The Science of Algorithmic Trading and Portfolio Management, with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind. Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems.
This valuable book summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. Readers learn the underlying details and mathematics of customized trading algorithms, as well as advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects.
- Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers.
- Helps readers design systems to manage algorithmic risk and dark pool uncertainty.
- Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives.
Students and professors studying stock selection and portfolio management, as well as traders, practitioners, and portfolio managers working in the financial industry..
Chapter 1. Algorithmic Trading
Changing Trading Environment
Recent Growth in Algorithmic Trading
Classifications of Algorithms
Types of Algorithms
Algorithmic Trading Trends
Trading Venue Classification
Types of Orders
The Trading Floor
Algorithmic Trading Decisions
Algorithmic Analysis Tools
High Frequency Trading
Direct Market Access
Chapter 2. Market Microstructure
Market Microstructure Literature
The New Market Structure
New NYSE Trading Model
NASDAQ Select Market Maker Program
Chapter 3. Algorithmic Transaction Cost Analysis
Unbundled Transaction Cost Components
Transaction Cost Classification
Transaction Cost Categorization
Transaction Cost Analysis
Final Note on Post-Trade Analysis
Chapter 4. Market Impact Models
Graphical Illustrations of Market Impact
Developing a Market Impact Model
Derivation of Models
I-Star Market Impact Model
Parameter Estimation Techniques
Chapter 5. Estimating I-Star Model Parameters
Chapter 6. Price Volatility
Market Observations—Empirical Findings
Forecasting Stock Volatility
HMA-VIX Adjustment Model
Measuring Model Performance
- No. of pages:
- © Academic Press 2014
- 1st July 2013
- Academic Press
- eBook ISBN:
- Hardcover ISBN:
Robert Kissell is an Executive Director responsible for analytics product initiatives within UBS Direct Execution and UBS Portfolio Trading. Prior to joining UBS, he was with JP Morgan where he served as Head of Quantitative Trading Strategies.
Executive Director, analytics product initiatives, UBS Direct Execution and UBS Portfolio Trading
"Kissell... introduces the mathematical models for constructing, calibrating, and testing market impact models that calculate the change in stock price caused by a large trade or order, and presents an advanced portfolio optimization process that incorporates market impact and transaction costs directly into portfolio optimization."--ProtoView.com, March 2014
"This book provides excellent coverage of the challenges faced by portfolio managers and traders in implementing investment ideas and the advanced modeling techniques to address these challenges."--Kumar Venkataraman, Southern Methodist University