Algorithmic trading strategies

Robert L Kissell, Fordham University


This dissertation presents the necessary techniques and framework to enable investors to make appropriate algorithmic trading decisions given the trading goals and investment objectives of the fund. These techniques can utilized by financial institutions, banks, hedge funds, sell-side broker-dealers, and corporations to improve implementation execution decisions, reduce trading costs, manage trading risk, and increase portfolio returns. The dissertation will introduce necessary mathematical models (namely, market impact and timing risk) to evaluate and compare alternative execution strategies, determine appropriate algorithms and algorithmic parameters, and construct more efficient portfolios. A multi-period trade schedule optimization technique is presented to determine "optimal" execution strategies for baskets of stocks in an amount of time that can be useful for investors (namely, minutes compared to hours or more). The dissertation aims to provide transparency and structure to a currently undisciplined field. This dissertation provides several key contributions to finance. They are: a market impact modeling technique, an efficient multi-period trade schedule optimization formulation, a real-time risk management technique, and an algorithmic decision-making framework. It also provides insight into improving portfolio performance through proper treatment of market impact and trading risk in the portfolio construction phase of the investment cycle.

Subject Area


Recommended Citation

Kissell, Robert L, "Algorithmic trading strategies" (2006). ETD Collection for Fordham University. AAI3216918.