better?
Here is a short piece on the VIX Phenomenon that no one in the financial blog sphere ever talked about. Maybe learning something about VIX from a completely different perspective all together can help us answer the questions above.
CBOE Volatility Index
VIX is the symbol for CBOE Volatility Index. I am not going to waste time here discussing what it is. You can find out more about the index at wikipedia. Links are provided below for further reading.
The one single most important key about the VIX value itself is that it is an annualized rate of the expected variance of the S&P 500 based on the nearest traded strikes of the SPX options.
Thus the value of VIX cannot be directly translated into the expected volatility until you plug the value into a formula to get the estimated standard deviation of the period you are interested in. The calculation method is quite simple. There is an example in wikipedia illustrating the method so I am not going to repeat that here.
Let’s dive in to the heart of the issue.
The VIX Phenomenon
Following is a table of VIX levels with the corresponding implied 30 days percentage change and the translated absolute value at 100 points interval based on S&P 500 price levels. If you do not understand what I mean in the first sentence, it is okay. Let’s look at the table first and I will explain right after.
When VIX is at 13, the 30 days estimated volatility is 3.75% and that translate into 45 S&P points if S&P is trading at 1200. If S&P is trading around 1800, that translates into 67.55 points. These absolute values carry a lot of weight. They are there telling you that if S&P is trading at 1200 with VIX at 13, there is a 65% chance S&P is going to stay within +/- 45 points from 1200. If you trade options, you must know this to formulate your strategy properly.
So many numbers in a huge table. What’s the point?
I have computed the average value of VIX since 1997 at each 100 point interval on the S&P 500. It is the 2nd line from the top of the table. For example, when S&P was trading at 1200 +/- 50 points, the average value of VIX was 20.4 since 1997.
Looking at the numbers themselves it is not easy to draw a connection. So, I have highlighted these average VIX levels in yellow corresponding to the respective S&P price levels. Now, they are very interesting.
The higher volatility readings at 1200 to 1500 was mainly due to the steep decline and spike values in VIX during the last 2 market crashes. But that does not change the fact that there is a general trend of decline in VIX level relative to the increase in S&P 500 price levels.
Why is it the case?
Keep It Simple Stupid
The clue is the near constant range of the absolute values translated from these standard deviations.
From the 1600 to 1800 column, the absolute value is within a constant range at 65 to 75 S&P 500 points.
If the extreme spikes (value greater than 40) are removed from the VIX historical readings, this constant range will be the same for the 1300 to 1500 columns too.
Traders who trade S&P 500 options, be that used for hedging or pure speculation, do not really depend their final trading decisions on their option models. When things boil down to money making, these traders are really looking for the absolute potential in their trades and adjust the risk they are going to take accordingly. After all, profit and losses are measured in S&P points, not the Greeks in the option price models.
In short, options on index are traded off the absolute value of the indices because human do not trade with unlimited capital and fictitious percentage measures. Humans behave the same way no matter S&P trading at 1200 or 1800. This phenomenon also indirectly shows that majority of volatility models failed to capture the essence of human trading behaviour.
It is now easy to answer the questions I raised in the beginning of this article.
The option traders more talented in math are blinded by their superior math skills and ignored the fundamental principle of any market. That is, traders are bounded by their profit making objectives and risk profiles. Thus, no matter what they think, VIX has the characteristics of a tradable instrument and it shows in its charts.
The traders who are good at chart reading can often pick up the interesting behaviour of VIX like how it loves to hold a particular level for a long period of time. That is excellent detective work but the lack of understanding the nature of VIX makes it difficult to figure out the reasons behind such phenomenon. In turn, the inference from the observations may not be as accurate as one likes it to be.
Both sides have something to learn from each other.
A frustrating week for many. As oppose to finding resistance at Y-0 and start a pullback, ES managed to hold in a tight range above previous week close. By the time NFP was out, it managed to hold week mid and blasted higher to close above previous year close. Closed the week above Y-0 and midpoint.
Bullish for a test of Y+1. Breadth deteriorated a lot. This push up will likely be carried by a few names only.
Expect sudden volatility this week due to compression in tick reading.
Unlike Nasdaq 100 and other indices managed by various exchanges, information on the S&P family of stock market indices are proprietary. That means all kinds of information about the S&P indices are not public information and that such information can only be obtained through various paid services that licensed the information directly from the owner of the S&P indices. The data you get from these paid services in turn bound you to certain limitations in terms of the scope of usage. Hence no one can make public the data they obtained directly from the source or its licensed data providers.
A Matter Of Public Records
This creates a special problem for those traders who are interested in the historical components of S&P 500 and its related indices but do not have access to services like Compustat or Bloomberg. Luckily, various fragments of information about these indices have to be made public due to the regulatory requirements of the financial products created around these indices. Hence, there exists public records of the public announcements of the changes to the constituents of these indices and snapshots of the lists of index components over time.
As I mentioned in my other article on Custom Market Breadth Components Resources, to track the latest set of components in S&P 500 can be done easily with the latest updates at the SPY ETF main site, or, if you track many indices, using a low cost paid service like TC2000 will save you time and effort.
On Going Tracking Is Easy
As long as you keep up with the changes once a year, your data set should be reasonably good for constructing your own custom market breadth data. The reason why it is possible to keep track of the changes once a year is that the number of companies switched every year is around 20 to 30. Majority of these changes are made towards the second half of the year. Statistically it means the overall usefulness of your custom breadth data are still good as long as many of the switched out companies are still trading.
If you are serious about the quality of your breadth data, you can go as frequent as a change is made. Personally, I found the data set on most breadth data are good if you keep your component list updated either monthly or quarterly.
Tracking Down Historical Components Is Difficult Detective Work
For historical components, however, it is a lot more complicated if you have not collected the information at the time they were made public. There is no readily available lists of historical components for download anywhere on the Net. You will have to go to the source which is very expensive or reconstruct the list yourself by back tracking all the component changes from the announcements.
I found the press releases from S&P (www.standardandpoors.com) itself provides the cleanest series of events to follow. If you plan to reconstruct the historical component lists yourself, this is the best way to go.
Other free sources are often incomplete and lack updates over time. For example, the list of components and the changes from wikipedia.org are incomplete at this point in time. The various online records of historical changes are incomplete because retail traders in general do not understand that certain corporate actions can still lead to component changes while the events themselves are not announced specifically as a planned change of components in the S&P 500.
A good example of such is the change of ownership of certain listed companies. These companies can be bought or sold by their parent companies any time. If the new owner of the listed company causes a change of industrial classification according to S&P, a replacement will be elected but it will not be a regular component change event.
Another source of confusion is symbol change of existing components. Many long lasting companies like to own the more iconic symbols for their stocks. When such symbols were freed up due to various reasons like bankruptcy or merger, many companies will rush in to apply for takeover of these rare symbols.
It may sound silly but who are we supposed to judge when people actually fight for special license plates on their cars.
If you find the description above confusing, be assured that you are not alone.
It has always been messy with corporate actions.
Mix Up Of Historical Data On Individual Components
This issue is actually an even bigger challenge than the maintenance of correct components. I guess I should mention it here because it is caused by the same messy issues with the way symbols are being reused.
Due to the reuse of symbols among the listed companies, it is very easy to make the mistake of using the wrong historical data from your data library for analysis and custom market breadth data generation.
Here is a good example. Washington Mutual was listed under the symbol WM before its collapse back in 2008/2009 financial crisis. Since its change of symbol at the time of its bankruptcy proceedings, Waste Management Inc. assumed the symbol WM from Washington Mutual even though it was listed under WMI happily for many years. Now that when you look at the historical components of S&P 500 by symbols only, many people will mistaken that the WM back in 2008 is the same WM showing up in 2009.
Casual researcher on the S&P 500 components will likely mix up the two even if they are aware of the potential issue. Many data vendors would stitch the Waste Management Inc. stock data under the two separate symbols into the new one that is now in use. It is standard practice and is a big convenience for majority of the traders. There is no problem with that until you actually need access to the data of Washington Mutual. The data services have no way in telling that the symbol WM you are looking for is in fact Washington Mutual. In another words, your access to the historical data for Washington Mutual is forever lost.
As you can see, there is no easy solution to this problem unless the data service you are using provides access to historical data by CUSIP numbers or other unique identification code. As far as I know, only high-end data services catering to institutional clients provide this level of historical data access.
My Snapshots Of Historical Components
I have been constructing my own custom breadth data since 1990s. Hence I have a large collection of snapshots of historical components of many indices. They may not be the most complete set and likely to contain errors here and there. I believe, however, they are useful to anyone interested in the historical changes in the S&P 500 components over the years. They are also critical for the accurate construction of custom market breadth data.
I am making the yearly snapshots of the S&P 500 component list available in the Historical Data Bank.
The data set starting from year 2008 is available for free to all members.
If you choose not to join us, you can purchase the data individually.
Strong reaction after closing year 2013 at the high. Sold off quickly after New Year until 100% absolute range expansion was reached. Stuck in that zone since. Closed the week below Y-0 and midpoint.
Potential spike and ledge pattern suggests that a break of B-1 will give us the B-3 target.
Although holding above B-1 points to at least a retest of B+1, I would not turn bullish until after B-0 is cleared.
Bennie arranged a not so important speech 1 hour before market close.
S&P managed to hold its ground by close.
Got our consolidation-like range. Upside target of above mid-1830s printed. Closed the week above Y+1 and midpoint.
Seasonal bullish bias used up at this point. No strong directional play until after new year.
Chart pattern suggests a retest of Y-2 is necessary. The issue is timing. Since next week is year end, I suspect the wild rides will probably start after new year.
Out of the 3 indices, ES is the worst offender among them in trapping the bears. Gap higher to start the week and drifted lower into FOMC announcement. Then the new shock spiked down to below Y-1 yet immediately reversed back up and zoomed to the normal upside target as mentioned in real-time chat. ES then continued its march higher by Friday and printed another new year high just like the seasonal bias suggested. Closed the week near Y+1 and near week high.
Outside up close week. 2nd outside week. Very powerful setup pointing to more upside. Due to the wide range swing, consolidation in play.
Combining the biases, we get a 50% range swings around Y+1 / B+1. Do not underestimate this 50%, we are talking about upside potential of above 1840 for the bullish scenario and at least mid 1830s for the sideway scenario. Will be difficult to trade swings like this in the expected low volume environment.
I thought the backfill back down to Y-1 was going to be choppy. Instead, we got this clean directional slide all the way down. Cleared Y-1 easily and then took ES down to almost Y-2 at 150% week expansion before support was found. Closed the week below Y-1 and near week low.
Outside down week with close below Y-1 is bearish. Very directional week with range expansion, however, points to consolidation move the very next week. So more downside is expected but it could be just a tad lower.
Once a bottom is found, ES can drift back up with low volume to B-0 easily.