The Science of Algorithmic Trading and Portfolio Management
By- Robert Kissell, Executive Director for analytics product intitiatives within UBS Direct Execution and UBS Portfolio Trading
Its emphasis on algorithmic trading processes and current trading models sets this book apart from others. As the first author to discuss algorithmic trading across the various asset classes, Robert Kissell provides key insights into ways to develop, test, and build trading algorithms. He summarizes market structure, the formation of prices, and how different participants interact with one another, including bluffing, speculating, and gambling. He shows readers the underlying details and mathematics required to develop, build, and test customized algorithms, providing them with advanced modeling techniques to improve profitability through algorithmic trading and appropriate risk management techniques. The accompanying website includes examples, data sets underlying exercises in the book, and large projects. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, as well as acquiring the ability to implement electronic trading systems.
Audience
Students and professors studying stock selection and portfolio management, as well as traders, practitioners, and portfolio managers working in the financial industry..
Hardbound, 256 Pages
Published: July 2013
Imprint: Academic Press
ISBN: 978-0-12-401689-7
Contents
- Part I - Introduction
- Algorithmic Trading
- What is algorithmic trading?
- Types of algorithms
- Single Stock vs. Portfolio Algorithms, P&L Trading
- Algorithmic Trading Preferences
- Data requirements
- Market Microstructure
- New Trading Environment / Different Exchanges
- NYSE Listed vs. Nasdaq OTC Stocks
- Displayed Venues vs. Dark Pools
- Intraday Trading Patterns
- Maker Taker Pricing & Liquidity Rebates
- May 2010 Flash-Crash
- Transaction Cost Analysis (TCA)
- Unbundled Transaction Cost Components
- Pre-Trade Analysis
- Intra-Day Trading
- Post Trade Measurement
- Execution Consulting Services
- Market Impact
- Definition
- Economic Description
- Random Walk with Market Impact
- I-Star Cost Allocation
- Underlying Dataset
- Estimating Parameters & Testing the Model
- Forecasting Market Impact
- Simulation of parameters - show how hard it is to fit a model
- Examples
- Multi-Asset Class Market Impact
- Equities
- Futures & ETFs
- Fixed Income
- Commodities
- FX Rates
- Price Volatility & Factor Models
- Volatility Models
- ARCH, GARCH, EWMA
- Factor Models
- Time Series
- Fundamental Factors
- Principal Component Analysis
- Algorithmic Trading Risk
- Price Risk
- Liquidity Risk
- Order Book & Limit Order Models
- Dark Pools
- Parameter Standard Errors
- Risk Simulation Example
- Algorithmic Decision Making Framework
- Macro, Micro, Order Placement Strategies
- Dark Pools, Limit Order Model, Smart Order Router
- Real-Time Adaptation Tactics
- Efficient Trading Frontier
- Portfolio Algorithms
- Formulating the Problems for a Basket
- Solution Speed & Techniques
- Constraints
- Real-Time Updatiing
- Mean Variance Optimization
- Unifying Investing and Trading
- Optimization with Market Impact
- Back-Testing approaches
- Stock Selection
- Maximum Capacity of a Strategy
- Liquidation of a Position
- Index Events and Corporate Actions
- Statistical Arbitrage
- Pairs Trading & Cointegration
- High Frequency Trading
- Liquidity Trading
- Market Making
- Rebates
- Advanced Topics

