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Part I: A Practical Guide to Trading System
Development and Evaluation 1
Chapter 1: What is a trading system? 3
1.1 An easy example of a trading system 4
1.2 Why you need a trading system 5
1.3 The science of trading systems 7
Chapter 2: Design, test, optimisation and evaluation of a
trading system 9
2.1 Design 9
Getting started 9
The programming task 10
Which timeframe to trade? 11
2.2 Test 12
The importance of the market data 12
The length of your back-testing period 14
Rule complexity and degrees of freedom 15
2.3 The forecasting power of a trading system 19
Optimisation 19
Walk forward analysis 21
Robustness 23
2.4 Evaluation of a trading system 27
What to look for in an indicator 27
Average trade 28
Percentage of profitable trades 28
Profit factor 30
Drawdown 30
Time averages 31
RINA Index 32
2.5 Conclusion 33
Part II: Trading System Development and Evaluation
of a Real Case 35
Chapter 3: How to develop a trading system step-by-step –
using the example of the British pound/US dollar pair 37
Introduction 37
3.1 The birth of a trading system 38
The free LUXOR system code 39
The entry logic 41
3.2 First evaluation of the trading system 43
Calculation without slippage and commissions 43
Calculation after adding slippage and commissions 47
3.3 Variation of the input parameters: optimisation and
stability diagrams 49
What does stability of a system’s input parameter mean?
A short theoretical excursion 49
Dependency of main system figures on the two moving
averages 51
Result with optimised input values 56
3.4 Inserting an intraday time filter 59
Finding the best entry time 59
Result with added time filter 61
3.5 Determination of appropriate exits – risk management 64
The concept of Maximum Adverse Excursion (MAE) 66
Inserting a risk stop loss 70
Adding a trailing stop 74
Looking for profit targets: Maximum Favorable
Excursion (MFE) 76
Summary: Result of the entry logic with the three
added exits 79
How exits are affected by money management 83
3.6 Summary: Step-by-step development of a trading system 86
Chapter 4: Two methods for evaluating the system’s
predictive power 89
4.1 Timescale analysis 90
Changing the compression of the price data 90
LUXOR tested on different bar compressions 92
Net profit and maximum drawdown dependent on the
traded bar length 96
Explanation for the time dependency of the system 97
4.2 Monte Carlo analysis 101
The principle of Monte Carlo analysis 101
Exchanging the order of the performed trades 104
Probabilities and confidence levels 105
Performing a Monte Carlo analysis with the LUXOR
trading system 107
Limitations of the Monte Carlo method 108
Chapter 5: The factors around your system 111
5.1 The market’s long/short bias 112
The trend is your friend? 112
Consequences for system development 114
5.2 Out-of-sample deterioration 115
A Bollinger Band system with logic and code 115
Optimising the Bollinger Band system 118
Out-of-sample result 119
Reasons for the out-of-sample deterioration 121
5.3 The market data bias 122
Expanding the training period 122
Conclusion: How to choose your training data 126
5.4 Optimisation and over-fitting 126
Step-by-step optimisation of the LUXOR system 126
Results depending on the number of optimised parameters 127
The meaning of the trading system’s complexity 134
5.5 Rule complexity explained with polynomial curve fitting 136
Interpolating data points with polynomial functions 136
Predictive power of the different polynomials 142
Conclusions for trading system development 145
Chapter 6: Periodic re-optimisation and walk forward analysis 147
6.1 Short repetition: “normal”, static optimisation 147
6.2 Anchored vs. rolling walk forward analysis (WFA) 149
6.3 Rolling WFA on the LUXOR system 150
Periodic optimisation of the two main system parameters 150
Out-of-sample test result 153
Conclusion 155
6.4 The meaning of sample size and market structure 155
Chapter 7: Position sizing example, using the LUXOR system 159
7.1 Definitions: money management vs. risk management 159
Risk management (RM) 159
Money management (MM) 160
7.2 Application of different MM schemes 161
Reference: The system traded with one lot 162
Maximum drawdown MM 163
Fixed fractional MM 164
Fixed ratio MM 168
7.3 Monte Carlo analysis of the position sized system 173
7.4 Conclusion 175
Contents
vii
Part III: Systematic Portfolio Trading 177
Chapter 8: Dynamic portfolio construction 179
8.1 Introduction to portfolio construction 179
A list of the main available software 180
The role of correlations 181
Publications and theoretical tools 182
Portfolio trading in practice 183
Total vs. partial equity contribution 185
8.2 Correlation among equity lines 186
8.3 A dynamic approach: equity line crossover 188
8.4 Dynamic portfolio composition: the walk forward analysis activator 190
8.5 Largest losing trade/largest losing streak/largest drawdown 192
Conclusion 193
Appendices: Systems and ideas 199
Appendix 1: Bollinger Band system 201
1.1 Idea 201
1.2 Entry logic and Easy Language code 202
1.3 Application of the strategy to seven markets with
same parameters 204
1.4 Results and conclusions 204
Appendix 2: The Triangle system 209
2.1 Idea 209
2.2 Programming and coding 210
2.3 Application to different liquid futures markets with
same parameters 211
2.4 Advantages in building a portfolio 212
2.5 Conclusion 212
Trading Systems
viii
Appendix 3: Portfolios with the LUXOR trading system 221
3.1 Idea 221
3.2 The trading logic 223
3.3 Results in the bond markets 223
3.4 Diversification with other market groups 224
3.5 Conclusion 225
Bibliography 235
Index 237
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