We propose a class of execution algorithms that consists of a strategic layer and a speculative layer. The strategic layer is an optimal trading schedule that encodes the trader's objective, her tolerance to risk, and the impact of her own trades in the market. The schedule of the strategic...

Automated market makers (AMMs) are a new type of trading venue where the rules for liquidity provision and liquidity taking are considerably different from those of the traditional electronic trading venues. AMMs have become one of the key markets to trade crypto-currencies, whose liquidity is...

We use high-frequency data from the Nasdaq exchange to build a measure of volume imbalance in the limit order book (LOB). We show that our measure is a good predictor of the sign of the next market order (MO), i.e. buy or sell, and also helps to predict price changes immediately after the...

We derive closed-form strategies for a broker who provides liquidity to an informed trader and to a noise trader over a finite-time and infinite-time trading horizon. The flow of the noise trader is uninformative and the broker trades with the noise trader at a profit, on average. On the other...

We propose a price impact model where changes in prices are purely driven by the order flow in the market. The stochastic price impact of market orders and the arrival rates of limit and market orders are functions of the market liquidity process which reflects the balance of the demand and...

We show how a market maker employs information about the momentum in the price of the asset (i.e., alpha signal) to make decisions in her liquidity provision strategy in an order driven electronic market. The momentum in the midprice of the asset depends on the execution of liquidity taking...