Science of Algorithmic Trading and Portfolio Management -  Robert Kissell

Science of Algorithmic Trading and Portfolio Management (eBook)

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2013 | 1. Auflage
496 Seiten
Elsevier Science (Verlag)
978-0-12-401693-4 (ISBN)
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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.

    Front Cover 1
    The Science of Algorithmic Trading and Portfolio Management 4
    Copyright Page 5
    Contents 8
    Preface 16
    Acknowledgments 18
    1 Algorithmic Trading 20
    Introduction 20
    Advantages 22
    Disadvantages 23
    Changing Trading Environment 24
    Recent Growth in Algorithmic Trading 30
    Investment Cycle 34
    Classifications of Algorithms 35
    Types of Algorithms 36
    Algorithmic Trading Trends 39
    Trading Venue Classification 40
    Displayed Market 40
    Dark Pool 40
    Grey Pool 40
    Dark Pool Controversies 41
    Types of Orders 42
    Execution Options 42
    The Trading Floor 44
    Research Function 45
    Sales Function 46
    Algorithmic Trading Decisions 48
    Macro-Level Strategies 48
    Step 1—Choose Implementation Benchmark 49
    Step 2—Select Optimal Execution Strategy 49
    Step 3—Specify Adaptation Tactic 51
    Micro-Level Decisions 52
    Limit Order Models 53
    Smart Order Routers 54
    Algorithmic Analysis Tools 56
    Pre-Trade Analysis 56
    Intraday Analysis 56
    Post-Trade Analysis 57
    Rule-Based Trading 57
    Quantitative Techniques 57
    High Frequency Trading 58
    Auto Market Making 58
    Quantitative Trading/Statistical Arbitrage 60
    Rebate/Liquidity Trading 60
    Direct Market Access 62
    Advantages 63
    Disadvantages 63
    2 Market Microstructure 66
    Introduction 66
    Market Microstructure Literature 68
    The New Market Structure 70
    Pricing Models 75
    Order Priority 76
    Equity Exchanges 76
    New NYSE Trading Model 76
    Designated Market Makers 77
    Supplemental Liquidity Providers 78
    Trading Floor Brokers 79
    NASDAQ Select Market Maker Program 79
    Empirical Evidence 80
    Trading Volumes 80
    Market Share 80
    Large and Small Cap Trading 81
    Do Stocks Trade Differently Across the Exchanges and Venues? 82
    Volume Distribution Statistics 82
    Day of Week Effect 84
    Intraday Trading Profiles 86
    Spreads 86
    Volumes 87
    Volatility 89
    Intraday Trading Stability—Coefficient of Variation 91
    Special Event Days 92
    Flash Crash 95
    Empirical Evidence from the Flash Crash 98
    What Should Regulators do to SafeGuard Investors from Potential Future Flash Crashes? 102
    Comparison with Previous Crashes 103
    Conclusion 104
    3 Algorithmic Transaction Cost Analysis 106
    Introduction 106
    What Are Transaction Costs? 107
    What Is Best Execution? 107
    What Is the Goal of Implementation? 108
    Unbundled Transaction Cost Components 108
    1. Commission 108
    2. Fees 108
    3. Taxes 108
    4. Rebates 109
    5. Spreads 109
    6. Delay Cost 110
    7. Price Appreciation 110
    8. Market Impact 110
    9. Timing Risk 111
    10. Opportunity Cost 111
    Transaction Cost Classification 111
    Transaction Cost Categorization 113
    Transaction Cost Analysis 113
    Measuring/Forecasting 115
    Cost versus Profit and Loss 116
    Implementation Shortfall 116
    Complete Execution 118
    Opportunity Cost (Andre Perold) 119
    Expanded Implementation Shortfall (Wayne Wagner) 120
    Implementation Shortfall Formulation 123
    Trading Cost/Arrival Cost 123
    Evaluating Performance 124
    Trading Price Performance 124
    Benchmark Price Performance 125
    VWAP Benchmark 125
    Participation Weighted Price (PWP) Benchmark 127
    Relative Performance Measure (RPM) 128
    Pre-Trade Benchmark 129
    Index Adjusted Performance Metric 130
    Z-Score Evaluation Metric 131
    Market Cost Adjusted Z-Score 132
    Adaptation Tactic 133
    Comparing Algorithms 134
    Non-Parametric Tests 135
    Paired Samples 136
    Sign Test 136
    Wilcoxon Signed Rank Test 137
    Independent Samples 139
    Mann-Whitney U Test 139
    Median Test 141
    Distribution Analysis 142
    Chi-Square Goodness of Fit 142
    Kolmogorov-Smirnov Goodness of Fit 143
    Experimental Design 144
    Proper Statistical Tests 145
    Small Sample Size 145
    Data Ties 145
    Proper Categorization 146
    Balanced Data Sets 146
    Final Note on Post-Trade Analysis 146
    4 Market Impact Models 148
    Introduction 148
    Definition 148
    Example 1: Temporary Market Impact 149
    Example 2: Permanent Market Impact 149
    Graphical Illustrations of Market Impact 150
    Illustration 1—Price Trajectory 150
    Illustration 2—Supply-Demand Equilibrium 151
    Illustration 3—Temporary Impact Decay Function 154
    Example—Temporary Decay Formulation 156
    Illustration 4—Various Market Impact Price Trajectories 157
    Developing a Market Impact Model 158
    Essential Properties of a Market Impact Model 159
    Derivation of Models 161
    Almgren & Chriss—Market Impact Model
    Random Walk with Price Drift—Discrete Time Periods 162
    Random Walk with Market Impact (No price drift) 163
    I-Star Market Impact Model 165
    Model Formulation 166
    I-Star: Instantaneous Impact Equation 166
    Market Impact Equation 167
    Derivation of the Model 167
    Cost Allocation Method 168
    I* Formulation 170
    Comparison of Approaches 172
    Underlying Data Set 173
    Imbalance/Order Size 173
    Parameter Estimation Techniques 176
    Technique 1: Two-Step Process 176
    Step 1: Estimate Temporary Impact Parameter 176
    Step 2: Estimate ai Parameters 177
    Technique 2: Guesstimate Technique 179
    Technique 3: Non-Linear Optimization 179
    Model Verification 179
    Model Verification 1: Graphical Illustration 180
    Model Verification 2: Regression Analysis 180
    Model Verification 3: Z-Score Analysis 180
    Model Verification 4: Error Analysis 181
    5 Estimating I-Star Model Parameters 182
    Introduction 182
    Scientific Method 183
    Step 1: Ask a Question 183
    Step 2: Research the Problem 183
    Step 3: Construct the Hypothesis 183
    Step 4: Test the Hypothesis 183
    Step 5: Analyze the Data 184
    Step 6: Conclusion and Communication 184
    Solution Technique 185
    The Question 185
    Research the Problem 185
    Construct the Hypothesis 190
    Test the Hypothesis 192
    Data Definitions 194
    Universe of Stocks 195
    Analysis Period 195
    Time Period 195
    Number of Data Points 195
    Imbalance 195
    Side 196
    Volume 196
    Turnover 196
    VWAP 197
    First Price 197
    Average Daily Volume 197
    Annualized Volatility 197
    Size 198
    POV Rate 198
    Cost 198
    Estimating Model Parameters 198
    Sensitivity Analysis 200
    Cost Curves 205
    Statistical Analysis 206
    Error Analysis 206
    Stock Specific Error Analysis 208
    6 Price Volatility 212
    Introduction 212
    Definitions 213
    Price Returns/Price Change 213
    Average Return 213
    Volatility 215
    Covariance 215
    Correlation 216
    Dispersion 216
    Value-at-Risk 216
    Implied Volatility 217
    Beta 217
    Market Observations—Empirical Findings 218
    Forecasting Stock Volatility 221
    Volatility Models 221
    Price Returns 222
    Data Sample 222
    Historical Moving Average (HMA) 223
    Exponential Weighted Moving Average (EWMA) 224
    Arch Volatility Model 224
    GARCH Volatility Model 225
    HMA-VIX Adjustment Model 225
    Determining Parameters via Maximum Likelihood Estimation 227
    Likelihood Function 227
    Estimation Results 228
    Measuring Model Performance 228
    Root Mean Square Error (RMSE) 229
    Root Mean Z-Score Squared Error (RMZSE) 229
    Outlier Analysis 230
    Results 230
    Problems Resulting from Relying on Historical Market Data for Covariance Calculations 233
    False Relationships 233
    Degrees of Freedom 238
    Factor Models 240
    Matrix Notation 242
    Constructing Factor Independence 243
    Estimating Covariance Using a Factor Model 244
    Types of Factor Models 246
    Multi-Index Models 247
    Macroeconomic Factor Models 247
    Cross-Sectional Multi-Factor Models 248
    Index Model 246
    Single Index Model 246
    Statistical Factor Models 250
    7 Advanced Algorithmic Forecasting Techniques 254
    Introduction 254
    Trading Cost Equations 255
    Model Inputs 255
    Trading Strategy 256
    Percentage of Volume 256
    Trading Rate 257
    Trade Schedule 257
    Comparison of POV rate to Trade Rate 258
    Trading Time 258
    Trading Risk Components 259
    Trading Cost Models—Reformulated 260
    Market Impact Expression 260
    I-Star 260
    Market Impact for a Single Stock Order 260
    Market Impact for a Basket of Stock 262
    Timing Risk Equation 262
    Timing Risk for a Basket of Stock 267
    Comparison of Market Impact Estimates 267
    Volume Forecasting Techniques 270
    Daily Volumes 270
    Definitions 270
    Daily Forecasting Analysis—Methodology 271
    Variable Notation 271
    ARMA Daily Forecasting Model 271
    Analysis Goal 272
    Forecast Improvements 276
    Daily Volume Forecasting Model 276
    Forecasting Monthly Volumes 277
    Forecasting Covariance 282
    Efficient Trading Frontier 284
    Single Stock Trade Cost Objective Function 286
    Portfolio Trade Cost Objective Function 286
    8 Algorithmic Decision Making Framework 288
    Introduction 288
    Equations 289
    Algorithmic Decision Making Framework 291
    1) Select Benchmark Price 291
    Arrival Price Benchmark 291
    Historical Price Benchmark 292
    Future Price Benchmark 294
    Comparison of Benchmark Prices 295
    2) Specify Trading Goal 295
    1. Minimize Cost 296
    2. Minimize Cost with Risk Constraint 298
    3. Minimize Risk with Cost Constraint 299
    4. Balance Trade-off between Cost and Risk 299
    5. Price Improvement 300
    Further Insight 302
    3) Specify Adaptation Tactic 303
    Projected Cost 304
    Target Cost Tactic 307
    Aggressive-in-the-Money 308
    Passive-in-the-Money 310
    Comparison across Adaptation Tactics 312
    Modified Adaptation Tactics 313
    How Often Should We Re-Optimize Our Tactics? 313
    9 Portfolio Algorithms 316
    Introduction 316
    Trader’s Dilemma 317
    Variables 318
    Transaction Cost Equations 319
    Market Impact 320
    Price Appreciation 320
    Timing Risk 321
    One-Sided Optimization Problem 321
    Optimization Formulation 321
    Constraint Description 322
    Objective Function Difficulty 324
    Optimization Objective Function Simplification 324
    Portfolio Optimization Techniques 325
    Quadratic Programming Approach 325
    Trade Schedule Exponential 327
    Residual Schedule Exponential 328
    Trading Rate Parameter 329
    Market Impact Expression 329
    Timing Risk Expression 330
    Comparison of Optimization Techniques 331
    Portfolio Adaptation Tactics 335
    Description of AIM and PIM for Portfolio Trading 336
    How Often Should We Re-Optimize? 338
    Managing Portfolio Risk 339
    Residual Risk Curve 339
    Minimum Trading Risk Quantity 341
    Maximum Trading Opportunity 342
    When to Use These Values? 343
    Program-Block Decomposition 344
    Appendix 347
    10 Portfolio Construction 350
    Introduction 350
    Portfolio Optimization and Constraints 351
    Transaction Costs in Portfolio Optimization 354
    Portfolio Management Process 358
    Example: Efficient Trading Frontier w/ and w/o Short Positions 359
    Example: Maximizing Investor Utility 359
    Trading Decision Process 360
    Unifying the Investment and Trading Theories 362
    Cost-Adjusted Frontier 367
    Determining the Appropriate Level of Risk Aversion 369
    Best Execution Frontier 370
    Portfolio Construction with Transaction Costs 371
    Quest for best execution frontier 373
    Return 374
    Risk 374
    Conclusion 378
    11 Quantitative Portfolio Management Techniques 380
    Introduction 380
    Are the Existing Models Useful Enough for Portfolio Construction? 382
    Current State of Vendor Market Impact Models 383
    Pre-Trade of Pre-Trades 386
    Estimation Process 387
    Applications 391
    Example 1 391
    Example 2 392
    Example 3 392
    Example 4 392
    How Expensive Is It to Trade? 393
    Acquisition and Liquidation Costs 396
    Portfolio Management—Screening Techniques 399
    MI Factor Scores 403
    Derivation of the MI Factor Score for Shares 403
    Current State of MI Factor Scores 405
    MI Factor Score Analysis 405
    Alpha Capture Program 407
    Example 5 408
    Example 6 409
    Alpha Capture Curves 412
    12 Cost Index & Multi-Asset Trading Costs
    Introduction 414
    Cost Index 415
    Cost Basis 416
    Cost Strategy 417
    Normalization Process 419
    Customized Indexes 421
    Real-Time Cost Index 422
    Back-Testing 427
    Market Impact Simulation 429
    Simulation Scenario 431
    Multi-Asset Class Investing 434
    Investing in Beta Exposure and Other Factors 434
    Beta Investment Allocation 438
    Multi-Asset Trading Costs 439
    Global Equity Markets 440
    Multi-Asset Classes 441
    13 High Frequency Trading and Black Box Models 448
    Introduction 448
    Data and Research 450
    Strategies 451
    Statistical Arbitrage 451
    Triangular Arbitrage 455
    Liquidity Trading 458
    Market-Neutral Arbitrage 459
    Index and Exchange Traded Fund Arbitrage 461
    Merger Arbitrage 462
    Evaluation 465
    Summary 469
    References 472
    Index 484

    Erscheint lt. Verlag 1.10.2013
    Sprache englisch
    Themenwelt Recht / Steuern Wirtschaftsrecht
    Wirtschaft Betriebswirtschaft / Management Finanzierung
    ISBN-10 0-12-401693-6 / 0124016936
    ISBN-13 978-0-12-401693-4 / 9780124016934
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