Bids, Asks, Trades, and Quotes

If you search Google for the price of Apple stock, you get a nice single number like $262.77. But at the same time, you've probably heard that there are millions and millions of shares traded every single day. How is it that stock prices can be so succinctly reported?

Well… the reality is a lot more complicated. Stock markets work off what are called “bids” and “asks.” These are just fancy terms for what is basically a negotiation process between a buyer and a seller.

Going back to our LEGO set example, you were willing to sell your lego set for $1,000. So your ask price for the LEGO set was $1000. If a buyer came up to you and offered you $950, that would be his bid price. There's a $50 gap between what someone is willing to pay, and what you're willing to sell at. That is called the bid-ask spread.

So you both talk it out and negotiate, and after a while you both agree to settle on $975. The lego set exchanges hands, and that would constitute a trade. The number of lego sets that were traded is called the volume, and in this case the volume is only 1.

In the stock market, ask price and bid price are typically represented as quotes, and there is a size associated with a quote. The size in a quote represents the number of shares of a stock, so an ask size of 10 means someone is looking to sell 10 shares of that stock.

That's basically what happens in the stock market, just digitally, hundreds of millions of times every day. Most websites, like Google, report the last trade price, typically often delayed by a few seconds, minutes, or even up to 15-minutes on some websites. Some websites report the midpoint of the bid-ask price, though that can be problematic for stocks with low volume, since the bid-ask spread might be large.

What also complicates the prices of stocks is the fact that there are multiple stock exchanges. The NASDAQ stock exchange, for example, is one of the largest exchanges that offers proprietary data feeds for a fee. IEX is another smaller exchange, which also has its own data about the last trade price of a stock.

To most accurately see the price of a stock, you would need a consolidated trade data feed, which takes data from all of the different exchanges into consideration. Because these consolidated trade feeds are often very expensive (and probably unnecessary for a regular trader), some websites might only use data from the IEX exchange, which will charge a smaller fee for their trade data.

Most stock graphs, like the ones seen on Google or this website, aggregates the trade data of a stock and creates a graph from it. Candle graphs, like the one shown below, represent OHLC data (open, high, low, close). These graphs group trade data by the hour, minute, day, week, etc.

Open: The opening trade price for the given time window High: The highest trade price for the given time window Low: The lowest trade price for the given time window Close: The last trade price for the given time window

Like stocks, options contracts also work with this barter-system of bids and asks. Options quotes represent the number of contracts someone is willing to buy or sell, as opposed to the number of shares of stock.

Our Optimal Calculation Strategy

The front page of this website shows the best options trades, sometimes with staggering gains. We use options quote data to calculate the optimal trades. Why?

Because trade data only represents options trade that actually happened in the real world. The problem with this approach is that sometimes options don't have high trade volume. Smaller stocks that don't get as much attention as Apple, Google, Microsoft, etc, get less options trade volume throughout the trading day.

Our website tries to answer the question of “what was the best options trade I could have made?” If we looked only at trade data, we would miss out on trades that could have happened but didn't. Ask quotes represent the highest price someone was willing to sell an option at, and bid quotes represent the lowest price someone was willing to buy a stock at. By using quote data, and calculating buying and selling off the bid/ask quotes, we are considering all hypothetical trades that could have happened to accurately answer our question.

In the first section, we talked about OHLC data for stocks / options. Most options data providers, including ours, provide options OHLC data as part of their offering. Almost no data provider provides OHLC data for quotes (which, arguably, doesn't even make sense).

On the frontpage of our website, our optimal trades (which were calculated using quote data) link out to options details pages which show a graph of OHLC data. Because quote data is hypothetical and trade data is reality, there can sometimes be a discrepancy in the buy time/price of our theoretical trade and the buy time/price of the practical trade data.

What compounds this issue is that for options with a wide bid-ask price, the actual trade data can be a lot more favorable than what our optimal calculator can do. For example, if the bid price of an option is 0.50, and the ask price is 1.00, then the midpoint is 0.75. It's entirely possible that sellers and buyers agree to that 0.75 price, and a trade is recorded at that price.

Our optimal calculator can't actually use the midpoint because across the data in the market, there are wildly optimistic sellers. It's not uncommon to see a bid price of 0.01 and an ask price of 10.00, when realistically the price should be 0.05. If our optimal calculator used the midpoint of 5.00, we'd end up reporting back horribly inaccurate trades (trust us, we know from painstaking experience).

The end result of all of this is that in reality, looking at the trade data, you will often see trades that are actually better than what our optimal calculator reports. Our optimal calculator reports back the best trades given the worst possible fills, meaning we always pay the highest anyone is asking for a contract, and always sell at the lowest anyone is buying the contract for. The reality is somewhere in-between.