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Trading Systems 2nd edition

A new approach to system development and portfolio optimisation

By Urban Jaekle and Emilio Tomasini

Paperback £39.99 / $49.99
eBook £29.99 / $39.99
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Trading Systems 2nd edition

A new approach to system development and portfolio optimisation

By Urban Jaekle and Emilio Tomasini

Jacket text

Completely revised and updated second edition, with new AmiBroker codes and new complete portfolio tests

Every day, there are traders who make a fortune. It may seem that it seldom happens, but it does – as William Eckhardt, Ed Seykota, Jim Simons, and many others remind us. You can join them by using systems to manage your trading.

This book explains how you can build a winning trading system. It is an insight into what a trader should know and do in order to achieve success in the markets, and it will show you why you don’t need to be a rocket scientist to become successful.

It shows how to adapt existing codes to the current market conditions, how to build a portfolio, and how to know when the moment has come to stop one system and use another one.

There are three main parts to Trading Systems. Part One is a short, practical guide to trading systems development and evaluation. It condenses the authors’ years of experience into a number of practical tips. It also forms the theoretical basis for Part Two, in which readers will find a step-by-step development process for building a trading system, covering everything from writing initial code to walk-forward analysis and money management. Two examples are provided, including a new beginning of the month trading system that works on over 20 different stock indices worldwide – from the US, to Europe, to Asian indices.

Part Three shows you how to build portfolios in two different ways. The first method is to combine a number of different trading systems, for a number of different markets, into an effective portfolio of systems. The second method is a new approach to system development: it provides step-by-step instructions to trade a portfolio of hundreds of stocks using a Bollinger Band trading strategy.

A trader can never really say they were successful, but only that they survived to trade another day; the black swan is always just around the corner. Trading Systems will help you find your way through the uncharted waters of systematic trading and show you what it takes to be among those that survive.

About the author

Urban Jaekle has been trading stocks for over 25 years and futures for over 20 years. He has worked on the floor of the Chicago Mercantile Exchange (CME) and has managed money for institutional investors with algo trading systems. More info on:

He recently started offering a video course to accompany the book which you can find here

More info on:

About the author

Emilio Tomasini is Adjunct Professor of Corporate Finance at the University of Bologna. Emilio Tomasini is one of the most renowned trading systems experts in Europe. Since 1997, he has managed a swing trading signals service on Nasdaq stocks, at:

Media coverage


Webinar with Urban Jaekle, author of Trading Systems.

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From Seeking Alpha:

In many successful trading systems, especially trend following systems, it is not uncommon that only half of all trades or even less end in a profit. But these winners are on average by a huge factor bigger than the losers and therefore let your account grow. As an example you find here an equity curve… Read more »

Read More…



Preface to the Second Edition
What has happened since 2008?
How this book is presented
The LUXOR system – when performance decays
The importance of controlling losses
Examples of working trading systems
Software and data

Part I: A Short Practical Guide to Trading System Development and Evaluation
1: What is a Trading System?
1.1 An easy example of a trading system
1.2 Why you need a trading system
1.3 The science of trading systems

2: Design, Test, Optimisation and Evaluation of a Trading System
2.1 Design
Getting started
The programming task
Which timeframe to trade?
2.2 Test
The importance of the market data
The length of your back-testing period
Rule complexity and degrees of freedom
2.3 The forecasting power of a trading system
Walk-forward analysis
2.4 Evaluation of a trading system
What to look for in an indicator
Average trade
Percentage of profitable trades
Profit factor
Time averages

2.5 Conclusion

Part II: Trading System Development and Evaluation of a Real Case
3: How to Develop a Trading System Step-By-Step – Using the Example of the British Pound/US Dollar Pair
3.1 The birth of a trading system
The free LUXOR system code
The entry logic
3.2 First evaluation of the trading system
Calculation without slippage and commissions
Calculation after adding slippage and commissions
3.3 Variation of the input parameters: optimisation and stability diagrams
What does stability of a system's input parameter mean? A short theoretical excursion
Dependency of main system figures on the two moving averages
Result with optimised input values
3.4 Inserting an intraday time filter50 Finding the best entry time
Result with added time filter
3.5 Determination of appropriate exits – risk management
The concept of Maximum Adverse Excursion (MAE)
Inserting a risk stop loss
Adding a trailing stop
Looking for profit targets: Maximum Favourable Excursion (MFE)
Summary: Result of the entry logic with the three added exits
How exits are affected by money management
3.6 Summary: Step-by-step development of a trading system

4: Two Methods for Evaluating the System's Predictive Power
4.1 Timescale analysis
Changing the compression of the price data
LUXOR tested on different bar compressions
Net profit and maximum drawdown dependent on the traded bar length
Explanation for the time dependency of the system
4.2 Monte Carlo analysis
The principle of Monte Carlo analysis
Exchanging the order of the performed trades
Probabilities and confidence levels
Performing a Monte Carlo analysis with the LUXOR trading system
Limitations of the Monte Carlo method

5: The Factors Around Your System
5.1 The market's long/short bias
The trend is your friend?
Consequences for system development
5.2 Out-of-sample deterioration
A Bollinger Band system with logic and code
Entry logic: Bollinger Band system
Optimising the Bollinger Band system
Out-of-sample result
Reasons for the out-of-sample deterioration
5.3 The market data bias
Expanding the training period
Conclusion: How to choose your training data
5.4 Optimisation and over-fitting
Step-by-step optimisation of the LUXOR system
Results depending on the number of optimised parameters
The meaning of the trading system's complexity
5.5 Rule complexity explained with polynomial curve fitting
Interpolating data points with polynomial functions
Predictive power of the different polynomials
Conclusions for trading system development
5.6 Example of a simple, robust trading system
Trading rules
Optimisation of the main parameter of the system
Strategy evaluation

6: Periodic Reoptimisation and Walk-forward Analysis
6.1 Short repetition: normal, static optimisation
6.2 Anchored vs. rolling walk-forward analysis (WFA)
6.3 Rolling WFA on the LUXOR system
Periodic optimisation of the two main system parameters
Out-of-sample test result
6.4 The meaning of sample size and market structure

7: Position Sizing Example, Using the LUXOR System
7.1 Definitions: money management vs. risk management
Risk management (RM)
Money management (MM)
7.2 Application of different MM schemes
Reference: The system traded with one lot
Maximum drawdown MM
Fixed fractional MM
Fixed ratio MM
7.3 Monte Carlo analysis of the position sized system
7.4 Conclusion

Part III: Systematic Portfolio Trading
8: Dynamic Portfolio Construction
8.1 Introduction to portfolio construction
A list of the main available software for portfolio trading
The role of correlations
Publications and theoretical tools
Portfolio trading in practice
Total vs. partial equity contribution
8.2 Correlation among equity lines
8.3 A dynamic approach: equity line crossover
8.4 How to transform an average system portfolio into a profitable one: the case of LUXOR
8.5 Dynamic portfolio composition: the walk-forward analysis activator
8.6 Largest losing trade/largest losing streak/largest drawdown

9: Trading a Portfolio of Stocks
9.1 Modifications when applying a Bollinger Band system to stocks
The Bollinger Band system – trading logic for stocks
9.2 Examples: Results on single stocks
9.3 Survivorship bias in portfolio back-tests
9.4 Application of the strategy to a portfolio of S&P 500 stocks
9.4.1 The S&P 500 index
9.4.2 Testing a portfolio of S&P 500 stocks
9.4.3 Introducing a market filter
9.4.4 Optimising two parameters together: index filter and Bollinger Band length
9.4.5 Variation of the entry and exit point = upper and lower band distance
9.4.6 Ranking methods in case multiple signals occur on the same day
9.4.7 Conclusion: Development of a trading system on the S&P 500 stocks
9.5 Monte Carlo analysis of the Bollinger Band system
9.6 Periodic reoptimisation/walk-forward analysis (WFA)
9.7 Results on other portfolios of stocks
9.7.1 Nasdaq 100 – technology at work
9.7.2 The S&P 1500 – a large index
9.7.3 Overview: Bollinger Band System vs. buy and hold
9.8 Position management with five stocks on the Nasdaq 100 – practical example
9.9 The psychological phenomenon of loss aversion
9.10 Different ways of daily execution
a) Professional back-testing and daily implementation, all in one
b) Professional back-testing and daily implementation, separated
c) Daily implementation without back-testing
Rule complexity
Monte Carlo analysis
Portfolio building
Dynamic risk management
Money management

Appendices: Systems and Ideas
Appendix 1. Bollinger Band System
1.1 Idea
1.2 Entry logic and EasyLanguage code
1.3 Application of the strategy to seven markets with same parameters
1.4 Results and conclusions

Appendix 2. The Triangle System
2.1 Idea
2.2 Programming and coding
2.3 Application to different liquid futures markets with same parameters
2.4 Advantages in building a portfolio
2.5 Conclusion

Appendix 3. Portfolios with the LUXOR Trading System
3.1 Idea
3.2 The trading logic
3.3 Results in the bond markets
3.4 Diversification with other market groups
3.5 Conclusion

Appendix 4. EasyLanguage Code Section
4.1 Beginning of Month (chapter 5.6)
4.2 Bollinger Band System (chapter 9)

Appendix 5: AmiBroker Code Section
5.1 Beginning of Month
5.2 Bollinger Band System (chapter 9)


Published: 17/12/2019
Edition: 2nd
Pages: 254
Formats: paperback - ISBN 9780857197559
ebook - ISBN 9780857197566
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