Excerpted with permission from Day Trading Options: Profiting from Price Distortions in Very Brief Time Frames , by Jeff Augen FT Press; I t is only fitting and proper that I write these words with a Conklin fountain pen—a gift from my wife. Most writers prefer a computer.

This pen has seen it all: Maybe some things never change. Everyone knows that the market crashed in Big time stock manipulators drove prices into the stratosphere by selling to each other. When the price climbed high enough that the average investor finally jumped in, they dumped their stock, collected the profit, and watched the collapse.

These investors often believe that they can level the playing field by working hard and staying one step ahead of the market with a combination of the latest software and news sources. They often follow a combination of fundamental and technical indicators that include analyst statements, earnings reports, company news, insider transactions, short interest, and a few different types of price charts.

Unfortunately, even the smartest and most diligent traders are further back in the pack than they might think. Consider, for example, IBM—a heavily traded blue chip stock followed closely by many analysts and a large investment community. The difference is surprising because insiders are restricted with regard to when they can sell stock; in this sense they are disadvantaged and might be expected to realize a lower average selling price.

Lifting all restrictions, therefore, might cause the gap to widen even further. In either case the point is clear. A private investor with some charting software and a few analyst reports is no match for corporate insiders who know considerably more about their own company than the general public. The same private investor must also lose to large institutional analysts who have access to the companies they write about.

Analysts routinely visit these companies and meet with key executives before writing their reports. Furthermore, their reports are proprietary and are often made available to a restricted group of subscribers or large clients of a particular brokerage. The playing field cannot be level when all investors do not have access to the same information.

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Many investors who realize that they are operating at an information disadvantage avoid strategies that depend on fundamental business analysis and, instead, focus on purely technical approaches.

Dozens of technical indicators are available in addition to scripting languages that allow investors to create and test their own. Most platforms also allow automatic order entry based on a predefined set of rules. Serious traders can chart information in a variety of time frames and simultaneously analyze this information with different indicators. When a signal appears, their software can instantly place a trade without asking for confirmation.

It would seem that such systems might have the potential to level the playing field for the private investor. Unfortunately, the capability gap between institutional and private investors is even larger on the technical side than it is on the fundamental side; that difference is growing rapidly. During the past few years, computerized algorithmic trading systems have become the dominant force in most financial markets, and their sophistication exceeds anything available to the general public.

Such systems instantly identify and exploit emerging trends with the effect of extinguishing them almost as fast as they appear. Unfortunately for the private investor, this new dynamic has completely invalidated many approaches to technical analysis that worked well just a couple of years ago.

These changes are a logical evolution of the random walk hypothesis described by Burton Malkiel in his book entitled A Random Walk Down Wall Street. Simply stated, the random walk hypothesis asserts that the evolution of market prices cannot be predicted—that is, the recent price history of a stock does not contain information that can be used to predict its future.

The random walk concept is built on an important set of assertions known as the efficient market hypothesis EMH. EMH predicts that such inefficiencies cannot persist. It was first proposed by Eugene Fama in his Ph. Since that time, there have been many debates between proponents of the theory and investors who believe that they can identify chart patterns with predictive power.

However, for a chart pattern to have predictive power, it must also be persistent in the sense that the market cannot learn the pattern and eliminate it. The random walk model described by Burton Malkiel in his book assumes that stock price changes are tantamount to coin tosses. The discussion is meant to illustrate the ease with which investors can be fooled by randomness.

These opportunities exist, in part, because contemporary option pricing models assume continuous trading even though markets are closed over the weekend and from 4: An efficient market can be expected to respond to these dynamics with price changes that comprehend the down time. These variations represent profit opportunity to an option trader and, as we shall see, the opportunity can become very large under certain circumstances.

In this regard, we will review new approaches that separately measure overnight, intraday, and traditional volatility. These differences make it possible to capitalize on short-term anomalies where volatility is misrepresented in an option price.

Finally, news events often introduce brief distortions that take many minutes for the market to digest. During these brief time frames the market becomes inefficient and new opportunities arise for the short-term trader.

We will capitalize on these opportunities with a new technical indicator that can be used to quantify rising or falling volatility. Investors who believe they have a trading system that consistently beats the market in all circumstances should read no further. This book was not written for them.

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It was written for investors who are seeking a different approach and are willing to work very hard to perfect new trading strategies. My goal was to find a way to narrow the performance gap that has plagued private investors since financial markets first opened. Volume adjusted prices VAP were used to obtain maximum accuracy. Each transaction price was multiplied by the number of shares traded; results were summed and ultimately divided by the volume over the entire time frame.

Insider trades are those reported on SEC form 4 and made available through Edgar Online. These transactions are readily available through many web-based sources including Yahoo!

Posted by Danielle on January 2, at You can follow this conversation by subscribing to the comment feed for this post. On page of day trading options you calc the log of C-C.

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Using Excel I put in the c-c George Howell June 18, at Al Uutela August 1, at I purchase long straddles on equities with a history of increasing volatility 2 weeks prior to an Earnings Release and selling it either just before or just after the release.

Is there software that can automate this search? My process right now is largely manual involving an Excel Spreadsheet and any software I evaluated does not search on a range of Earnings Release dates in the future. Mark Scovera December 4, at The letters and numbers you entered did not match the image. As a final step before posting your comment, enter the letters and numbers you see in the image below. This prevents automated programs from posting comments.

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TL Twitter Updates follow me on Twitter. Profiting from Price Distortions in Very Brief Time Frames , by Jeff Augen FT Press; Preface I t is only fitting and proper that I write these words with a Conklin fountain pen—a gift from my wife.

Eighty years later, the game remains remarkably unchanged. The recent crash serves as a terrific illustration.

Day Trading Options by Jeff Augen - Traders' Library Blog

Investment banks built high-risk portfolios of mortgage-backed derivatives, money poured in, bonuses flowed like water, and when it all collapsed the general public picked up the tab. Smart investors who saw the collapse coming and shorted the market lost money as the bubble inflated. Those who stayed in the market watched their money evaporate when the bubble burst.

But many private investors—including the author of this book—did just fine. For the most part, they tended to be students of both the economy and the financial markets—active traders armed with a trading platform, charting software, and access to live news feeds.

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