In recent years, global major exchanges such as the NYSE, LSE, and TSE have faced an unprecedented amount of a specific type of trading known as high frequency trading (HFT). Although researchers and practitioners have not agreed on the precise definition of HFT, the Securities and Exchange Commission (SEC) loosely defines it as “a trading that uses high-speed computer systems to monitor market data and submit a large number of orders to the market.” HFT began in the late 1990s, and its proportion of total trading volume has rapidly increased during the past decade. In 2009, a rough estimation (by TABB group) indicated that HFT accounted for 60% and 30% of the total trading volumes in the US and European equity markets, respectively. To accommodate and process surging HFT-related orders, exchange-level projects to expand order processing capacity and reduce trade execution time are under way among a number of global exchanges, including the Korea Stock Exchange. On March 23, 2009, the Korea Exchange migrated to the EXTURE (‘EXchange + fuTURE'), an upgraded trade settlement system. The launch of this technically advanced trading system might enable investors to implement HFT in the Korean stock market. However, as far as the authors know, little is known about HFT in the Korean stock market. In this study, we find a special type of HFT has emerged as a conspicuous market phenomenon characterized by the extremely fast repetition of order submissions and cancellations. It closely resembles the ‘strategic runs' observed on the NASDAQ (Hasbrouck and Saar (2013)). The strategic runs discovered in the Korean stock market consist of a chain of normal orders and its cancellation within a certain period of no more than one second between each consecutive order. We further examine the effect that strategic runs have on market quality in terms of short-term liquidity and volatility, measured in intraday ten-second intervals. To measure liquidity, we use proportional spread and the number of shares at the best bid, or ask prices divided by total number of shares outstanding. The highest price minus the lowest price divided by the bid-ask midpoint is used to calculate volatility. During the 10-second intervals when strategic runs are most concentrated, they attract liquidity by submitting higher proportions of marketable limit orders. This leads to increased spreads, decreased depth, and higher volatility. Furthermore, 10-second interval intraday vector auto regression (VAR) results indicate that strategic runs deteriorate market quality by decreasing market depth and raising volatility. We do not, however, find a statistically significant relationship between strategic runs and spreads. Overall, strategic runs appear to have negative effects on market quality. Our results must be interpreted with caution. Because the sample period of VAR analysis is as short as three months, one cannot make sure whether our main results still hold for the post sample period. Another problem is that strategic run is only a special type of high frequency trading. It implies that we cannot generalize our results based on strategic runs for other types of high frequency trading that we do not know yet. We hope these issues will be examined in the future research. While major exchanges are making considerable capital investments into IT infrastructure and network system recently to accommodate and attract high frequency trading, it is unclear what the socioeconomic benefit of the investment is and who makes profits (or suffers losses) in high frequency trading. As high frequency trading is increasingly dominant in the stock market, individual investors who cannot access stock market as fast as high frequency traders will leave the market, and this may lead to reduction in liquidity and eventually market failure. This paper contributes to the finance literature and the government's policymaking as follows. First, this study is the first to not only verify that strategic runs exist in the Korean stock market, but also to examine their characteristics and effect on market quality. Second, this study finds strategic runs without incurring errors thanks to the use of account-level trades and quotes data. In contrast, the data used by Hasbrouck and Saar (2013) are subject to inherent limitation, as they do not include account level information. For example, they cannot identify whether two consecutive orders are submitted by the same trader, which makes it difficult to extract strategic runs from quote data. Our study is free from such problems because the data used enable us to identify which traders submit which orders. Finally, given that HFT is in the early stages in the Korean stock market, our results might provide useful information for financial authorities regarding whether they will need to regulate HFT in the Korean stock market.