Inside the Black Box: A Simple Guide to Quantitative and High Frequency Trading (by Rishi K. Narang)

Inside the Black Box
Inside the Black Box


ISBN: 9781118362419Number of Pages: 336
Publisher:  WileyBook Title: Inside the Black Box: A Simple Guide to Quantitative and High Frequency Trading
Publication Year: 2013Target Audience: Trade
Author: Rishi K. NarangReading Age: 18+


Whether it is quantification, algorithm, or black box trading, we are talking about one thing: systematic trading executed by computers.

Although someone blame them for being dangerously out of human control and driving excessive market volatility, others believe that quantitative trading can overcome human greed and human cognitive bias in making investment decisions.

In general, no matter how much you know about quantitative trading, quantitative funds continue to outperform the market, which is why many smart investors chase black boxes.

Unfortunately, many parts of quantitative trading are still ambiguous, mainly because of the extreme confidentiality how the system works. However, in this version, as a quantitative trader and master interpreter, the author skillfully tells the reader that quantitative trading is easier to understand and control than you think.

Inside the Black Box is to enable readers and even investors who are afraid of mathematics or technology to understand quantitative trading. This book will lead you through the black box journey. The author points out the work done by the quants with concise language and unveils the mystery of quantitative trading and quantitative trading strategy.

After a brief introduction of quantitative trading rules and general rules, the author turned to the topic and began to introduce the detailed internals of a typical black box system, explaining in non-technical language what the internals are and how they are combined.

The author clearly explains with a large number of actual cases and true stories:

  • The most common quantization system structure
  • How to chase Alpha
  • Subjective judgment level in quantitative trading
  • High-frequency trading and facilities
  • Executing algorithms and how they work
  • How to build a risk model and how to know whether a specific model is effective
  • Important differences between theory-driven systems and data mining strategies
  • How to evaluate quantitative managers and their strategies
  • How to embed quantitative strategies into a comprehensive portfolio strategy and why they are important
  • Quantify current and future trends of transactions and their roles in the future

This book explains black box trading, making it transparent, intuitive, and easier to understand. This book is a must-read for institutional investors, asset managers, pension managers, and all smart investors who are eager to gain advantages in today’s uncertain financial markets.

Inside the Black Box is one of the Best Quantitative Trading Books for Beginners

About the Author

Rishi K. Narang is a top quantitative financial expert on Wall Street and a senior hedge fund manager. Now, he is the principal partner of Telesis Capital LLC, which mainly uses a quantitative trading strategy for investment.

Previously, he was the general manager and portfolio manager of Santa Barbara Alpha Strategies.

He also co-founded Tradeworx, a company that managed quantitative hedge funds from 1999 to 2002, and served as president.

Since 1996, he has been engaged in hedge funds, focusing on quantitative trading strategies. Rich graduated from the University of California, Berkeley, with a bachelor’s degree in economics.

Inside the Black Box  PDF version will come as soon as possible.

Table of Contents

Part one – the quant universe

1. Why does quant trading matter

  • the benefit of deep thought
  • the measurement and mismeasurement of risk
  • disciplined implementation

2. A introduction to quant trading

  • what is a quant
  • what is the typical structure of the quantitative trading system

Part two – inside the black box

3. Alpha models – how quants make money

  • types of alpha models: theory-driven and data-driven
  • theory-driven alpha models
  • data-driven alpha models
  • implementing the strategies
  • blending alpha models

4. risk models

5. transaction construction models

6. portfolio construction models

7. execution

8. data

9. research

Part three – a practical guide for investors in quantitive strategies

10. risks inherent to quant strategies

  • model risk
  • regime change risk
  • exogenous shock risk
  • contagion, or common investor, risk
  • how quants monitor risk

11. criticism of quant trading – setting the record straight

  • trading is an art, not a science
  • quants cause more market volatility by underestimating the risk
  • quants cannot handle unusual events or rapid changes in market conditions
  • quants are all the same
  • only a few large quants can thrive in the long run
  • quants are guilty of data mining

12. evaluating quants and quant strategies

13. looking to the future of quant-trading

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