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.

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.

1;Front Cover;12;The Science of Algorithmic Trading and Portfolio Management;43;Copyright Page;54;Contents;85;Preface;166;Acknowledgments;187;1 Algorithmic Trading;207.1;Introduction;207.1.1;Advantages;227.1.2;Disadvantages;237.2;Changing Trading Environment;247.3;Recent Growth in Algorithmic Trading;307.4;Investment Cycle;347.5;Classifications of Algorithms;357.6;Types of Algorithms;367.7;Algorithmic Trading Trends;397.8;Trading Venue Classification;407.8.1;Displayed Market;407.8.2;Dark Pool;407.8.3;Grey Pool;407.8.4;Dark Pool Controversies;417.9;Types of Orders;427.10;Execution Options;427.11;The Trading Floor;447.11.1;Research Function;457.11.2;Sales Function;467.12;Algorithmic Trading Decisions;487.12.1;Macro-Level Strategies;487.12.1.1;Step 1-Choose Implementation Benchmark;497.12.1.2;Step 2-Select Optimal Execution Strategy;497.12.1.3;Step 3-Specify Adaptation Tactic;517.12.2;Micro-Level Decisions;527.12.2.1;Limit Order Models;537.12.2.2;Smart Order Routers;547.13;Algorithmic Analysis Tools;567.13.1;Pre-Trade Analysis;567.13.2;Intraday Analysis;567.13.3;Post-Trade Analysis;577.13.4;Rule-Based Trading;577.13.5;Quantitative Techniques;577.14;High Frequency Trading;587.14.1;Auto Market Making;587.14.2;Quantitative Trading/Statistical Arbitrage;607.14.3;Rebate/Liquidity Trading;607.15;Direct Market Access;627.15.1;Advantages;637.15.2;Disadvantages;638;2 Market Microstructure;668.1;Introduction;668.2;Market Microstructure Literature;688.3;The New Market Structure;708.4;Pricing Models;758.5;Order Priority;768.6;Equity Exchanges;768.7;New NYSE Trading Model;768.7.1;Designated Market Makers;778.7.2;Supplemental Liquidity Providers;788.7.3;Trading Floor Brokers;798.8;NASDAQ Select Market Maker Program;798.9;Empirical Evidence;808.9.1;Trading Volumes;808.9.1.1;Market Share;808.9.1.2;Large and Small Cap Trading;818.9.1.3;Do Stocks Trade Differently Across the Exchanges and Venues?;828.9.2;Volume Distribution Statistics;828.9.3;Day of Week Effect;848.9.4;Intraday Trading Profiles;868.9.4.1;Spreads;868.9.4.2;Volumes;878.9.4.3;Volatility;898.9.4.3.1;Intraday Trading Stability-Coefficient of Variation;918.9.5;Special Event Days;928.10;Flash Crash;958.10.1;Empirical Evidence from the Flash Crash;988.10.2;What Should Regulators do to SafeGuard Investors from Potential Future Flash Crashes?;1028.10.3;Comparison with Previous Crashes;1038.11;Conclusion;1049;3 Algorithmic Transaction Cost Analysis;1069.1;Introduction;1069.1.1;What Are Transaction Costs?;1079.1.2;What Is Best Execution?;1079.1.3;What Is the Goal of Implementation?;1089.2;Unbundled Transaction Cost Components;1089.2.1;1. Commission;1089.2.2;2. Fees;1089.2.3;3. Taxes;1089.2.4;4. Rebates;1099.2.5;5. Spreads;1099.2.6;6. Delay Cost;1109.2.7;7. Price Appreciation;1109.2.8;8. Market Impact;1109.2.9;9. Timing Risk;1119.2.10;10. Opportunity Cost;1119.3;Transaction Cost Classification;1119.4;Transaction Cost Categorization;1139.5;Transaction Cost Analysis;1139.5.1;Measuring/Forecasting;1159.5.2;Cost versus Profit and Loss;1169.6;Implementation Shortfall;1169.6.1;Complete Execution;1189.6.2;Opportunity Cost (Andre Perold);1199.6.3;Expanded Implementation Shortfall (Wayne Wagner);1209.6.3.1;Implementation Shortfall Formulation;1239.6.3.1.1;Trading Cost/Arrival Cost;1239.7;Evaluating Performance;1249.7.1;Trading Price Performance;1249.7.2;Benchmark Price Performance;1259.7.3;VWAP Benchmark;1259.7.4;Participation Weighted Price (PWP) Benchmark;1279.7.5;Relative Performance Measure (RPM);1289.7.6;Pre-Trade Benchmark;1299.7.7;Index Adjusted Performance Metric;1309.7.8;Z-Score Evaluation Metric;1319.7.9;Market Cost Adjusted Z-Score;1329.7.10;Adaptation Tactic;1339.8;Comparing Algorithms;1349.8.1;Non-Parametric Tests;1359.8.1.1;Paired Samples;1369.8.1.2;Sign Test;1369.8.1.3;Wilcoxon Signed Rank Test;1379.8.1.4;Independent Samples;1399.8.1.4.1;Mann-Whitney U Test;1399.8.1.4