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High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems

Name: High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems
Author: Irene Aldridge
ISBN: 9780470563762

by Irene Aldridge

December 2009

Intermediate to advanced

352 pages

8h 47m

English

Wiley

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Copyright
Acknowledgments
1. Introduction
2. Evolution of High-Frequency Trading
2.1. FINANCIAL MARKETS AND TECHNOLOGICAL INNOVATION2.2. EVOLUTION OF TRADING METHODOLOGY
3. Overview of the Business of High-Frequency Trading
3.1. COMPARISON WITH TRADITIONAL APPROACHES TO TRADING3.1.1. Technical, Fundamental, or Quant?3.1.2. Algorithmic, Systematic, Electronic, or Low-Latency?3.2. MARKET PARTICIPANTS3.2.1. Competitors3.2.2. Investors3.2.3. Services and Technology Providers3.2.3.1. Electronic Execution3.2.3.2. Custody and Clearing3.2.3.3. Software3.2.3.4. Legal, Accounting, and Other Professional Services3.2.4. Government3.3. OPERATING MODEL3.3.1. Overview3.3.2. Model Development3.3.3. System Implementation3.3.4. Trading Platform3.3.5. Risk Management3.4. ECONOMICS3.4.1. Revenue Driven by Leverage and the Sharpe Ratio3.4.2. Transparent and Latent Costs3.4.3. Staffing3.5. CAPITALIZING A HIGH-FREQUENCY TRADING BUSINESS3.6. CONCLUSION
4. Financial Markets Suitable for High-Frequency Trading
4.1. FINANCIAL MARKETS AND THEIR SUITABILITY FOR HIGH-FREQUENCY TRADING4.1.1. Fixed-Income Markets4.1.1.1. Interest Rate Markets4.1.1.2. Bond Markets4.1.2. Foreign Exchange Markets4.1.3. Equity Markets4.1.4. Commodity Markets4.2. CONCLUSION
5. Evaluating Performance of High-Frequency Strategies
5.1. BASIC RETURN CHARACTERISTICS5.2. COMPARATIVE RATIOS5.3. PERFORMANCE ATTRIBUTION5.4. OTHER CONSIDERATIONS IN STRATEGY EVALUATION5.4.1. Strategy Capacity5.4.2. Length of the Evaluation Period for High-Frequency Strategies5.5. CONCLUSION
6. Orders, Traders, and Their Applicability to High-Frequency Trading
6.1. ORDER TYPES6.1.1. Order Price Specifications6.1.1.1. Market Orders versus Limit Orders6.1.1.2. Profitability of Limit Orders6.1.1.3. Delays in Limit Order Execution6.1.1.4. Limit Orders and Bid-Ask Spreads6.1.1.5. Limit Orders and Market Volatility6.1.2. Order Timing Specifications6.1.3. Order Size Specifications6.1.4. Order Disclosure Specifications6.1.5. Stop-Loss and Take-Profit Orders6.1.6. Administrative Orders6.2. ORDER DISTRIBUTIONS6.3. CONCLUSION
7. Market Inefficiency and Profit Opportunities at Different Frequencies
7.1. PREDICTABILITY OF PRICE MOVES AT HIGH FREQUENCIES7.1.1. Predictability and Market Efficiency7.1.2. Testing for Market Efficiency and Predictability7.1.2.1. Non-Parametric Runs Test7.1.2.2. Tests of Random Walks7.1.2.3. Autoregression-Based Tests7.1.2.4. Market Efficiency Tests Based on the Martingale Hypothesis7.1.2.5. Cointegration-Based Tests of Market Efficiency7.2. CONCLUSION
8. Searching for High-Frequency Trading Opportunities
8.1. STATISTICAL PROPERTIES OF RETURNS8.2. LINEAR ECONOMETRIC MODELS8.2.1. Stationarity8.2.2. Autoregressive (AR) Estimation8.2.3. Moving Average (MA) Estimation8.2.4. Autoregressive Moving Average (ARMA)8.2.5. Cointegration8.3. VOLATILITY MODELING8.4. NONLINEAR MODELS8.4.1. Overview8.4.2. Taylor Series Expansion (Bilinear Models)8.4.3. Threshold Autoregressive (TAR) Models8.4.4. Markov Switching Models8.4.5. Nonparametric Estimation of Nonlinear Models8.4.6. Neural Networks8.5. CONCLUSION

9. Working with Tick Data
9.1. PROPERTIES OF TICK DATA9.2. QUANTITY AND QUALITY OF TICK DATA9.3. BID-ASK SPREADS9.4. BID-ASK BOUNCE9.5. MODELING ARRIVALS OF TICK DATA9.6. APPLYING TRADITIONAL ECONOMETRIC TECHNIQUES TO TICK DATA9.7. CONCLUSION
10. Trading on Market Microstructure: Inventory Models
10.1. OVERVIEW OF INVENTORY TRADING STRATEGIES10.2. ORDERS, TRADERS, AND LIQUIDITY10.2.1. Orders Used in Microstructure Trading10.2.2. Trader Types in Market Microstructure Trading10.2.3. Liquidity Provision10.3. PROFITABLE MARKET MAKING10.4. DIRECTIONAL LIQUIDITY PROVISION10.4.1. When the Limit Order Book Is Observable10.4.2. When the Limit Order Book Is Not Observable10.5. CONCLUSION
11. Trading on Market Microstructure: Information Models
11.1. MEASURES OF ASYMMETRIC INFORMATION11.1.1. Quoted Bid-Ask Spread11.1.2. Effective Bid-Ask Spread11.1.3. Information-Based Impact11.1.4. Adverse Selection Components of the Bid-Ask Spread11.1.5. Probability of Informed Trading11.2. INFORMATION-BASED TRADING MODELS11.2.1. Trading on Information Contained in Bid-Ask Spreads11.2.2. Trading on Order Aggressiveness11.2.3. Trading on Order Flow11.2.3.1. Order Flow Overview11.2.3.2. Order Flow Is Directly Observable11.2.3.3. Order Flow Is Not Directly Observable11.2.3.4. Autocorrelation of Order Flows11.3. CONCLUSION
12. Event Arbitrage
12.1. DEVELOPING EVENT ARBITRAGE TRADING STRATEGIES12.2. WHAT CONSTITUTES AN EVENT?12.3. FORECASTING METHODOLOGIES12.3.1. Directional Forecasts12.3.1.1. Example: Trading USD/CAD on U.S. Inflation Announcements12.3.2. Point Forecasts12.4. TRADABLE NEWS12.4.1. Corporate News12.4.2. Industry News12.4.3. Macroeconomic News12.5. APPLICATION OF EVENT ARBITRAGE12.5.1. Foreign Exchange Markets12.5.2. Equity Markets12.5.3. Fixed-Income Markets12.5.4. Futures Markets12.5.5. Emerging Economies12.5.6. Commodity Markets12.5.7. Real Estate Investment Trusts (REITS)12.6. CONCLUSION
13. Statistical Arbitrage in High-Frequency Settings
13.1. MATHEMATICAL FOUNDATIONS13.2. PRACTICAL APPLICATIONS OF STATISTICAL ARBITRAGE13.2.1. General Considerations13.2.2. Foreign Exchange13.2.2.1. Triangular Arbitrage13.2.2.2. Uncovered Interest Parity Arbitrage13.2.3. Equities13.2.3.1. Arbitraging Different Equity Classes of the Same Issuer13.2.3.2. Market-Neutral Arbitrage13.2.3.3. Liquidity Arbitrage13.2.3.4. Large-to-Small Information Spillovers13.2.4. Futures13.2.4.1. Basis Trading13.2.4.2. Futures/Equity Arbitrage13.2.5. Indexes and ETFs13.2.6. Options13.3. CONCLUSION
14. Creating and Managing Portfolios of High-Frequency Strategies
14.1. ANALYTICAL FOUNDATIONS OF PORTFOLIO OPTIMIZATION14.1.1. Graphical Representation of the Portfolio Optimization Problem14.1.2. Core Portfolio Optimization Framework14.1.3. Portfolio Optimization in the Presence of Transaction Costs14.1.4. Portfolio Diversification with Asymmetric Correlations14.1.5. Dealing with Estimation Errors in Portfolio Optimization14.2. EFFECTIVE PORTFOLIO MANAGEMENT PRACTICES14.2.1. How Much Leverage Is Appropriate within the Portfolio?14.2.2. What Proportion of the Portfolio Should Be Invested into Which Trading Strategy?14.3. CONCLUSION
15. Back-Testing Trading Models
15.1. EVALUATING POINT FORECASTS15.2. EVALUATING DIRECTIONAL FORECASTS15.2.1. Determination of Model-Driven Trade Signals15.2.2. Ex-Ante Identification of Successful and Unsuccessful Trades in the Historical Data15.2.3. Computation of Marginal Probabilities15.2.4. Accuracy Curves15.3. CONCLUSION
16. Implementing High-Frequency Trading Systems
16.1. MODEL DEVELOPMENT LIFE CYCLE16.2. SYSTEM IMPLEMENTATION16.2.1. Key Steps in Implementation of High-Frequency Systems16.2.2. Common Pitfalls in Systems Implementation16.2.2.1. Time Distortion16.2.2.2. Speed of Execution16.3. TESTING TRADING SYSTEMS16.3.1. Data Set Testing16.3.2. Unit Testing16.3.3. Integration Testing16.3.4. System Testing16.3.5. Use Case Testing16.4. CONCLUSION
17. Risk Management
17.1. DETERMINING RISK MANAGEMENT GOALS17.2. MEASURING RISK17.2.1. Measuring Market Risk17.2.2. Measuring Credit and Counterparty Risk17.2.3. Measuring Liquidity Risk17.2.4. Measuring Operational Risk17.2.5. Measuring Legal Risk17.3. MANAGING RISK17.3.1. Stop Losses17.3.2. Hedging Portfolio Exposure17.4. CONCLUSION
18. Executing and Monitoring High-Frequency Trading
18.1. EXECUTING HIGH-FREQUENCY TRADING SYSTEMS18.1.1. Overview of Execution Algorithms18.1.2. Market-Aggressiveness Selection18.1.3. Price-Scaling Strategies18.1.4. Slicing Large Orders18.2. MONITORING HIGH-FREQUENCY EXECUTION18.2.1. Pre-Trade Analysis18.2.2. Monitoring Run-Time Performance18.3. CONCLUSION
19. Post-Trade Profitability Analysis
19.1. POST-TRADE COST ANALYSIS19.1.1. Transparent Execution Costs19.1.1.1. Broker Commissions19.1.1.2. Exchange Fees19.1.1.3. Taxes19.1.2. Latent Execution Costs19.1.2.1. Bid-Ask Spreads19.1.2.2. Investment Delay Costs19.1.2.3. Price Appreciation Costs19.1.2.4. Market Impact Costs19.1.2.5. Timing Risk Costs19.1.2.6. Opportunity Costs19.1.3. Cost Variance Analysis19.1.4. Cost Analysis Summary19.2. POST-TRADE PERFORMANCE ANALYSIS19.2.1. Efficient Trading Frontier19.2.2. Benchmarked Analysis19.2.3. Relative Performance Measurement19.2.4. Implementation Shortfall19.2.5. Performance Analysis Summary19.3. CONCLUSION
References
About the Web Site
19.4. WHAT YOU WILL FIND ON THE WEB SITE
About the Author

Overview

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.

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Algorithmic Trading: Winning Strategies and Their Rationale

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