Working with High-Frequency Data
Abstract: High-frequency trading (HFT) has exploded into the popular press as a major development affecting securities markets around the world. Unlike more established trading approaches that examine daily data and tactically rebalance portfolios every month or quarter, HFT parses trade-by-trade data at the highest speeds available. This typically implies that high-frequency traders monitor every tick of many securities concurrently and make their portfolio allocation decisions at lightning speeds with ultra-short investment horizons in mind. In fact, hedge fund managers consider strategies to be high frequency when their holding periods range from microseconds to several hours, without any positions held overnight. To process reams of data and make informed and rational decisions at such high speeds would be difficult even for the most accomplished traders. Thankfully, computer technology has evolved to become robust and inexpensive enough to aid any willing portfolio manager to take up the high-frequency craft.
This entry examines high-frequency data, the particularities and opportunities they bring, and compares these data with their low-frequency counterparts, wherever appropriate. High-frequency trading (HFT) strategies by their nature use a different population of data, and the traditional methods of data analysis need to be adjusted accordingly. Specifically, this entry examines the ...
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