This is the fourth and final installment of a four-part series of articles describing an options trading system that accomplishes better than averages outcomes.

The first installment (Part 1) explained methods for selecting companies and quantifying technical attributes. The second installment (Part 2) explained the theory and its assumptions, and the selection of strong reversal or continuation signals. The installment (Part 3) provides examples of application for the quantifying tests, with strong and weak outcomes.

This final installment (Part 4) summarizes the methodology and outcome of a two-year test.

This theory was first documented in a paper written for and published by the Journal of Technical analysis (JOTA), which subjected the concept to a rigorous series of peer reviews. The paper was published in the 2016 edition of JOTA, issue 69: JOTA issue 69 The theory was expanded and explained in greater detail in “Profiting from Technical Analysis and Candlestick Indicators” (FT Press)

 In the two-year test of signal correlation, the intention was to test the effectiveness of signal correlation with the use of options. The option contracts were generally selected to expire within one to two months, based on cost as well as time value.

The use of options is advantageous based on the tendency of stock prices to overreact to news, notably the unexpected, such as earnings surprises. When this is combined with application of signal correlation, the potential for consistent outcomes based on accurate forecasting is significant.

Unusually high losses (100%) occurred on 25 trades, and unusually high gains (above 100%) occurred in 14 trades. These are summarized below.


Outcome of 578 trades

Outcome Number %
100% loss 25    4.3%
Profit 1-25% 441 76.3
Profit 26-50% 70 12.1
Profit 51-75% 22    3.8
Profit 76-100%    6    1.0
Profit over 100% 14    2.5
                       Total 578 100.0%


Before trades were entered, a specific course of analysis was undertaken. This began with selection of high-quality companies whose stocks were traded with options. The methodology for stock selection was as follows, with analysis based on five fundamental attributes over the most recent 10 years:

  1. Dividend yield and history – higher-yielding stocks were evaluated as favorable, and raising dividends over the past 10 years was further evidence of a company’s fundamental quality. A company raising dividends for all 10 of the past 10 years was most desirable.
  2. P/E ratio range – the annual range from high to low price/earnings ratio was also evaluated, with the most desirable range identified between 25 and 10.
  3. Revenue growth – annual increases in revenues were also studied, and the more years of increased dollar value of revenues, the more favorable the opinion.
  4. Earnings growth – increases in net earnings were also evaluated in three separate ways: number of years reporting increases in dollar value of earnings, the same analysis for S&P core earnings, and a study of the net return (earnings divided by revenues).
  5. Debt capitalization ratio – this ratio compares debt capitalization to total capitalization. The lower the debt ratio, the more desirable; a flat or falling debt ratio was treated as a positive result, and a rising debt ratio was treated as a negative condition.

Additional factors were also considered in the selection of a stock for analysis. These included news concerning mergers or acquisitions, purchase by the company of its own stock, and earnings reports. An earnings surprise (positive or negative) was likely to result in an exaggerated move in the stock price, and in most instances, the price move retreated within two to three trading sessions. A study of 82,705 earnings surprises between 1984 and 2009 revealed an average of -7.49% of what the market expected. The occurrence of earnings surprises presents additional opportunities to enter short-term trades. (Shon, J. and P. Zhou, 2011. Trading on Corporate Earnings News, Upper Saddle River, NJ: FT Press)

Combinations of the five key fundamentals with other factors (especially earnings surprises), served as the basis for companies selected for analysis. Trades were entered during trading hours and based on study of the price chart provided by – with short positions the net of bid prices minus trading costs assessed by Charles Schwab & Co. of $8.75 per trade for the first option plus $0.75 for each additional option traded; and with long positions the sum of ask prices plus trading costs. The principles of signal correlation were applied to price charts, with the requirement for an initial signal plus confirmation, with proximity to support or resistance. Unusual situations were of special interest; these include large price gaps with volume spikes, price movement through support or resistance representing overreaction to earnings, rumors and other news, and exceptionally strong signals and confirmation.

The analysis of signal correlation provides convincing arguments favoring application of charting techniques to create reliable timing for trades. Theories may only offer one concept of how price movement works, and how success or failure should be interpreted. In this study, failed signals were traceable to weak trends, signals and confirmation; however, this does not guarantee that weakness will always lead to failure, or that strength will always lead to success.