We present a framework for optimal execution in presence of stochastic volatility. The theoretical model utilizes the fair pricing theory of market impact and the Heston model for volatility. We use computer optimization to solve common trading problems, including optimal execution schedules on...

We investigate how the dynamics of supply and demand affect the relationship between aggregated order flow and returns/market impact. We classify order flow according to the different event types that comprise it: Limit orders, cancelations and market orders executed against displayed or hidden...

We develop a theory for the market impact of large trading orders, which we call metaorders because they are typically split into small pieces and executed incrementally. Market impact is empirically observed to be a concave function of metaorder size, i.e. the impact per share of large...

Starting from basic hypotheses on how footprints from hidden orders are interpreted by short-term traders, we derive a fair price model that predicts market impact for non-uniform participation rate schedules. We use this model to derive an optimal execution schedule for a risk-averse trader....

We examine information, market impact and trade sizes using a data-set of institutional trades where approximately 1/4 of the orders are labeled as having been created for cash flow purposes. We find that during the execution the functional form and scale of market impact are similar for cash...

Using publicly-available market data we construct a three component order flow imbalance vector that represents executions against displayed quotes, executions against dark liquidity and the net imbalance in the flow of limit orders. The main accomplishment of this paper is to provide empirical...