HFT (high-frequency trading) has emerged as a powerful force in modern financial markets. Only 20 years ago, most of the trading volume occurred in exchanges such as the New York Stock Exchange, where humans dressed in brightly colored outfits would gesticulate and scream their trading intentions. Nowadays, trading occurs mostly in electronic servers in data centers, where computers communicate their trading intentions through network messages. This transition from physical exchanges to electronic platforms has been particularly profitable for HFT firms, which invested heavily in the infrastructure of this new environment.
We formulate a trade execution problem at the market microstructure level and solve it using dynamic programming. The objective is to sell a single lot of an as- set in a short time horizon T, using the imbalance of the top of book bid and ask sizes as a price predictor. (download the full article here)
order book dynamics
The limit order book keeps track of the buy and sell orders in a market. In this paper with Rama Cont and Rishi Talreja, we used data from the Tokyo stock exchange and built a market simulation (download article here)
The role of a dealer in securities markets is to provide liquidity on the exchange by quoting bid and ask prices at which he is willing to buy and sell a specific quantity of assets. Traditionally, this role has been filled by marketmaker or specialist firms. In recent years, with the growth of electronic exchanges such as Nasdaq’s Inet, anyone willing to submit limit orders in the system can effectively play the role of a dealer. Indeed, the availability of high frequency data on the limit order book ensures a fair playing field where various agents can post limit orders at the prices they choose. In this paper, we study the optimal submission strategies of bid and ask orders in such a limit order book.