Trading Systems : A new approach to system development and portfolio optimisation / Emilio Tomasini and Urban Jaekle.

Format:

Book

Author/Creator:

Tomasini, Emilio, author.

Jaekle, Urban, author.

Language:

English

Subjects (All):

Commodity exchanges--Statistical methods.

Commodity exchanges.

Technical analysis (Investment analysis).

Physical Description:

1 online resource (351 pages)

Edition:

Second edition.

Place of Publication:

Petersfield, England : Harriman House Ltd, [2019]

Summary:

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.

Contents:

Intro

Disclaimer

Acknowledgements

Preface

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

Optimisation

Walk-forward analysis

Robustness

2.4 Evaluation of a trading system

What to look for in an indicator

Average trade

Percentage of profitable trades

Profit factor

Drawdown

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

Introduction

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 filter.

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

Idea

Trading rules

Optimisation of the main parameter of the system

Results

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

Conclusion

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&amp

P 500 stocks

9.4.1 The S&amp

P 500 index

9.4.2 Testing a portfolio of S&amp

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&amp

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&amp

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

Testing

Monte Carlo analysis

Portfolio building

Dynamic risk management

Money management

Appendices

Systems and Ideas

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

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

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.

4.1 Beginning of Month (chapter 5.6)

4.2 Bollinger Band System (chapter 9)

5.1 Beginning of Month

5.2 Bollinger Band System (chapter 9)

Bibliography

Index.

Notes:

Description based on print version record.

Includes bibliographical references and index.

ISBN:

9780857197566

0857197568