We analyze the impact of high frequency trading in financial markets based on a model with three types of traders: liquidity traders, market makers, and high frequency traders.Our four main findings are: i) The price impact of the liquidity trades is higher in the presence of the high frequency trader and is increasing with the size of the trade. In particular, we show that the high frequency trader reduces (increases) the prices that liquidity traders receive when selling (buying) their equity holdings. ii) Although market makers also lose revenue to the high frequency trader in every trade, they are compensated for these losses by a higher liquidity discount. iii) High frequency trading increases the volatility of prices. iv) The volume of trades doubles as the high frequency trader intermediates all trades between the liquidity traders and market makers. This additional volume is a consequence of trades which are carefully tailored for surplus extraction and are neither driven by fundamentals nor is it noise trading. In equilibrium, high frequency trading and traditional market making coexist as competition drives down the profits for new high frequency traders while the presence of high frequency traders does not drive out traditional market makers. * We would like to thank Harrison Hong for his valuable comments and discussions. We are also grateful to Andrés Almazán, Gene Amromin, Michael Brennan, Pete Kyle and Eduardo Schwartz for their comments.We also thank seminar participants at CEMFI. The usual caveat applies. We welcome comments, including references we have inadvertently missed. The views expressed in this paper are those of the authors and do not necessarily reflect those of the Banco de España.† alvaro.cartea@uc3m.es, Universidad Carlos III de Madrid. ‡ jpenalva@emp.uc3m.es, Universidad Carlos III de Madrid and Banco de España.

We analyze the impact of high frequency trading in financial markets based on a model with three types of traders: liquidity traders, market makers, and high frequency traders.Our four main findings are: i) The price impact of the liquidity trades is higher in the presence of the high frequency trader and is increasing with the size of the trade. In particular, we show that the high frequency trader reduces (increases) the prices that liquidity traders receive when selling (buying) their equity holdings. ii) Although market makers also lose revenue to the high frequency trader in every trade, they are compensated for these losses by a higher liquidity discount. iii) High frequency trading increases the volatility of prices. iv) The volume of trades doubles as the high frequency trader intermediates all trades between the liquidity traders and market makers. This additional volume is a consequence of trades which are carefully tailored for surplus extraction and are neither driven by fundamentals nor is it noise trading. In equilibrium, high frequency trading and traditional market making coexist as competition drives down the profits for new high frequency traders while the presence of high frequency traders does not drive out traditional market makers. * We would like to thank Harrison Hong for his valuable comments and discussions. We are also grateful to Andrés Almazán, Gene Amromin, Michael Brennan, Pete Kyle and Eduardo Schwartz for their comments.We also thank seminar participants at CEMFI. The usual caveat applies. We welcome comments, including references we have inadvertently missed. The views expressed in this paper are those of the authors and do not necessarily reflect those of the Banco de España.† alvaro.cartea@uc3m.es, Universidad Carlos III de Madrid. ‡ jpenalva@emp.uc3m.es, Universidad Carlos III de Madrid and Banco de España.

This paper studies the relationship between the auctioneer's provision of information and the level of competition in private value auctions. We use a general notion of informativeness which allows us to compare the efficient with the (privately) optimal amount of information provided by the auctioneer. We show that in the private value setting more information increases the efficiency of the allocation while it also increases informational rents so that it is not optimal for the auctioneer to provide the efficient level of information. We also show that as the number of participants in the auction increases both the efficient and the optimal level of information increase and both converge when the number of bidders goes to infinity.

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We analyze the impact of high frequency trading in financial markets based on a model with three types of traders: liquidity traders, market makers, and high frequency traders.Our four main findings are: i) The price impact of the liquidity trades is higher in the presence of the high frequency trader and is increasing with the size of the trade. In particular, we show that the high frequency trader reduces (increases) the prices that liquidity traders receive when selling (buying) their equity holdings. ii) Although market makers also lose revenue to the high frequency trader in every trade, they are compensated for these losses by a higher liquidity discount. iii) High frequency trading increases the volatility of prices. iv) The volume of trades doubles as the high frequency trader intermediates all trades between the liquidity traders and market makers. This additional volume is a consequence of trades which are carefully tailored for surplus extraction and are neither driven by fundamentals nor is it noise trading. In equilibrium, high frequency trading and traditional market making coexist as competition drives down the profits for new high frequency traders while the presence of high frequency traders does not drive out traditional market makers. * We would like to thank Harrison Hong for his valuable comments and discussions. We are also grateful to Andrés Almazán, Gene Amromin, Michael Brennan, Pete Kyle and Eduardo Schwartz for their comments.We also thank seminar participants at CEMFI. The usual caveat applies. We welcome comments, including references we have inadvertently missed. The views expressed in this paper are those of the authors and do not necessarily reflect those of the Banco de España.† alvaro.cartea@uc3m.es, Universidad Carlos III de Madrid. ‡ jpenalva@emp.uc3m.es, Universidad Carlos III de Madrid and Banco de España.