Why should I use the Options Heat Map?
The predictive power of options activity in correlation to the stock market has been observed in numerous studies. Within the theoretical proposition of cross-market predictability, it has been observed that out-of-the-money options provide insight into short-term price corrections in the underlying. Gkionis et al. (2021) confirms the theoretical arguments of Easley et al. (1998) and An et al. (2014) on the cross-market predictability of options within the stock market by demonstrating how the options market “can lead the stock market with respect to both negative and positive price discovery.” These studies demonstrate that options prices can contain price-predicting information about the underlying stock.
Now that I have your attention, let’s talk about why this is important in the context of the options heat map. As demonstrated in the prominent options-market-related research, options prices have been proven to contain price-predicting information about the underlying. The options heat map allows you to see a visual depiction of the concentration of activity in the strikes surrounding the current price of the underlying.
So…What exactly is the Options Heat Map?
A heat map visually depicts a particular variable over two axis variables. The color of the cell in the heat map indicates some value relative to the corresponding axis variables. In the options heat map on the Quant Data platform, our main variable of interest is the net premium of calls/puts for a particular security. The two axis variables of interest are the strike price (X-axis) and the expiration date (Y-axis).
In the example above, the heat map depicts the net premium of calls and puts for SPY on 9/08/2022. As you can see, each cell represents a numeric value that is representative of the net value for calls/puts. A corresponding color accompanies this numeric value, this color indicates whether the net premium is leaning towards the call side (green) or the put side (red). The heat map cells are brighter if they have a higher relative percentage of net premium than the surrounding cells.
Additionally, you can hover over a cell to reveal more information about that particular contract. An example of this is posted above. The additional information includes call premium, put premium, net premium, call volume, put volume, net volume, call open interest, put open interest, and net open interest.
The heat map updates for every optionable ticker in the U.S. stock market in real-time. As a result, you can see a live, granular visual depiction of the market activity concentration on the options chain.
How do I use this data?
Traders may use options contracts to disguise information in the presence of uninformed traders or to take advantage of the information they possess by benefitting from the higher leverage of options contracts. With this information in mind, I’ve created a set of things to look for on the options heat map that can contribute to a directional bias in your analysis.
The first is to look for increased concentration of activity on out-of-the-money (OTM) strikes. Since OTM contracts are more likely to contain price-predicting information, we should place an emphasis on the activity surrounding them. Second, price corrections due to cross-market information gaps are typically quick and occur within the same day or overnight. With this in mind, when observing the chain for increased activity concentration, we want to focus on short-term expiries and be cognizant of the fact that these price corrections can happen quickly. Third, the more prevalent the concentration of activity, the more likely it is that price will be attracted to that zone. For example, five OTM strikes receiving abnormally high net premiums on the call-side will be more significant than if only one strike were to receive an abnormally high net premium. Fourth, keep in mind that ETFs such as SPY are commonly used to hedge positions. As a result, institutions rebalancing a position or creating a position for hedging can skew the activity within the heat map. By focusing on increased areas of concentration around strikes instead of individual strikes, you should not have to worry much about these positions. Fifth, use the heat map in confluence with other high conviction market data tools.
Here’s a shortened version of the checklist:
Increased concentration on OTM strikes.
Focus on activity around short-term expiries.
The more prevalent the concentration is, the more likely price will react to it.
ETFs may be skewed by hedged or rebalanced positions.
Use the heat map in confluence with other market data related tools.
Case Study #1:
The image above was taken at 9:40 am ET on September 7th, 2022. Just 10 minutes into open, you can visually see the obvious concentration of activity on the OTM calls on SPY. At this time, the price of SPY was hovering around $392.17. The $391-$397 strikes were heating up with call activity. We see that this activity concentration was focused on short-term expiries. It met all of the criteria on our checklist. As a result, you can see in the image below that SPY pushed all the way to $394 shortly after the heat map image was taken and posted within our community. The heatmap on SPY continued to receive large amounts of activity, indicating a bullish directional bias. SPY pushed all the way to $398 on that day. In this scenario, the heatmap remained bullish throughout the day, with the concentration of activity receiving more net premium as the day went on. This may not always be the case, it is possible that the concentration of activity reverts intraday. In that situation, you should adjust your positions accordingly. That’s what makes the heat map so strong, it’s real-time and extremely effective.
Case Study #2:
The image above was taken at 9:44 am ET on September 6th, 2022. 14 minutes into the open, you can see the obvious activity concentration on the OTM strikes for SPY. At this time, the price of SPY was hovering around $392.31. The $388-$393 strikes were heating up with put activity. Again, this activity was focused on short-term expiries. It met all of the criteria on our checklist. As a result, you can see in the image below that SPY broke down all the way to $388 shortly after the heat map image was taken and posted within our community. What I like about this example is that the concentration of activity began to switch to the call-side, and as a result, SPY reversed. In this scenario, the heat map provided a fantastic opportunity to trade the near 4-point move to the downside. This situation demonstrates how quickly the price can correct, as we discussed previously.
Don’t forget to check out our options heat map video here.
Also, make sure you check out our article on using Dark Pool levels here.
Dark Pool levels are a fantastic tool for identifying supply/demand. They can be extremely powerful when used in conjunction with the heat map!
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