Augen, Day Trading Options

Jeff Augen’s Day Trading Options: Profiting from Price Distortions in Very Brief Time Frames (FT Press, 2009) is tough sledding. Although it’s a slim volume (under 200 pages), it took me the better part of a day to digest it—or, more accurately, most of it. But I consider it time well spent. The odds that I will ever adopt Augen’s strategies as my own are slim to none. No matter. What is most valuable about this book is that it demonstrates how, with imagination and careful crafting, the trader can maintain his edge even as markets change. In this respect the book is both challenging and inspiring.

Let me say up front that if you’re looking for a get rich quick scheme you’ll be sorely disappointed. The book’s title may evoke a variation on, or an update of, the day trading bubble days when guts trumped brains. But this book is more like the revenge of the nerds. Well, even that’s not accurate. Augen is not dueling against the unschooled but against the likes of high frequency traders. As short-term markets have evolved to the overwhelming advantage of those with outsized capital investments in both talent and technology the individual trader needs to retool. Augen points out one way to do this.

The first order of business is to identify the enemy. For Augen the problem is that “the combined activities of automated high-performance trading systems extinguish market inefficiencies almost immediately.” For instance, “studies reveal that large price changes do not result in persistent trends—even at the single-minute level. Stated differently, the recent price history of a stock does not contain enough information to predict the direction.” (p. 35) The retail trader, whatever his time frame, will almost always lose to the institutions who avoid the effects of volatility and optimize their use of capital “with very brief trades placed at just the right time” (p. 44) over a variety of instruments.

So as financial markets have become increasingly efficient and as “the war is being fought between rival computer systems, with speed and precision being the most important considerations,” (p. 77) how can the individual trader compete? He needs to find “statistical advantages that cannot be extinguished by the market as simple inefficiencies.” (p. 78)

Augen offers several examples of how to exploit volatility distortions in options. The advantage of this approach is twofold. First, the trader doesn’t have to make a directional bet and, second, he is playing in a space (volatility) that high frequency traders avoid.

Take, for instance, the sometimes dramatically different measures of historical volatility depending on the slice of the 24-hour period one looks at. Traditionally, historical volatility is calculated by using a month’s worth of close-to-close price changes. But what if we separately calculate overnight volatility (close-to-open), intraday volatility (open-to-close), and weekend volatility? (Augen shows how to calculate the annualization factors for daily, intraday, and overnight volatility. For instance, intraday volatility is the standard deviation of the 20 [or whatever number the trader wants to plug into the formula] most recent open-to-close price changes multiplied by 30.5.) We will find that options are often underpriced intraday because their prices are based on close-to-close calculations. Moreover, we might find that “two stocks with similarly priced options have significantly different profiles with regard to intraday and overnight volatility. . . . The first reacts to overnight events around the world; the second reacts to news events that occur during the trading day. The first stock might be a candidate for overnight long straddles initiated near the closing bell; the second might be a candidate for the same trade placed after the market stabilizes around 10:00 in the morning.” (p. 93)

Augen takes the reader through a series of challenging ways to capitalize on volatility distortions. Although Augen writes clearly and uses only the rudimentary math that all options traders should be familiar with, these examples are not for traders who struggle with how to structure a credit spread. Moreover, they are not formulaic by nature; the trader still has to seek out potential anomalies, still has to use his brains. But I think they are important case studies in how to think imaginatively, intelligently, and profitably about financial markets.