INDICE: Contents Acknowledgements Introduction PART I Chapter 1 IntermarketAnalysis 1.1 Determining Intermarket relations 1.2 Using Intermarket Correlations for Portfolio Diversification Chapter 2 Correlation 2.1 The Correlation Coefficient 2.2 Assumptions 2.3 Outliers 2.4 Homoscedasticity Chapter 3 Regression 3.1 The regression equation 3.2 Multiple Regression 3.3 Assumptions 3.4 Non Parametric Regression Chapter 4 International Indices and Commodities 4.1 The DAX 4.2 The CAC 40 4.3 The FTSE 4.4 The Dow Jones Stoxx 50 and Euro Stoxx 504.5 The NIKKEI 4.6 The HANG SENG 4.7 Trading Hours, Symbols and Volatility 4.8 The Dollar Index 4.9 The XOI and the OIX 4.10 The CRB Index 4.11 The GoldmanSachs Commodity Index (GSCI) 4.12 The XAU and the HUI 4.13 The VIX Chapter 5 THE S&P-500 5.1 Correlation with International Indices 5.2 Interest rates, Commodities, FOREX and the VIX 5.3 Correlation between the S&P-500 and stocks Chapter 6 European Indices 6.1 The Dax 6.2 Correlation with Stocks 6.3 European Futures 6.4 Time factor 6.5 Intraday Chapter 7 GOLD 7.1 Correlations with Equity and Commodity assets 7.2 Leading or Lagging? 7.3 Which Time Frame? Chapter 8Intraday Correlations 8.1 Relationships Between Different time frames. 8.2 Intermarket regression 8.3 Which Time Frame? 8.4 Lagging or Leading? Chapter 9 Intermarket Indicators 9.1 Relative Strength 9.2 Bollinger Band Divergence 9.3 Intermarket Disparity 9.4 Intermarket LRS Divergence 9.5 Intermarket Regression Divergence 9.6 Divergence Momentum Oscillator 9.7 Z-Score Divergence 9.8 Multiple Intermarket Divergence 9.9 Multiple Regression Divergence 9.10 Intermarket Moving Average 9.11 Congestion Index PART II Chapter 10 Trading System Design 10.1 Back-testing 10.2 Evaluating Profitability 10.3 Drawdown and other Risk metrics 10.4 Stop-Loss 10.5 Profit Targets 10.6 Money Management 10.7 NeuralNetworks 10.8 Fuzzy Logic Conclusion Chapter 11 A comparison of fourteen technical systems for trading gold 11.1 Test Specifications 11.2 Test Design 11.3 Regression Systems 11.4 Relative Strength 11.5 The Bollinger Band Divergence System 11.6 The Z-Score 11.7 The Linear Regression Slope Method 11.8 Disparity 11.9 Discussion of test results Chapter 12 Trading the S&P ETF and the e-mini 12.1 Daily System 12.2 E-mini Intraday System Chapter 13 Trading DAX futures 13.1 Intermarket Divergence System 13.2 Moving Average Crossover System Chapter14 A Comparison of a Neural Network and a conventional system for trading FTSE futures 14.1 Correlation with International Indices 14.2 Setting up the tests 14.3 Summary of Conditions 14.4 Evaluation of results 14.5 A Neural Network system for trading the FTSE 14.6 Conclusion Chapter 15 The Use of Intermarket systems in trading Stocks 15.1 Testing Method 15.2 A System for trading Oil stocks 15.3 Evaluation of the Oil stock model 15.4 Trading Gold stocks Conclusion Chapter 16 A relative strength asset allocation trading system 16.1 Testing Procedure 16.2 Discussion of results Conclusion Chapter 17 Forex Trading UsingIntermarket Analysis 17.1 Forex Fundamentals 17.2 The Carry Trade 17.3 Trading the Japanese Yen 17.4 The Euro 17.5 Trading the Euro 17.6 Evaluation of Results 17.7 The Australian dollar Conclusion APPENDIX A Metastock code and Test Specifications A.1 Metastock code for the Indicators described in Chapter 9 A.2Metastock code for the Gold Comparison Tests in Chapter 11 A.3 Metastock codefor the S&P systems described in Chapter 12 A.4 Metastock code for the DAX systems described in Chapter 13 A.5 Metastock code for the FTSE systems described in Chapter 14 A.6 Metastock code for the Oil and Gold stock systems in Chapter 15 A.7 Metastock code for the Futures and ETF systems in Chapter 16 A.8 Metastock code for the Forex systems described in Chapter 16 APPENDIX B Neural Network Systems APPENDIX C Rectangles Glossary Index Bibliography
- ISBN: 978-0-470-72424-8
- Editorial: John Wiley & Sons
- Encuadernacion: Cartoné
- Páginas: 512
- Fecha Publicación: 28/11/2008
- Nº Volúmenes: 1
- Idioma: Inglés