You are previewing High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems.
O'Reilly logo
High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems

Book Description

A hands-on guide to the fast and ever-changing world of high-frequency, algorithmic trading

Financial markets are undergoing rapid innovation due to the continuing proliferation of computer power and algorithms. These developments have created a new investment discipline called high-frequency trading.

This book covers all aspects of high-frequency trading, from the business case and formulation of ideas through the development of trading systems to application of capital and subsequent performance evaluation. It also includes numerous quantitative trading strategies, with market microstructure, event arbitrage, and deviations arbitrage discussed in great detail.

  • Contains the tools and techniques needed for building a high-frequency trading system

  • Details the post-trade analysis process, including key performance benchmarks and trade quality evaluation

  • Written by well-known industry professional Irene Aldridge

Interest in high-frequency trading has exploded over the past year. This book has what you need to gain a better understanding of how it works and what it takes to apply this approach to your trading endeavors.

Table of Contents

  1. Copyright
  2. Acknowledgments
  3. 1. Introduction
  4. 2. Evolution of High-Frequency Trading
    1. 2.1. FINANCIAL MARKETS AND TECHNOLOGICAL INNOVATION
    2. 2.2. EVOLUTION OF TRADING METHODOLOGY
  5. 3. Overview of the Business of High-Frequency Trading
    1. 3.1. COMPARISON WITH TRADITIONAL APPROACHES TO TRADING
      1. 3.1.1. Technical, Fundamental, or Quant?
      2. 3.1.2. Algorithmic, Systematic, Electronic, or Low-Latency?
    2. 3.2. MARKET PARTICIPANTS
      1. 3.2.1. Competitors
      2. 3.2.2. Investors
      3. 3.2.3. Services and Technology Providers
        1. 3.2.3.1. Electronic Execution
        2. 3.2.3.2. Custody and Clearing
        3. 3.2.3.3. Software
        4. 3.2.3.4. Legal, Accounting, and Other Professional Services
      4. 3.2.4. Government
    3. 3.3. OPERATING MODEL
      1. 3.3.1. Overview
      2. 3.3.2. Model Development
      3. 3.3.3. System Implementation
      4. 3.3.4. Trading Platform
      5. 3.3.5. Risk Management
    4. 3.4. ECONOMICS
      1. 3.4.1. Revenue Driven by Leverage and the Sharpe Ratio
      2. 3.4.2. Transparent and Latent Costs
      3. 3.4.3. Staffing
    5. 3.5. CAPITALIZING A HIGH-FREQUENCY TRADING BUSINESS
    6. 3.6. CONCLUSION
  6. 4. Financial Markets Suitable for High-Frequency Trading
    1. 4.1. FINANCIAL MARKETS AND THEIR SUITABILITY FOR HIGH-FREQUENCY TRADING
      1. 4.1.1. Fixed-Income Markets
        1. 4.1.1.1. Interest Rate Markets
        2. 4.1.1.2. Bond Markets
      2. 4.1.2. Foreign Exchange Markets
      3. 4.1.3. Equity Markets
      4. 4.1.4. Commodity Markets
    2. 4.2. CONCLUSION
  7. 5. Evaluating Performance of High-Frequency Strategies
    1. 5.1. BASIC RETURN CHARACTERISTICS
    2. 5.2. COMPARATIVE RATIOS
    3. 5.3. PERFORMANCE ATTRIBUTION
    4. 5.4. OTHER CONSIDERATIONS IN STRATEGY EVALUATION
      1. 5.4.1. Strategy Capacity
      2. 5.4.2. Length of the Evaluation Period for High-Frequency Strategies
    5. 5.5. CONCLUSION
  8. 6. Orders, Traders, and Their Applicability to High-Frequency Trading
    1. 6.1. ORDER TYPES
      1. 6.1.1. Order Price Specifications
        1. 6.1.1.1. Market Orders versus Limit Orders
        2. 6.1.1.2. Profitability of Limit Orders
        3. 6.1.1.3. Delays in Limit Order Execution
        4. 6.1.1.4. Limit Orders and Bid-Ask Spreads
        5. 6.1.1.5. Limit Orders and Market Volatility
      2. 6.1.2. Order Timing Specifications
      3. 6.1.3. Order Size Specifications
      4. 6.1.4. Order Disclosure Specifications
      5. 6.1.5. Stop-Loss and Take-Profit Orders
      6. 6.1.6. Administrative Orders
    2. 6.2. ORDER DISTRIBUTIONS
    3. 6.3. CONCLUSION
  9. 7. Market Inefficiency and Profit Opportunities at Different Frequencies
    1. 7.1. PREDICTABILITY OF PRICE MOVES AT HIGH FREQUENCIES
      1. 7.1.1. Predictability and Market Efficiency
      2. 7.1.2. Testing for Market Efficiency and Predictability
        1. 7.1.2.1. Non-Parametric Runs Test
        2. 7.1.2.2. Tests of Random Walks
        3. 7.1.2.3. Autoregression-Based Tests
        4. 7.1.2.4. Market Efficiency Tests Based on the Martingale Hypothesis
        5. 7.1.2.5. Cointegration-Based Tests of Market Efficiency
    2. 7.2. CONCLUSION
  10. 8. Searching for High-Frequency Trading Opportunities
    1. 8.1. STATISTICAL PROPERTIES OF RETURNS
    2. 8.2. LINEAR ECONOMETRIC MODELS
      1. 8.2.1. Stationarity
      2. 8.2.2. Autoregressive (AR) Estimation
      3. 8.2.3. Moving Average (MA) Estimation
      4. 8.2.4. Autoregressive Moving Average (ARMA)
      5. 8.2.5. Cointegration
    3. 8.3. VOLATILITY MODELING
    4. 8.4. NONLINEAR MODELS
      1. 8.4.1. Overview
      2. 8.4.2. Taylor Series Expansion (Bilinear Models)
      3. 8.4.3. Threshold Autoregressive (TAR) Models
      4. 8.4.4. Markov Switching Models
      5. 8.4.5. Nonparametric Estimation of Nonlinear Models
      6. 8.4.6. Neural Networks
    5. 8.5. CONCLUSION
  11. 9. Working with Tick Data
    1. 9.1. PROPERTIES OF TICK DATA
    2. 9.2. QUANTITY AND QUALITY OF TICK DATA
    3. 9.3. BID-ASK SPREADS
    4. 9.4. BID-ASK BOUNCE
    5. 9.5. MODELING ARRIVALS OF TICK DATA
    6. 9.6. APPLYING TRADITIONAL ECONOMETRIC TECHNIQUES TO TICK DATA
    7. 9.7. CONCLUSION
  12. 10. Trading on Market Microstructure: Inventory Models
    1. 10.1. OVERVIEW OF INVENTORY TRADING STRATEGIES
    2. 10.2. ORDERS, TRADERS, AND LIQUIDITY
      1. 10.2.1. Orders Used in Microstructure Trading
      2. 10.2.2. Trader Types in Market Microstructure Trading
      3. 10.2.3. Liquidity Provision
    3. 10.3. PROFITABLE MARKET MAKING
    4. 10.4. DIRECTIONAL LIQUIDITY PROVISION
      1. 10.4.1. When the Limit Order Book Is Observable
      2. 10.4.2. When the Limit Order Book Is Not Observable
    5. 10.5. CONCLUSION
  13. 11. Trading on Market Microstructure: Information Models
    1. 11.1. MEASURES OF ASYMMETRIC INFORMATION
      1. 11.1.1. Quoted Bid-Ask Spread
      2. 11.1.2. Effective Bid-Ask Spread
      3. 11.1.3. Information-Based Impact
      4. 11.1.4. Adverse Selection Components of the Bid-Ask Spread
      5. 11.1.5. Probability of Informed Trading
    2. 11.2. INFORMATION-BASED TRADING MODELS
      1. 11.2.1. Trading on Information Contained in Bid-Ask Spreads
      2. 11.2.2. Trading on Order Aggressiveness
      3. 11.2.3. Trading on Order Flow
        1. 11.2.3.1. Order Flow Overview
        2. 11.2.3.2. Order Flow Is Directly Observable
        3. 11.2.3.3. Order Flow Is Not Directly Observable
        4. 11.2.3.4. Autocorrelation of Order Flows
    3. 11.3. CONCLUSION
  14. 12. Event Arbitrage
    1. 12.1. DEVELOPING EVENT ARBITRAGE TRADING STRATEGIES
    2. 12.2. WHAT CONSTITUTES AN EVENT?
    3. 12.3. FORECASTING METHODOLOGIES
      1. 12.3.1. Directional Forecasts
        1. 12.3.1.1. Example: Trading USD/CAD on U.S. Inflation Announcements
      2. 12.3.2. Point Forecasts
    4. 12.4. TRADABLE NEWS
      1. 12.4.1. Corporate News
      2. 12.4.2. Industry News
      3. 12.4.3. Macroeconomic News
    5. 12.5. APPLICATION OF EVENT ARBITRAGE
      1. 12.5.1. Foreign Exchange Markets
      2. 12.5.2. Equity Markets
      3. 12.5.3. Fixed-Income Markets
      4. 12.5.4. Futures Markets
      5. 12.5.5. Emerging Economies
      6. 12.5.6. Commodity Markets
      7. 12.5.7. Real Estate Investment Trusts (REITS)
    6. 12.6. CONCLUSION
  15. 13. Statistical Arbitrage in High-Frequency Settings
    1. 13.1. MATHEMATICAL FOUNDATIONS
    2. 13.2. PRACTICAL APPLICATIONS OF STATISTICAL ARBITRAGE
      1. 13.2.1. General Considerations
      2. 13.2.2. Foreign Exchange
        1. 13.2.2.1. Triangular Arbitrage
        2. 13.2.2.2. Uncovered Interest Parity Arbitrage
      3. 13.2.3. Equities
        1. 13.2.3.1. Arbitraging Different Equity Classes of the Same Issuer
        2. 13.2.3.2. Market-Neutral Arbitrage
        3. 13.2.3.3. Liquidity Arbitrage
        4. 13.2.3.4. Large-to-Small Information Spillovers
      4. 13.2.4. Futures
        1. 13.2.4.1. Basis Trading
        2. 13.2.4.2. Futures/Equity Arbitrage
      5. 13.2.5. Indexes and ETFs
      6. 13.2.6. Options
    3. 13.3. CONCLUSION
  16. 14. Creating and Managing Portfolios of High-Frequency Strategies
    1. 14.1. ANALYTICAL FOUNDATIONS OF PORTFOLIO OPTIMIZATION
      1. 14.1.1. Graphical Representation of the Portfolio Optimization Problem
      2. 14.1.2. Core Portfolio Optimization Framework
      3. 14.1.3. Portfolio Optimization in the Presence of Transaction Costs
      4. 14.1.4. Portfolio Diversification with Asymmetric Correlations
      5. 14.1.5. Dealing with Estimation Errors in Portfolio Optimization
    2. 14.2. EFFECTIVE PORTFOLIO MANAGEMENT PRACTICES
      1. 14.2.1. How Much Leverage Is Appropriate within the Portfolio?
      2. 14.2.2. What Proportion of the Portfolio Should Be Invested into Which Trading Strategy?
    3. 14.3. CONCLUSION
  17. 15. Back-Testing Trading Models
    1. 15.1. EVALUATING POINT FORECASTS
    2. 15.2. EVALUATING DIRECTIONAL FORECASTS
      1. 15.2.1. Determination of Model-Driven Trade Signals
      2. 15.2.2. Ex-Ante Identification of Successful and Unsuccessful Trades in the Historical Data
      3. 15.2.3. Computation of Marginal Probabilities
      4. 15.2.4. Accuracy Curves
    3. 15.3. CONCLUSION
  18. 16. Implementing High-Frequency Trading Systems
    1. 16.1. MODEL DEVELOPMENT LIFE CYCLE
    2. 16.2. SYSTEM IMPLEMENTATION
      1. 16.2.1. Key Steps in Implementation of High-Frequency Systems
      2. 16.2.2. Common Pitfalls in Systems Implementation
        1. 16.2.2.1. Time Distortion
        2. 16.2.2.2. Speed of Execution
    3. 16.3. TESTING TRADING SYSTEMS
      1. 16.3.1. Data Set Testing
      2. 16.3.2. Unit Testing
      3. 16.3.3. Integration Testing
      4. 16.3.4. System Testing
      5. 16.3.5. Use Case Testing
    4. 16.4. CONCLUSION
  19. 17. Risk Management
    1. 17.1. DETERMINING RISK MANAGEMENT GOALS
    2. 17.2. MEASURING RISK
      1. 17.2.1. Measuring Market Risk
      2. 17.2.2. Measuring Credit and Counterparty Risk
      3. 17.2.3. Measuring Liquidity Risk
      4. 17.2.4. Measuring Operational Risk
      5. 17.2.5. Measuring Legal Risk
    3. 17.3. MANAGING RISK
      1. 17.3.1. Stop Losses
      2. 17.3.2. Hedging Portfolio Exposure
    4. 17.4. CONCLUSION
  20. 18. Executing and Monitoring High-Frequency Trading
    1. 18.1. EXECUTING HIGH-FREQUENCY TRADING SYSTEMS
      1. 18.1.1. Overview of Execution Algorithms
      2. 18.1.2. Market-Aggressiveness Selection
      3. 18.1.3. Price-Scaling Strategies
      4. 18.1.4. Slicing Large Orders
    2. 18.2. MONITORING HIGH-FREQUENCY EXECUTION
      1. 18.2.1. Pre-Trade Analysis
      2. 18.2.2. Monitoring Run-Time Performance
    3. 18.3. CONCLUSION
  21. 19. Post-Trade Profitability Analysis
    1. 19.1. POST-TRADE COST ANALYSIS
      1. 19.1.1. Transparent Execution Costs
        1. 19.1.1.1. Broker Commissions
        2. 19.1.1.2. Exchange Fees
        3. 19.1.1.3. Taxes
      2. 19.1.2. Latent Execution Costs
        1. 19.1.2.1. Bid-Ask Spreads
        2. 19.1.2.2. Investment Delay Costs
        3. 19.1.2.3. Price Appreciation Costs
        4. 19.1.2.4. Market Impact Costs
        5. 19.1.2.5. Timing Risk Costs
        6. 19.1.2.6. Opportunity Costs
      3. 19.1.3. Cost Variance Analysis
      4. 19.1.4. Cost Analysis Summary
    2. 19.2. POST-TRADE PERFORMANCE ANALYSIS
      1. 19.2.1. Efficient Trading Frontier
      2. 19.2.2. Benchmarked Analysis
      3. 19.2.3. Relative Performance Measurement
      4. 19.2.4. Implementation Shortfall
      5. 19.2.5. Performance Analysis Summary
    3. 19.3. CONCLUSION
  22. References
  23. About the Web Site
    1. 19.4. WHAT YOU WILL FIND ON THE WEB SITE
  24. About the Author