High Frequency Trading

High-frequency trading has been taking Wall Street by storm, and for a good reason: its immense profitability. According to Alpha magazine, the highest earning investment manager of 2008 was Jim Simons of Renaissance Technologies Corp., a long-standing proponent of high-frequency strategies. Dr. Simons reportedly earned $2.5 billion in 2008 alone. While no institution was thoroughly tracking performance of highfrequency funds when this book was written, colloquial evidence suggests that the majority of high-frequency managers delivered positive returns in 2008, whereas 70 percent of low-frequency practitioners lost money, according to the New York Times. The profitability of high-frequency enterprises is further corroborated by the exponential growth of the industry. According to a February 2009 report from Aite Group, high-frequency trading now accounts for over 60 percent of trading volume coming through the financial exchanges. High-frequency trading professionals are increasingly in demand and reap top-dollar compensation. Even in the worst months of the 2008 crisis, 50 percent of all open positions in finance involved expertise in high-frequency trading (Aldridge, 2008). Despite the demand for information on this topic, little has been published to help investors understand and implement high-frequency trading systems.

So what is high-frequency trading, and what is its allure? The main innovation that separates high-frequency from low-frequency trading is a high turnover of capital in rapid computer-driven responses to changing market conditions. High-frequency trading strategies are characterized by a higher number of trades and a lower average gain per trade. Many traditional money managers hold their trading positions for weeks or even months, generating a few percentage points in return per trade. By comparison, high-frequency money managers execute multiple trades each day, gaining a fraction of a percent return per trade, with few, if any, positions carried overnight. The absence of overnight positions is important to investors and portfolio managers for three reasons:

1. The continuing globalization of capital markets extends most of the trading activity to 24-hour cycles, and with the current volatility in the markets, overnight positions can become particularly risky. Highfrequency strategies do away with overnight risk.

2. High-frequency strategies allow for full transparency of account holdings and eliminate the need for capital lock-ups.

3. Overnight positions taken out on margin have to be paid for at the interest rate referred to as an overnight carry rate. The overnight carry rate is typically slightly above LIBOR. With volatility in LIBOR and hyperinflation around the corner, however, overnight positions can become increasingly expensive and therefore unprofitable for many money managers. High-frequency strategies avoid the overnight carry, creating considerable savings for investors in tight lending conditions and in high-interest environments. High-frequency trading has additional advantages.

High-frequency strategies have little or no correlation with traditional long-term buy and hold strategies, making high-frequency strategies valuable diversification tools for long-term portfolios. High-frequency strategies also require shorter evaluation periods because of their statistical properties, which are discussed in depth further along in this book. If an average monthly strategy requires six months to two years of observation to establish the strategy’s credibility, the performance of many high-frequency strategies can be statistically ascertained within a month. In addition to the investment benefits already listed, high-frequency trading provides operational savings and numerous benefits to society. From the operational perspective, the automated nature of high-frequency trading delivers savings through reduced staff headcount as well as a lower incidence of errors due to human hesitation and emotion. Among the top societal benefits of high-frequency strategies are the following:
Increased market efficiency
Added liquidity
Innovation in computer technology Stabilization of market systems.

Evolution of High-Frequency Trading

Financial Markets and Technological Innovation

Evolution of Trading Methodology

Overview of the Business of High-Frequency Trading

Comparison with Traditional Approaches to Trading

Market Participants

Operating Model

Economics

Capitalizing a High-Frequency Trading Business

Financial Markets Suitable for High-Frequency Trading 

Financial Markets and Their Suitability for High-Frequency Trading

Evaluating Performance of High-Frequency Strategies

Basic Return Characteristics 

Comparative Ratios

Performance Attribution

Other Considerations in Strategy Evaluation

Orders, Traders, and Their Applicability to High-Frequency Trading

Order Types

Order Distributions

Market Inefficiency and Profit Opportunities at Different Frequencies 

Predictability of Price Moves at High Frequencies

Searching for High-Frequency Trading Opportunities 

Statistical Properties of Returns

Linear Econometric Models

Volatility Modeling

Nonlinear Models

Working with Tick Data 

Properties of Tick Data

Quantity and Quality of Tick Data

Bid-Ask Spreads

Bid-Ask Bounce

Modeling Arrivals of Tick Data

Applying Traditional Econometric Techniques to Tick Data

Trading on Market Microstructure: Inventory Models 

Overview of Inventory Trading Strategies 

Orders, Traders, and Liquidity

Profitable Market Making

Directional Liquidity Provision

Trading on Market Microstructure: Information Models 

Measures of Asymmetric Information

Information-Based Trading Models

Event Arbitrage

Developing Event Arbitrage Trading Strategies

What Constitutes an Event?

Forecasting Methodologies

Tradable News

Application of Event Arbitrage

Statistical Arbitrage in High-Frequency Settings 

Mathematical Foundations

Practical Applications of Statistical Arbitrage

Creating and Managing Portfolios of High-Frequency Strategies

Analytical Foundations of Portfolio Optimization

Effective Portfolio Management Practices

Back-Testing Trading Models

Evaluating Point Forecasts

Evaluating Directional Forecasts

Implementing High-Frequency Trading Systems

Model Development Life Cycle

System Implementation

Testing Trading Systems

Risk Management

Determining Risk Management Goals

Measuring Risk

Managing Risk

Executing and Monitoring High-Frequency Trading 

Executing High-Frequency Trading Systems

Monitoring High-Frequency Execution

Post-Trade Profitability Analysis 

Post-Trade Cost Analysis

Post-Trade Performance Analysis