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New edition of book that demystifies quant and algo trading
In this updated edition of his bestselling book, Rishi K Narang offers in a straightforward, nontechnical style--supplemented by real-world examples and informative anecdotes--a reliable resource takes you on a detailed tour through the black box. He skillfully sheds light upon the work that quants do, lifting the veil of mystery around quantitative trading and allowing anyone interested in doing so to understand quants and their strategies. This new edition includes information on High Frequency Trading. Offers an update on the…mehr
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New edition of book that demystifies quant and algo trading
In this updated edition of his bestselling book, Rishi K Narang offers in a straightforward, nontechnical style--supplemented by real-world examples and informative anecdotes--a reliable resource takes you on a detailed tour through the black box. He skillfully sheds light upon the work that quants do, lifting the veil of mystery around quantitative trading and allowing anyone interested in doing so to understand quants and their strategies. This new edition includes information on High Frequency Trading.
Offers an update on the bestselling book for explaining in non-mathematical terms what quant and algo trading are and how they work
Provides key information for investors to evaluate the best hedge fund investments
Explains how quant strategies fit into a portfolio, why they are valuable, and how to evaluate a quant manager
This new edition of Inside the Black Box explains quant investing without the jargon and goes a long way toward educating investment professionals.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
In this updated edition of his bestselling book, Rishi K Narang offers in a straightforward, nontechnical style--supplemented by real-world examples and informative anecdotes--a reliable resource takes you on a detailed tour through the black box. He skillfully sheds light upon the work that quants do, lifting the veil of mystery around quantitative trading and allowing anyone interested in doing so to understand quants and their strategies. This new edition includes information on High Frequency Trading.
Offers an update on the bestselling book for explaining in non-mathematical terms what quant and algo trading are and how they work
Provides key information for investors to evaluate the best hedge fund investments
Explains how quant strategies fit into a portfolio, why they are valuable, and how to evaluate a quant manager
This new edition of Inside the Black Box explains quant investing without the jargon and goes a long way toward educating investment professionals.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Wiley Finance Series .
- Verlag: Wiley & Sons
- Artikelnr. des Verlages: 1W118362410
- 2. Aufl.
- Seitenzahl: 336
- Erscheinungstermin: 26. April 2013
- Englisch
- Abmessung: 236mm x 156mm x 38mm
- Gewicht: 542g
- ISBN-13: 9781118362419
- ISBN-10: 1118362411
- Artikelnr.: 36549195
- Wiley Finance Series .
- Verlag: Wiley & Sons
- Artikelnr. des Verlages: 1W118362410
- 2. Aufl.
- Seitenzahl: 336
- Erscheinungstermin: 26. April 2013
- Englisch
- Abmessung: 236mm x 156mm x 38mm
- Gewicht: 542g
- ISBN-13: 9781118362419
- ISBN-10: 1118362411
- Artikelnr.: 36549195
Rishi K. Narang is the Founding Principal of Telesis Capital LLC, which invests in quantitative trading strategies. Previously, he was managing director and co-portfolio manager at Santa Barbara Alpha Strategies. Narang cofounded and was president of Tradeworx, Inc., a quantitative hedge fund manager, from 1999-2002. He has been involved in the hedge fund industry, with a focus on quantitative trading strategies, since 1996. Narang graduated from the University of California, Berkeley, with a BA in economics.
Preface to the Second Edition xiii Acknowledgments xvii Part ONE The Quant
Universe Chapter 1 Why Does Quant Trading Matter? 3 The Benefit of Deep
Thought 8 The Measurement and Mismeasurement of Risk 9 Disciplined
Implementation 10 Summary 11 Notes 11 Chapter 2 An Introduction to
Quantitative Trading 13 What Is a Quant? 14 What Is the Typical Structure
of a Quantitative Trading System? 16 Summary 19 Notes 20 Part two Inside
the Black Box Chapter 3 Alpha Models: How Quants Make Money 23 Types of
Alpha Models: Theory-Driven and Data-Driven 24 Theory-Driven Alpha Models
26 Data-Driven Alpha Models 42 Implementing the Strategies 45 Blending
Alpha Models 56 Summary 62 Notes 64 Chapter 4 Risk Models 67 Limiting the
Amount of Risk 69 Limiting the Types of Risk 72 Summary 76 Notes 78 Chapter
5 Transaction Cost Models 79 Defining Transaction Costs 80 Types of
Transaction Cost Models 85 Summary 90 Note 91 Chapter 6 Portfolio
Construction Models 93 Rule-Based Portfolio Construction Models 94
Portfolio Optimizers 98 Output of Portfolio Construction Models 112 How
Quants Choose a Portfolio Construction Model 113 Summary 113 Notes 115
Chapter 7 Execution 117 Order Execution Algorithms 119 Trading
Infrastructure 128 Summary 130 Notes 131 Chapter 8 Data 133 The Importance
of Data 133 Types of Data 135 Sources of Data 137 Cleaning Data 139 Storing
Data 144 Summary 145 Notes 146 Chapter 9 Research 147 Blueprint for
Research: The Scientific Method 147 Idea Generation 149 Testing 151 Summary
170 Note 171 Part three A Practical Guide for Investors in Quantitative
Strategies Chapter 10 Risks Inherent to Quant Strategies 175 Model Risk 176
Regime Change Risk 180 Exogenous Shock Risk 184 Contagion, or Common
Investor, Risk 186 How Quants Monitor Risk 193 Summary 195 Notes 195
Chapter 11 Criticisms of Quant Trading 197 Trading Is an Art, Not a Science
197 Quants Cause More Market Volatility by Underestimating Risk 199 Quants
Cannot Handle Unusual Events or Rapid Changes in Market Conditions 204
Quants Are All the Same 206 Only a Few Large Quants Can Thrive in the Long
Run 207 Quants Are Guilty of Data Mining 210 Summary 213 Notes 213 Chapter
12 Evaluating Quants and Quant Strategies 215 Gathering Information 216
Evaluating a Quantitative Trading Strategy 218 Evaluating the Acumen of
Quantitative Traders 221 The Edge 223 Evaluating Integrity 227 How Quants
Fit into a Portfolio 229 Summary 231 Note 233 Part four High-Speed and
High-Frequency Trading Chapter 13 An Introduction to High-Speed and
High-Frequency Trading* 237 Notes 241 Chapter 14 High-Speed Trading 243 Why
Speed Matters 244 Sources of Latency 252 Summary 262 Notes 263 Chapter 15
High-Frequency Trading 265 Contractual Market Making 265 Noncontractual
Market Making 269 Arbitrage 271 Fast Alpha 273 HFT Risk Management and
Portfolio Construction 274 Summary 277 Note 277 Chapter 16 Controversy
Regarding High-Frequency Trading 279 Does HFT Create Unfair Competition?
280 Does HFT Lead to Front-Running or Market Manipulation? 283 Does HFT
Lead to Greater Volatility or Structural Instability? 289 Does HFT Lack
Social Value? 296 Regulatory Considerations 297 Summary 299 Notes 300
Chapter 17 Looking to the Future of Quant Trading 303 About the Author 307
Index 309
Universe Chapter 1 Why Does Quant Trading Matter? 3 The Benefit of Deep
Thought 8 The Measurement and Mismeasurement of Risk 9 Disciplined
Implementation 10 Summary 11 Notes 11 Chapter 2 An Introduction to
Quantitative Trading 13 What Is a Quant? 14 What Is the Typical Structure
of a Quantitative Trading System? 16 Summary 19 Notes 20 Part two Inside
the Black Box Chapter 3 Alpha Models: How Quants Make Money 23 Types of
Alpha Models: Theory-Driven and Data-Driven 24 Theory-Driven Alpha Models
26 Data-Driven Alpha Models 42 Implementing the Strategies 45 Blending
Alpha Models 56 Summary 62 Notes 64 Chapter 4 Risk Models 67 Limiting the
Amount of Risk 69 Limiting the Types of Risk 72 Summary 76 Notes 78 Chapter
5 Transaction Cost Models 79 Defining Transaction Costs 80 Types of
Transaction Cost Models 85 Summary 90 Note 91 Chapter 6 Portfolio
Construction Models 93 Rule-Based Portfolio Construction Models 94
Portfolio Optimizers 98 Output of Portfolio Construction Models 112 How
Quants Choose a Portfolio Construction Model 113 Summary 113 Notes 115
Chapter 7 Execution 117 Order Execution Algorithms 119 Trading
Infrastructure 128 Summary 130 Notes 131 Chapter 8 Data 133 The Importance
of Data 133 Types of Data 135 Sources of Data 137 Cleaning Data 139 Storing
Data 144 Summary 145 Notes 146 Chapter 9 Research 147 Blueprint for
Research: The Scientific Method 147 Idea Generation 149 Testing 151 Summary
170 Note 171 Part three A Practical Guide for Investors in Quantitative
Strategies Chapter 10 Risks Inherent to Quant Strategies 175 Model Risk 176
Regime Change Risk 180 Exogenous Shock Risk 184 Contagion, or Common
Investor, Risk 186 How Quants Monitor Risk 193 Summary 195 Notes 195
Chapter 11 Criticisms of Quant Trading 197 Trading Is an Art, Not a Science
197 Quants Cause More Market Volatility by Underestimating Risk 199 Quants
Cannot Handle Unusual Events or Rapid Changes in Market Conditions 204
Quants Are All the Same 206 Only a Few Large Quants Can Thrive in the Long
Run 207 Quants Are Guilty of Data Mining 210 Summary 213 Notes 213 Chapter
12 Evaluating Quants and Quant Strategies 215 Gathering Information 216
Evaluating a Quantitative Trading Strategy 218 Evaluating the Acumen of
Quantitative Traders 221 The Edge 223 Evaluating Integrity 227 How Quants
Fit into a Portfolio 229 Summary 231 Note 233 Part four High-Speed and
High-Frequency Trading Chapter 13 An Introduction to High-Speed and
High-Frequency Trading* 237 Notes 241 Chapter 14 High-Speed Trading 243 Why
Speed Matters 244 Sources of Latency 252 Summary 262 Notes 263 Chapter 15
High-Frequency Trading 265 Contractual Market Making 265 Noncontractual
Market Making 269 Arbitrage 271 Fast Alpha 273 HFT Risk Management and
Portfolio Construction 274 Summary 277 Note 277 Chapter 16 Controversy
Regarding High-Frequency Trading 279 Does HFT Create Unfair Competition?
280 Does HFT Lead to Front-Running or Market Manipulation? 283 Does HFT
Lead to Greater Volatility or Structural Instability? 289 Does HFT Lack
Social Value? 296 Regulatory Considerations 297 Summary 299 Notes 300
Chapter 17 Looking to the Future of Quant Trading 303 About the Author 307
Index 309
Preface to the Second Edition xiii Acknowledgments xvii Part ONE The Quant
Universe Chapter 1 Why Does Quant Trading Matter? 3 The Benefit of Deep
Thought 8 The Measurement and Mismeasurement of Risk 9 Disciplined
Implementation 10 Summary 11 Notes 11 Chapter 2 An Introduction to
Quantitative Trading 13 What Is a Quant? 14 What Is the Typical Structure
of a Quantitative Trading System? 16 Summary 19 Notes 20 Part two Inside
the Black Box Chapter 3 Alpha Models: How Quants Make Money 23 Types of
Alpha Models: Theory-Driven and Data-Driven 24 Theory-Driven Alpha Models
26 Data-Driven Alpha Models 42 Implementing the Strategies 45 Blending
Alpha Models 56 Summary 62 Notes 64 Chapter 4 Risk Models 67 Limiting the
Amount of Risk 69 Limiting the Types of Risk 72 Summary 76 Notes 78 Chapter
5 Transaction Cost Models 79 Defining Transaction Costs 80 Types of
Transaction Cost Models 85 Summary 90 Note 91 Chapter 6 Portfolio
Construction Models 93 Rule-Based Portfolio Construction Models 94
Portfolio Optimizers 98 Output of Portfolio Construction Models 112 How
Quants Choose a Portfolio Construction Model 113 Summary 113 Notes 115
Chapter 7 Execution 117 Order Execution Algorithms 119 Trading
Infrastructure 128 Summary 130 Notes 131 Chapter 8 Data 133 The Importance
of Data 133 Types of Data 135 Sources of Data 137 Cleaning Data 139 Storing
Data 144 Summary 145 Notes 146 Chapter 9 Research 147 Blueprint for
Research: The Scientific Method 147 Idea Generation 149 Testing 151 Summary
170 Note 171 Part three A Practical Guide for Investors in Quantitative
Strategies Chapter 10 Risks Inherent to Quant Strategies 175 Model Risk 176
Regime Change Risk 180 Exogenous Shock Risk 184 Contagion, or Common
Investor, Risk 186 How Quants Monitor Risk 193 Summary 195 Notes 195
Chapter 11 Criticisms of Quant Trading 197 Trading Is an Art, Not a Science
197 Quants Cause More Market Volatility by Underestimating Risk 199 Quants
Cannot Handle Unusual Events or Rapid Changes in Market Conditions 204
Quants Are All the Same 206 Only a Few Large Quants Can Thrive in the Long
Run 207 Quants Are Guilty of Data Mining 210 Summary 213 Notes 213 Chapter
12 Evaluating Quants and Quant Strategies 215 Gathering Information 216
Evaluating a Quantitative Trading Strategy 218 Evaluating the Acumen of
Quantitative Traders 221 The Edge 223 Evaluating Integrity 227 How Quants
Fit into a Portfolio 229 Summary 231 Note 233 Part four High-Speed and
High-Frequency Trading Chapter 13 An Introduction to High-Speed and
High-Frequency Trading* 237 Notes 241 Chapter 14 High-Speed Trading 243 Why
Speed Matters 244 Sources of Latency 252 Summary 262 Notes 263 Chapter 15
High-Frequency Trading 265 Contractual Market Making 265 Noncontractual
Market Making 269 Arbitrage 271 Fast Alpha 273 HFT Risk Management and
Portfolio Construction 274 Summary 277 Note 277 Chapter 16 Controversy
Regarding High-Frequency Trading 279 Does HFT Create Unfair Competition?
280 Does HFT Lead to Front-Running or Market Manipulation? 283 Does HFT
Lead to Greater Volatility or Structural Instability? 289 Does HFT Lack
Social Value? 296 Regulatory Considerations 297 Summary 299 Notes 300
Chapter 17 Looking to the Future of Quant Trading 303 About the Author 307
Index 309
Universe Chapter 1 Why Does Quant Trading Matter? 3 The Benefit of Deep
Thought 8 The Measurement and Mismeasurement of Risk 9 Disciplined
Implementation 10 Summary 11 Notes 11 Chapter 2 An Introduction to
Quantitative Trading 13 What Is a Quant? 14 What Is the Typical Structure
of a Quantitative Trading System? 16 Summary 19 Notes 20 Part two Inside
the Black Box Chapter 3 Alpha Models: How Quants Make Money 23 Types of
Alpha Models: Theory-Driven and Data-Driven 24 Theory-Driven Alpha Models
26 Data-Driven Alpha Models 42 Implementing the Strategies 45 Blending
Alpha Models 56 Summary 62 Notes 64 Chapter 4 Risk Models 67 Limiting the
Amount of Risk 69 Limiting the Types of Risk 72 Summary 76 Notes 78 Chapter
5 Transaction Cost Models 79 Defining Transaction Costs 80 Types of
Transaction Cost Models 85 Summary 90 Note 91 Chapter 6 Portfolio
Construction Models 93 Rule-Based Portfolio Construction Models 94
Portfolio Optimizers 98 Output of Portfolio Construction Models 112 How
Quants Choose a Portfolio Construction Model 113 Summary 113 Notes 115
Chapter 7 Execution 117 Order Execution Algorithms 119 Trading
Infrastructure 128 Summary 130 Notes 131 Chapter 8 Data 133 The Importance
of Data 133 Types of Data 135 Sources of Data 137 Cleaning Data 139 Storing
Data 144 Summary 145 Notes 146 Chapter 9 Research 147 Blueprint for
Research: The Scientific Method 147 Idea Generation 149 Testing 151 Summary
170 Note 171 Part three A Practical Guide for Investors in Quantitative
Strategies Chapter 10 Risks Inherent to Quant Strategies 175 Model Risk 176
Regime Change Risk 180 Exogenous Shock Risk 184 Contagion, or Common
Investor, Risk 186 How Quants Monitor Risk 193 Summary 195 Notes 195
Chapter 11 Criticisms of Quant Trading 197 Trading Is an Art, Not a Science
197 Quants Cause More Market Volatility by Underestimating Risk 199 Quants
Cannot Handle Unusual Events or Rapid Changes in Market Conditions 204
Quants Are All the Same 206 Only a Few Large Quants Can Thrive in the Long
Run 207 Quants Are Guilty of Data Mining 210 Summary 213 Notes 213 Chapter
12 Evaluating Quants and Quant Strategies 215 Gathering Information 216
Evaluating a Quantitative Trading Strategy 218 Evaluating the Acumen of
Quantitative Traders 221 The Edge 223 Evaluating Integrity 227 How Quants
Fit into a Portfolio 229 Summary 231 Note 233 Part four High-Speed and
High-Frequency Trading Chapter 13 An Introduction to High-Speed and
High-Frequency Trading* 237 Notes 241 Chapter 14 High-Speed Trading 243 Why
Speed Matters 244 Sources of Latency 252 Summary 262 Notes 263 Chapter 15
High-Frequency Trading 265 Contractual Market Making 265 Noncontractual
Market Making 269 Arbitrage 271 Fast Alpha 273 HFT Risk Management and
Portfolio Construction 274 Summary 277 Note 277 Chapter 16 Controversy
Regarding High-Frequency Trading 279 Does HFT Create Unfair Competition?
280 Does HFT Lead to Front-Running or Market Manipulation? 283 Does HFT
Lead to Greater Volatility or Structural Instability? 289 Does HFT Lack
Social Value? 296 Regulatory Considerations 297 Summary 299 Notes 300
Chapter 17 Looking to the Future of Quant Trading 303 About the Author 307
Index 309