2015Lecture notes in business information processingOpen access

Quantitative Research in High Frequency Trading for Natural Gas Futures Market

Saulius Masteika, Mantas Vaitonis

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Abstract

High frequency trading (HFT) in micro or milliseconds has recently drawn attention of financial researches and engineers. In nowadays algorithmic trading and HFT account for a dominant part of overall trading volume. The main objective of this research is to test statistical arbitrage strategy in HFT natural gas futures market. The arbitrage strategy attempts to profit by exploiting price differences between successive futures contracts of the same underlying asset. It takes long/short positions when the spread between the contracts widens; hoping that the prices will converge back in the near future. In this study high frequency bid/ask and last trade records were collected from NYMEX exchange. The strategy was back tested applying MatLab software of technical computing. Statistical arbitrage and HFT has given positive results and refuted the efficient market hypothesis. The strategy can be interesting to financial engineers, market microstructure developers or market participants implementing high frequency trading strategies.

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What this paper is about

High frequency trading (HFT) in micro or milliseconds has recently drawn attention of financial researches and engineers. In nowadays algorithmic trading and HFT account for a dominant part of overall trading volume. The main objective of this research is to test statistical arbitrage strategy in HFT natural gas futures market. The arbitrage strategy attempts to profit by exploiting price differences between successive futures contracts of the same underlying asset. It takes long/short positions when the spread between the contracts widens; hoping that the prices will converge back in the near future. In this study high frequency bid/ask and last trade records were collected from NYMEX exchange. The strategy was back tested applying MatLab software of technical computing. Statistical arbitrage and HFT has given positive results and refuted the efficient market hypothesis. The strategy can be interesting to financial engineers, market microstructure developers or market participants implementing high frequency trading strategies.

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Available abstract

High frequency trading (HFT) in micro or milliseconds has recently drawn attention of financial researches and engineers. In nowadays algorithmic trading and HFT account for a dominant part of overall trading volume. The main objective of this research is to test statistical arbitrage strategy in HFT natural gas futures market. The arbitrage strategy attempts to profit by exploiting price differences between successive futures contracts of the same underlying asset. It takes long/short positions when the spread between the contracts widens; hoping that the prices will converge back in the near future. In this study high frequency bid/ask and last trade records were collected from NYMEX exchange. The strategy was back tested applying MatLab software of technical computing. Statistical arbitrage and HFT has given positive results and refuted the efficient market hypothesis. The strategy can be interesting to financial engineers, market microstructure developers or market participants implementing high frequency trading strategies.

Key concepts: High-frequency trading, Statistical arbitrage, Futures contract, Algorithmic trading, Trading strategy, Pairs trade, Arbitrage, Financial economics

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