This paper examines the role of high-frequency trading (HFT) in price discovery and price efficiency. Using transaction-level data from NASDAQ, the authors find that HFTs facilitate price efficiency by trading in the direction of permanent price changes and in the opposite direction of transitory pricing errors, both on average and on the most volatile days. This is done through their liquidity demanding orders. In contrast, HFTs' liquidity supplying orders are adversely selected. The direction of buying and selling by HFTs predicts price changes over short horizons measured in seconds. The direction of HFTs' trading is correlated with public information, such as macro news announcements, market-wide price movements, and limit order book imbalances. The study uses a state space model to decompose price movements into permanent and temporary components and to relate changes in both to HFTs. The permanent component is interpreted as information, while the transitory component is pricing errors or noise. HFTs appear to reduce the risk associated with transitory price movements by trading against them. The state space model incorporates the interrelated concepts of price discovery (how information is impounded into prices) and price efficiency (the informativeness of prices). The authors find that HFTs' trading is correlated with public information, such as macro news announcements, market-wide price movements, and limit order book imbalances. The results suggest that HFTs provide a useful service to markets by reducing the noise component of prices and acquiring and trading on different types of information, making prices more efficient. The paper also discusses the implications of these findings for policymakers considering measures to curb HFT. The authors conclude that HFTs play a beneficial role in price efficiency and that their activities are consistent with theoretical models of informed trading. The study highlights the importance of HFTs in the price discovery process and their role in improving market efficiency.This paper examines the role of high-frequency trading (HFT) in price discovery and price efficiency. Using transaction-level data from NASDAQ, the authors find that HFTs facilitate price efficiency by trading in the direction of permanent price changes and in the opposite direction of transitory pricing errors, both on average and on the most volatile days. This is done through their liquidity demanding orders. In contrast, HFTs' liquidity supplying orders are adversely selected. The direction of buying and selling by HFTs predicts price changes over short horizons measured in seconds. The direction of HFTs' trading is correlated with public information, such as macro news announcements, market-wide price movements, and limit order book imbalances. The study uses a state space model to decompose price movements into permanent and temporary components and to relate changes in both to HFTs. The permanent component is interpreted as information, while the transitory component is pricing errors or noise. HFTs appear to reduce the risk associated with transitory price movements by trading against them. The state space model incorporates the interrelated concepts of price discovery (how information is impounded into prices) and price efficiency (the informativeness of prices). The authors find that HFTs' trading is correlated with public information, such as macro news announcements, market-wide price movements, and limit order book imbalances. The results suggest that HFTs provide a useful service to markets by reducing the noise component of prices and acquiring and trading on different types of information, making prices more efficient. The paper also discusses the implications of these findings for policymakers considering measures to curb HFT. The authors conclude that HFTs play a beneficial role in price efficiency and that their activities are consistent with theoretical models of informed trading. The study highlights the importance of HFTs in the price discovery process and their role in improving market efficiency.