A guide to the high-frequency trading strategy in options

high-frequency trading

High-frequency trading is a type of algorithmic trading characterized by high turnover and high order-to-trade ratios. It typically employs concise time horizons, holding securities for seconds or less. Because this definition requires holding periods of mere seconds, most transactions are done out of necessity on electronic communication networks (ECNs) using models implemented by specialized computer programs.

There are many types of strategies used in high-frequency trading. These include statistical arbitrage, market making, scalping, illuminated market arbitrage (IMA), latency arbitrage, and super predatory. All these strategies attempt to capture ultrafast profits at the expense of investors who do not have the resources to implement them. This article will discuss some of the strategies that HFTs use in combination with options.

You can use high-frequency trading on various financial instruments, but one of the most popular markets is the derivatives market. The derivative market has many advantages for high-frequency strategies, and it also offers numerous opportunities to implement them.

HFTs trade options because they can make money from relatively small price changes due to liquidity rebates from exchanges which encourage order flow. In addition, options have different prices depending on volatility, allowing traders to speculate or hedge their directional view on an underlying instrument by shorting put or calls. This article will focus exclusively on options contracts and how they are traded in high-frequency regimes.

Types of strategies

There are three main types of strategies that high-frequency traders use when trading options:

  • Hourly/Daily Statistical Arbitrage
  • Market-Making Strategies for Options
  • Super Predatory Strategies in options

Statistical Arbitrage

Harris and Raviv (1994) described the statistical arbitrage strategy in detail. This strategy consists of statically taking advantage of the mispricing of asset pairs once they are detected, without any reference to information or events related to the cash market underlying these assets. Using this approach, HFTs can make money by offering markets at exchanges price improvement, providing liquidity at a better price than other competitors. The overall idea is that HFTs must get prices better than the other market participants since they are one of the market makers.

HFTs need to detect mispricings in the options markets to implement this type of strategy successfully. Once detected, they must quickly determine what assets should be traded and at which exchanges they should be traded. It requires large databases with quotes from many different sources to spot price discrepancies quickly.

Types of statistical arbitrage strategies

  • calendar spreads
  • inter-market spreads
  • intra-market pairs trading

The first strategy is based on intraday statistical price differences between an options contract and another contract that belongs to the same underlying security. Still, it has a different maturity date—for instance, the price difference between the September 2020 and December 2021 options of security.

The second strategy consists of taking advantage of temporary deviations between different assets from the same issuer, which is not traded in conjunction. The term for this is inter-market arbitrage. For instance, a trader who has an online quote for Microsoft stock might notice a difference in the price of Microsoft’s options versus its options or another exchange where it trades on a different day., but they should eventually converge because HFTs will adjust their prices to be more attractive than others to attract buyers and sellers.

The third strategy is when traders look for mispricings within two similar contracts that belong to different series. They finance their positions by selling options that are close to expiration while simultaneously purchasing further out-of-the-money options. Today, these strategies are widely used due to the rise in computing power and trade execution costs. Their traders have benefited from reducing latency by using co-location services near an exchange’s matching engine.

Market-making strategies

The second type of high-frequency trading strategy is market-making strategies. These strategies consist of placing limit buy or sell orders whose purpose is to capture prices deviations that occur during short periods. To successfully implement this algorithm, HFTs monitor order books continuously, but they do not need cancellation privileges for their orders because any other delayed market participant can perform this function. If you’re eager to continue learning, read more here.