Index Options: Table of Contents
SISCO'sOption World: Specific statistics and details for each individual contract month
Legend:
The CBOE put/call ratio represents the CBOE exchange's total put volume divided by the CBOE's total call volume. However, this widely reported value may not reflect the nuance of a particular index. So we have probed into the CBOE's data and determined each individual index option's put/call ratio. Below are the put/call ratios of the CBOE's top 5 most active indices.
Below are the composite put/call ratios. We use the term composite to mean the sum of all puts and calls traded in all actively traded contract months for a particular index. This produces one aggregate put/call ratio for each index option. In addition, each individual index option trades many different contract months simultaneously and each contract month has its own put/call ratio. For a detail of each contract month ratios, visit our Option World.
This series of notes and research is intended for those interested in exploring unusual ways of quantifying option data. It is assumed that you are familiar with options and their terminology. Here is a short list of some of the terms used in these discussions: "In-the-money", "Out-of-the-money", long, short, covered, uncovered, writing, expiration day, and open interest. It is also assumed that you understand the that options decay in value in a predictable fashion due to the "black-scholes" formula. And lastly, it is assumed that you know the basics of option trading; what it is your purchasing or selling and when it expires. If you aren't familiar with options, then peruse the following links to become acquainted with options.
Preface
Option data is so dense that option traders need specialized software to assist them in digesting the information. Typically option packages display option chains (a series of options from one base symbol) in search of deltas, betas, etc. These metrics are meant to assist the option trader in identifing the momentary disparities from the theoretical values computed by the Black-Scholes valuation formula. Wherein these disparities can be arbitraged/traded if one is inclined to chase these fleeting quantities. The primary purpose of the software is to display pricing information and to find price anomalies. Another facet to option software is it ability to display the historical prices of options so that the trader can visualize the decay in prices. In addition, these packages also show the trader multiple strike prices simultaneously and provide the trader with an arsenal of analytical tools to so that they can analyze any option they choose. These views of option data are important in the day to day buying and selling of options, but this is only the first level of option data analysis - contract analysis.
The articles presented below will skip the first level of analysis and focus on the next level of analysis - market analysis. These articles don't analyze one option contract in detail but rather aggregate all of the information reported from all of the individual options for one index into one composite value. The information for calls and puts are teased apart and recombined into various groups in an effort to understand option traders behaviours.
Option data is perhaps the most complex data to analyze. The complexity arises from the seemingly endless combinations of comparisons that can be made between the numerous contracts available to trade. In this series of articles presented, familiar data (such as the put/call ratio, volume, and open interest) are manipulated in a variety of unusal combinations. These articles do not explain the basic tools typically found in option software available to option traders, but they do they move on to the third level of analysis - intermarket analysis. These articles manipulate option data in atypical combinations in search of understanding the behaviour of option traders. This understanding of behaviours will hopefully lead to a more reliable use of option data to forecast future prices.
Part 1: Index Option put/call Ratios The traditional put/call ratio as provided by the CBOE is compared to the underlying index's individual put/call ratio. These are volume based ratios.
Part 2: Index Option value Ratios In this essay, the put/call ratio is presented in terms of value rather than volume. Here the index's dollar weighted put/call ratio is compared to several other ratios such as the CBOE's volume based put/call ratio, the index's individual put/call ratio, and the total dollar weighted value/total option volume.
Part 3: Index Option volumes Here the actual volumes are presented for each index.
Part 4: Index Option Open Interest The daily total open interest figures along with the put and call open interest figures are presented
Part 5: Index Options Total Theoretical Values This complex calculation determines which group of options can theoretically make the most money.
The following articles examine how much risk option traders are willing to take and how much money is spent on worthless options. In-the-money options have real value and out-of-the money options don't at the time of purchase, which makes them riskier to own. Risk is an elusive quality and that's why options change in value every minute of the day. However in general it can be stated that purchasing out-of the-money options cost less because they don't have any intrinsic value. If the contract were to expire today, the out-of-the-money options would be worthless. So if we know the total value of these options, we know how much money traders lost. The expression that 80% of all options expire worthless is a commonly used phrase to describe the option market. We will examine this axiom to ascertain if this statement is correct.
Part 6: Index Options In-the-Money/Out-of-the-Money Volume In this segment option volume is divided into four groups. The four groups consist of in-the-money calls and puts and out-of-the-money call and puts. These four groups allow you to see the activity of these different kinds of traders.
Part 7: Index Options In-the-Money/Out-of-the-Money Open Interest Once again the open interest is revisited by dividing it into four groups. The four groups consist of in-the-money calls and puts and out-of-the-money call and puts. These four groups allow you to see the activity of these different kinds of positions.
Part 8: Index Options In-the-Money/Out-of-the-Money Values We wanted to know how confident traders are with their positions. So we computed the daily change in value from the net change in open interest and these changes in value are plotted. Unfortunately there is an inherent problem. Values can change wildly from one day to the next so these charts are difficult to use due to the occasional spike shown.
Part 9: Index Options In-the-Money/Out-of-the-Money Flips A "flip" is a day trade. Your in and out of the market the same day or usually within minutes. Well, in these charts you'll see the volume that exceeds the open interest. For those unfamilar with option data, this is complicated by the fact that the trading volume is posted every evening but the open interest posted is for the previous trading day. In other words the open interest is posted one day later than the quote. This is due to the exchange matching trades overnight. So after the data is adjusted, the trading volume for each contract is compared to the change in open interest. Sometimes the volume exceeds the open interest and sometimes it doesn't. When the volume exceeds the change in open interest, these are classified as "flips". The hypothesis is that flipping increases at market turns. Go see for your self what the data show.
Part 10: Index Options Exchange Errors As a caveat, when the change in volume is less than the change in open interest, we classify it as an exchange error and these exchange errors are displayed. They're classified as errors because the volume can't be less than the change in open interest. This discovery was an unexpected surprise in our research of index option data and even surprised those at the exchange as to the amount of errors that occur each day. Yes the volume data is ladened with errors that total in the thousands each day. This is displayed merely for instructional purposes and no hypothesis was formed regarding the use of these data. Perhaps you'll see a correlation.
Part 11: Index Options Who's in the game?The Option Clearing Corporation (OCC) releases a daily report that tells us who made the trades. The trading activity is divided into three groups: Customers, Market Makers, and Firms. This segment shows you who is trading and how much they are trading.
Part 12: Index Options Price Histograms: In-the-Money/Out-of-the-Money Zones. Here is a matrix that shows the activity of the "big fish" and the "little fish". Twenty dollar-value-zones are created from $0 to $70+ These arbitrarily chosen values divide the option trading activity into zones: small, medium, and large.While these zones are mutually exclusive in price, these zones generally represent different groups of traders that utilize options for different reasons. However you can have a large trader in the small zone buying/selling thousands of contracts, but you will not find a small traders buying/selling deep in-the-money options. The essential question asked here is to see if small and large traders react alike? Do they use options for different reasons? Can their activity be associated with market turns?
Part 13: Life of Contract Total Trading Value The dollar weighted trading value is computed daily and cumulatively added to the the previous total. This value represents the total trading value of the index option. In the graphs displayed, these graphs show you how much was spent on options. It also shows you how much was spent in each trading month and it shows you how much money is in play, or can be lost. The total value of calls and puts are displayed and shows which side is favored by traders. Afterall, isn't this a proxy for sentiment. You be the judge.
created 9/24/03, ©2003 The Small Investors Software Co. All rights reserved.