# Using the Options Order Flow Sentiment Screener

## Page Summary

This page provides unique insight on the market's favorability towards particular stocks, indicating whether they are trending bullish or bearish based on investor order flow. Click here to go to the page https://marketchameleon.com/Reports/OptionOrderFlowSentiment

Order flow sentiment is a unique technical indicator of market trending based on actual investor trading data. The theory is based on the belief that investors "bet" on market direction, based on their willingness to purchase puts or calls at the high end of the bid - ask price spread. By calculating overall market sentiment based on this investor desire, traders obtain valuable insight on trending market direction when considering investment decisions for specific equities.

## How do you know if an option is bought or sold?

First let's explain what we mean when we say an option is being bought or sold. Every trade has a buyer and a seller and that trade is made up of a dealer and customer on the options market. What we are trying to determine is if the customer orders are on the buy side or sell side. Customers enter orders into the market to buy or sell options. The dealer displays prices (quotes) they are willing to buy or sell any particular option contract.

A car dealer makes a good analogy to help you better understand this concept. A car dealer is willing to buy your used car and/or sell you a used car. The difference between the price a dealer buys and then sells is called the spread or profit margin. Similarly, when an options dealer trades an options contract with a customer, the dealer will have a theoretical profit margin based on a mathematical equation. As part of that equation, they tend to hedge their position with the underlying stock to mitigate directional risk.

Examples
If the dealer is willing to buy an option contract for \$1, we call this the bid. If a dealer is willing to sell the same contract for \$1.25, we call this the ask or offer price. So, the dealer quote would be the bid and ask""

\$1.00 \$1.25

Now, let's say we witness a trade of 10 contracts for \$1.25. We can infer that the incoming order was a buy of 10 contracts because the trade of \$1.25 paid was the ask price of the dealer.

But, it is NOT always this simple. Oftentimes, the market quotes are not only dealer quotes but also include limit orders from customers. So, sometimes the above example would give you a false indication.

Let's look at another example:

\$1.00 \$1.15

A trade is executed at \$1.15. On the surface, this appears like a buy order. But let's dig deeper and inspect more information by looking at the quote before, at the time of and after the trade.
Right Before Trade \$1.00 \$2.00
Time of Trade \$1.00 \$1.15
Right After Trade \$1.00 \$2.00

The first quote was bid \$1 and ask \$2. But then it appears that a customer put a limit order to sell at \$1.15. This changed the quote. Afterwards, the dealer, or somebody else, saw the opportunity to scoop up the limit order and bought the option at \$1.15. Subsequently, the new quote (immediately after the trade) went back to bid \$1 and ask \$2. In this case, it is more likely that the customer put a limit sell order and the dealer filled the order (also referred to as price improvement). Therefore, we would not say that a customer bought the option contract at \$1.15 as in the previous example.

## How does MarketChameleon.com detect if an option is bought or sold?

As you can see from the examples above, there isn't a way to determine if an option was bought or sold with 100% accuracy. Nobody can do that. Note: if the system cannot estimate with a high degree of certainty if the trade was a customer buy or sell, it will tag that trade as undetermined and will not influence the sentiment inference. However, with the benefit of an automated interpretation algorithm, using several various relevant data points, we can get very close. The MarketChameleon.com algorithm uses the following:

• Proprietary Rules
• Various Benchmarks
• Statistics
• Past Knowledge and Experience of Trading as Dealers
• Tick by Tick Data Analysis
• Stock Price Movement
• Surrounding Options Markets
• Implied Volatility