# How High-frequency Trading Works?

High-frequency trading (HFT) involves making use of sophisticated software tools to trade in various securities such as stocks and options.

Such trading is generally characterized by following certain trading strategies, holding positions for less than one day, and frequent trading that could go up as much as thousands of times in a day.

High frequency traders target opportunities that are very small such as expected returns of 0.2 cps before costs. These opportunities are practically nonexistent for long-term investors because of the higher cost structure. Normal retail investors pay a brokerage fee of approx. 5 cps while long-term institutional investors pay a brokerage of 1 cps and above.

HFTs don't employ a lot of capital, and don't use much leverage, so they really can't lose much capital.

The high frequency traders are very interested in small returns because throughout the day there are a plenty of such opportunities, and HFTs use their highly quantitative algorithmic approach to make hundreds of thousands of such trades that adds up in the day and in the long run.

High-frequency trading opportunities need use of advanced technology and quants that can help traders to identify and pursue these strategies in a very short period of time. Since many people are competing, such opportunities exist for a very short period of time.

An important characteristic is low latency. Solid algorithms and the minimum latency network infrastructure helps ensure that the trader can collect the liquidity-rebate that markets pay to ensure a highly liquid environment. As costs decrease, more opportunities become tradeable, leading to higher volumes and further reducing costs.

Some of the trading strategies used by HFTs include:

Pair Trading: This involves taking advantage of the price differential between two stocks that have a historical correlation and the prices have deviated from this correlation. The idea is that the prices will revert to their historical trend.

Volume-Weighted Average Price (VWAP): VWAP is the ratio of value traded to total volume traded over a given time horizon, usually a day. VWAP strategies involve executing large orders at a better average price. There are many VWAP strategies such as Guaranteed principal VWAP bid, Forward VWAP cross, etc.

Time-Weighted Average Price (TWAP): This refers to the average price of a security over a given time horizon. This allows a trader to time-slice a trade over a certain period of time. Traders use TWAP for buying and selling large blocks of shares without affecting its price.

Percentage of Volume (POV): These strategies involve defining the percentage of volume, trading intervals, and price in order to trade large blocks of stock without affecting its price.

Iceberg: In Iceberging, large orders are broken down into several smaller orders and entered into the market over time. The success of such a strategy is measured by the average purchase price. One algorithm designed to find hidden orders or icebergs is called "Stealth".

Sniffers: Sniffers are algorithms that find out other algorithms and use this information to trade and make profit.

Flash Orders: According to traders magazine, a flash order is a marketable order sent to a market center that is not quoting the industry's best price or that cannot fill that order in its entirety. The order is then flashed to recipients of the venue's proprietary data feed to see if any of those firms wants to take the other side of the order. This practice enables the market center to try to keep the trade. High frequency trading systems see these flash orders and acts on this information. These flash orders are displayed for just 500ms.

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