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.
Introduction:
It has been more than 15 years since John Murphy, a pioneer on the subject, wrote his first book on intermarket analysis. The material in my book is based on original research not published anywhere else and, unlike Murphy’s intuitive chart-based approach, I am going to use mathematical and statistical principles to develop and design intermarket trading systems appropriate for long- and short-term and even day trading. Although the book makes extensive use of market statistics obtained from hundreds of correlation studies, the data and empirical findings are not its heart. They serve as a background in developing the trading systems presented in the second part of the book, as well as help shape our thinking about the way the financial markets work.
The key difference between Intermarket Trading Strategies and other books on trading lies in its philosophy. I believe that knowing how the markets work is, in the end, more important than relying on a “black box” mechanical system that produced profitable trades in the past but not even the creator of the system can fully explain why. The focus of this book is how intermarket analysis can be used to forecast future equity and index price movements by introducing custom indicators and intermarket-based systems. A total of 29 conventional and five neural network trading systems are provided to trade gold, the S&P ETF (SPY), S&P e-mini futures, DAX and FTSE futures, gold and oil stocks, commodities, sector and international ETF, and finally the yen and the euro.
Naturally, past results are no guarantee of future performance. Even so, the results of out-of-sample back-testing are compelling enough to merit attention. Some results are more compelling. The multiple regression gold system, presented in Chapter 11, returned an amazing $1.2 million of profits on a $100 000 initial equity. The stock index trading systems also produced impressive profits. The profitability of the Standard & Poor’s e-mini intraday system was neither standard nor poor, producing a 300 % profit during the test duration. Investors who prefer to trade only stocks will find intermarket systems for trading oil and gold stocks in Chapter 15. My favorite is the oil stock system which made more than $1.6 million on an initial equity of only $100 000.
The foreign exchange (or Forex) market, which until recently was dominated by large international banks, is gaining popularity among active traders, because of its superior liquidity and 24-hour trading. Readers who are interested in forex trading will find, in Chapter 17, an intermarket system for trading the yen which made over$70 000 on an initial $3000 account. The EUR/USD is the most popular currency pair among forex traders and the chapter on forex wouldn’t be complete without a system for trading the euro. The next section in Chapter 17 presents two systems: a conventional and a hybrid system. The latter is an excellent example of how you can enhance a classic system by adding intermarket conditions. The hybrid system improved considerably on the profitability of the traditional trend-following system, almost doubling the profit factor while reducing drawdown.
The system design is fully described from the initial concept to optimization and actual implementation. All systems are back-tested using out-of-sample data and the performance statistics are provided for each one. The MetaStock code for all systems is provided in Appendix A and a detailed procedure for recreating the artificial neural network systems in NeuroShell Trader is included in Appendix B. The benefits of diversification, and an example of static portfolio diversification by optimizing the portfolio allocation based on the desired risk and return characteristics, are discussed in the first chapter and a dynamic portfolio allocation method, based on market timing and relative strength, is included in Chapter 16.
The book is divided into two parts. Part I serves as a background to Part II and includes an overview of the basics of intermarket analysis, correlation analysis in Chapter 2 and custom intermarket indicators in Chapter 9. Part II uses many of the concepts presented in Part I to develop custom trading systems to trade popular markets like US and European stock index futures, forex and commodities.
Contents:
- Intermarket Analysis
- Correlation
- Regression
- International Indices and Commodities
- The S&P 500
- European Indices
- Gold
- Intraday Correlations
- Intermarket Indicators
- Trading System Design
- A Comparison of Fourteen Technical Systems for Trading Gold
- Trading the S&P 500 ETF and the e-mini
- Trading DAX Futures
- A Comparison of a Neural Network and a Conventional System for Trading FTSE Futures
- The Use of Intermarket Systems in Trading Stocks
- A Relative Strength Asset Allocation Trading System
- Forex Trading Using Intermarket Analysis
Intermarket Trading Strategies By Markos Katsanos pdf
