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Intermarket Trading Strategies - Markos Katsanos
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Intermarket Trading Strategies – Markos Katsanos

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Description
This book shows traders how to use Intermarket Analysis to forecast future equity, index and commodity price movements. It introduces custom indicators and Intermarket based systems using basic mathematical and statistical principles to help traders develop and design Intermarket trading systems…

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SKU: dee8ef7af984 Category: Forex & Trading Tags: Intermarket Trading Strategies, Intermarket Trading Strategies - Markos Katsanos, Markos Katsanos
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Intermarket Trading Strategies – Markos Katsanos

Intermarket Trading Strategies

This book shows traders how to use Intermarket Analysis to forecast future equity, index and commodity price movements. It introduces custom indicators and Intermarket based systems using basic mathematical and statistical principles to help traders develop and design Intermarket trading systems appropriate for long term, intermediate, short term and day trading. The metastock code for all systems is included and the testing method is described thoroughly. All systems are back tested using at least 200 bars of historical data and compared using various profitability and drawdown metrics.

About the Author

Markos Katsanos is an expert in technical analysis and trading systems and inventor of two new technical indicators. In showing the relationship of volume to price movement, his Finite Volume Element (FVE) and Volume Flow Indicators (VFI) have become popular tools used by traders and the code was incorporated in almost all Technical Analysis and trading software. He has a Bachelors degree in Civil Engineering and a Masters degree in Structural Engineering, and is a member of the Technical Securities Analysts Association of San Francisco (TSAASF). He has traded stocks and commodities since 1987, starting with fundamental analysis. With his engineering training he quickly gravitated to technical analysis of the market. With more than two decades of experience in computerized analysis of stocks and futures, he has spent years refining his methods to come up with some of the most profitable strategies for choosing trades. He specializes in mechanical systems and has constructed dozens of systems for his clients and his own use. Markos Katsanos has contributed several articles to Technical Analysis of Stocks & Commodities and other financial publications. He is currently in the process of setting up his own financial consulting company.

Table of Contents

PART I

1. Intermarket Analysis
1.1 Determining Intermarket relations
1.2 Using Intermarket Correlations for Portfolio Diversification

2. Correlation

3. Regression
3.1 The regression equation
3.2 Multiple Regression
3.3 Assumptions
3.4 Non Parametric Regression

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 50
4.5 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 Goldman Sachs Commodity Index (GSCI)
4.12 The XAU and the HUI
4.13 The VIX

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

6. European Indices
6.1 The Dax
6.2 Correlation with Stocks.
6.3 European Futures
6.4 Time factor
6.5 Intraday

7. GOLD
7.1 Correlations with Equity and Commodity assets
7.2 Leading or Lagging?
7.3 Which Time frame?

8. Intraday Correlations
8.1 Relationships Between Different time frames.
8.2 Intermarket regression
8.3 Which Time frame?
8.4 Lagging or Leading?

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

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 Neural Networks
10.8 Fuzzy Logic

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

12. Trading the S&P ETF and the e-mini
12.1 Daily System
12.2 E-mini Intraday System

13. Trading DAX futures
13.1 Intermarket Divergence System
13.2 Moving Average Crossover System

14. 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

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

16. A relative strength asset allocation trading system
16.1 Testing Procedure
16.2 Discussion of results

17. Forex Trading Using Intermarket 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.2 metastock code for the Gold Comparison Tests in Chapter 11
A.3 metastock code for 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

Includes a detailed procedure for recreating the Neural Network systems described in Chapter 14, using NeuroShell Trader.

APPENDIX C

Rectangles

Provides the metastock code and evaluation of an exploration to detect rectangle formations.

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Archive: https://archive.ph/wip/VL4Jh

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