The Science of Algorithmic Trading and Portfolio Management

We provide a discussion of the current state of the market and advanced modeling techniques

for trading algorithms, stock selection, and portfolio construction.

This reference book will provide readers with:

An understanding of the new electronic trading environment.

An understanding of transaction cost analysis (TCA) and proper metrics for cost measurement

and performance evaluation.

A thorough understanding of the different types of trading algorithms: liquidity seeking,

dark pools, arrival price, implementation shortfall (IS), volume weighted average price

(VWAP), arrival price, and portfolio implementation shortfall.

Proven market impact modeling techniques.

An understanding of algorithmic trading across various asset classes: equities, futures,

fixed income, foreign exchange, and commodities.

Advanced algorithmic forecasting techniques to estimate daily liquidity and monthly volumes.

An algorithmic decision making framework to ensure consistency between investment

and trading objectives.

A best execution process.

Readers will subsequently be prepared to:

Develop real-time trading algorithms customized to specific institutional needs.

Design systems to manage algorithmic risk and dark pool uncertainty.

Evaluate market impact models and assess performance across algorithms, traders, and

brokers.

Implement electronic trading systems.

For the first time, portfolio managers are not forgotten and will be provided with proven

techniques to better construct portfolios through:

Stock Selection

Portfolio Optimization

Asset Allocation

MI Factor Scores