eSignal recently introduced a series of more than 40 option statistic symbols all based on the put / call ratio. The main symbol for the put / call is $PC-ST and is calculated by dividing the total volume of all put contracts by the total volume of all call contracts.

If you are new to the markets, you may be wondering what puts and calls are. Let’s do a quick review of options, so we can better relate to the overall picture later on. Puts and calls are types of option contracts.

An option contract is a right to buy or sell a certain number of shares of a specific stock at a specific price and before a specific expiration date. A contract that gives the owner the right to buy is called a call, and one that gives the right to sell is called a put.

Let’s look at a quick example. At the time of this writing, a popular contract to trade is AMD January 2007 25 Call (AMD AE). If I owned this call option, I could buy 100 shares of AMD at a price of 25.00 per share any time before the expiration of this contract, which occurs on the third Friday in January of 2007.

Two typical types of option traders are a speculator and a hedger. A speculator typically doesn’t own any shares of the underlying stock nor has any desire to do so but is, instead, predicting that the price of that stock will head in his or her direction, and, thus, the price of the option contract will increase exponentially.

A hedger is someone who wants to protect an investment by buying a contract in the reverse direction.

For example, if I have invested in 1,000 shares of company XYZ, I can purchase 10 put contracts (100 shares each) to protect against my 1,000 shares from going down in value. This is because the value of the put contract typically rises at a similar rate to the decrease of the equity’s value.

The majority of equity options volume is speculative. Knowing this, we can say that when the put / call ratio is rising, more bears are out there buying put options than bulls buying calls. And, the inverse is true as well; a falling ratio is a bullish sentiment.

Let’s take a closer look at the put / call and how this relates to trading. Take this chart for example:


Figure 1: Composite Put / Call Ratio

Based on the way the put / call is calculated, you may have thought that the typical value is centered around 1.00 (i.e., a balance between the number of puts traded versus the number of calls), but, in actuality, there is a typical bias to the up side in options trading, causing the average to be approximately 0.75 or 0.80.

Also, take note of how choppy the values are. This is common in volume-based statistic symbols. To make better use of these values, a smoothed-out version of put / call is a great way to look for patterns and breakouts, and a moving average fits the bill nicely.

In order to find overbought or oversold conditions, we’ll need a way to assess when we’ve reached extreme levels of sentiment. One method is to approximate trend levels above and below the typical value of the moving average (i.e., ~0.75-0.80). In the example shown below, we’ll use a 9-period Exponential Moving Average (EMA) of the put / call in combination with horizontal trend lines at 0.90 and 0.65.

Figure 2: EMA of the Put / Call and the $SPX

In the example shown above, we can see that the EMA’s peaks and valleys can often indicate that a turn is occurring. In the case of “A”, the amount of put volume was steadily increasing during the down trend in the S&P 500. At the first down turn in the put / call, the S&P 500 started a 3-day uptrend.

Likewise, “B” peaked right at 0.90 on the EMA, and it was one bar away from the bottom of the retracement in the S&P 500. “C, D and E” show how the lows in the put / call will often show an overbought condition in broad market indices.

“F” is where we are at the time of this writing. Remember how the peaks at “A” and “B” caught some nice up turns? I would expect we could see another continuation of this uptrend at approximately this same level.

Another method is to use the Linear Regression Channel to pick the extreme levels. This study uses a least squares model for the line of best fit (the red line) and standard deviation to determine the channel lines (in blue). This dynamic analysis method is less subjective and geared more toward traders who lean toward the technical side of market analysis.

Figure 3: Linear Regression of the Put / Call and the $SPX

As you can see, very similar points are found with this technique. The orange circles picked out the extreme lows in the $SPX. And, to a lesser degree, the green circles picked out the tops. Another nice thing about using the linear regression method is that you get a clear mid-point (in yellow) to help define areas of indecision. Notice how the market is sideways while the $PC-ST is riding the basis line of the Linear Regression.