Options Market Making
Humans versus Computers
A $3,116,900 Profit in Minutes
When I began my trading career on the floor of the Chicago Board of Options Exchange (CBOE) in 1999 as a market maker, it was my job to make markets for small retail investors, large hedge funds and banks. For example, if a broker came into my trading crowd asking for a market on JPMorgan (JPM) calls, I would give a price that the investor could buy and sell the calls for.
Let’s say a broker from Goldman Sachs came into my crowd looking for a market on JPM January 65 Calls. I would do some quick math and then come up with a price I thought the calls were worth. In this case, let’s say I thought the calls were worth $2. I would then tell the Goldman Sachs broker that my market was $1 bid and offered at $3. That meant I was willing to buy the calls for $1, and sell them for $3.
Theoretically, if my math was right, I had $1 of “edge” when I bought or sold this call. If I did it often enough through the course of the day, more times than not, I accumulated a nice profit.
However, at some point in the mid-2000s, things changed in the market-making world. More and more computers were making markets, and I was no longer competing against humans in the pit, but against computers. The markets began to tighten, and that $1 “edge” I had was down to a $0.05 edge.
To compete for “market share,” I also began to make electronic markets. However, I soon learned the hard way that I couldn’t compete with the top hedge funds in the race to have the fastest technology. Too often I would sell hundreds of calls milliseconds before a stock ripped higher, costing me thousands of dollars. Because of this, I left the trading floor and now trade with a retail brokerage account like most people.
Last Friday, there was a perfect example of why I left the trading floor, and how computers have taken over the trading world.
On Friday at 1:10:15 pm, a trader on multiple exchanges bought 570 Humana (HUM) May 180 Calls (exp. 5/29) for $0.25. The calls were expiring in less than three hours. This was a capital outlay of $14,250. At the time of the trade, HUM common stock was trading at 177.20, and trader would need HUM to rally $3.05 before the close of trade that very day to break even on his call purchase.
At the exact same second as the first purchase, a trader on multiple exchanges also bought 470 HUM May 177.50 Calls (exp. 5/29) for $0.55. These calls were also expiring in less than three hours. This was a capital outlay of $25,850. This trader would need HUM to rally $0.85 before the close of trade that very day to break even on his call purchase.
Within seconds of these weekly options purchases, news broke that Humana was considering a sale of the company. Within minutes, the stock was trading as high as 217.57, or higher by $40.37.
The May 180 Calls (exp. 5/29) were now worth $29.00—a profit of $28.75 per call, or a total net profit of $1,638,750 on the 570 calls purchased seconds before the news broke.
The May 177.5 Calls (exp. 5/29) were now worth $32.00—a profit of $31.45 per call, or a total net profit of $1,478,150 on the 470 calls purchased seconds before the news broke.
I can say with a fairly high level of confidence this wasn’t a case of insider trading. Instead it was a case of an algorithm being able to read a news story faster than the rest of us, and buying approximately 1,000 calls to get ahead of the rest of the trading community.
The computer system turned an “investment” of $40,100, into a profit of $3,116,900, or 7,773%, in minutes.
Trying to compete with the computers these days is a battle that cannot be won. The market moves too fast minute to minute, and day to day. Many options traders try to trade short dated options looking for a quick pop in a hot biotech or technology stock.
This strategy cannot work over time. At Cabot Options Trader, and Cabot Options Trader Pro, the positions we put on are positions that we will likely hold for days, weeks or even months. That way we don’t get beat by the computers in a race for profits.
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