Intermarket Trading Strategies

Markos Katsanos

• Publisher: Wiley
• Year: 2010
• Print ISBN:
  9780470758106
• Edition: 1
• eBook ISBN:
  9781119995906
• Topic: Business
• Subtopic: Finance
• Index: Business

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.

Part I

1

Intermarket Analysis

It’s not that I am so smart; it’s just that I stay with the problems longer.

-Albert Einstein

The basic premise of intermarket analysis is that there is both a cause and effect to the movement of money from one area to another. Consider, for example, the price of gold and the dollar. Because gold is denominated in US dollars, any significant fluctuation of the dollar will have an impact on the price of gold, which in turn will affect the price of gold mining stocks.

The strength and direction of the relationship between two markets is measured by the correlation coefficient which reflects the simultaneous change in value of a pair of numeric series over time.

Highly positively correlated markets can be expected to move in similar ways and highly negatively correlated markets are likely to move in opposite directions. Knowing which markets are positively or negatively correlated with a given market is very important for gaining an understanding of the future directional movement of the market you propose to trade.

Advancements in telecommunications have contributed to the integration of international markets. Sophisticated traders are starting to incorporate intermarket analysis in their trading decisions through a variety of means ranging from simple chart analysis to correlation analysis. Yet the intermarket relationships hidden in this data are often quite complex and not readily apparent, while the scope of analysis is virtually unlimited.

But what is intermarket analysis?

The financial markets comprise of more than 500 000 securities, derivatives, currencies, bonds, and other financial instruments – the size of a small city. All interact with each other to some extent and a seemingly unimportant event can cause a chain of reactions causing a landslide of large-scale changes to the financial markets.

Consider the following example: Let’s suppose that the Bank of Japan decides to buy dollars in order to push the yen down. As a result Japanese stock prices will go up as a weak yen will help boost profits for exporters. A sharp rise of the Nikkei will in turn have a positive effect on all other Asian markets. The next morning European markets, in view of higher Asian markets and in the absence of other overnight news, will open higher. This will in turn drive US index futures higher and boost US markets at open. In addition lower yen prices will encourage the “yen carry trade”, i.e. borrowing yen at lower or near zero interest rates and buying higher yielding assets such as US bonds or even emerging market equities, which in turn will push bonds and equities higher. On the other hand, a scenario for disaster will develop if the opposite happens and the yen rises sharply against the dollar. This will cause a sharp unwinding of the “yen carry trade”, triggering an avalanche of sharp declines in all financial markets.

But what might cause the yen to rise? The following is a possible scenario: As we head into the economic slowdown, the carry trade money that has flowed into risky cyclical assets is likely to fall in value. As a result, speculators in these assets will cut their losses, bail out and repay their yen debts. This is a scenario for disaster because when the yen rebounds against the dollar, it often snaps back very fast and carry trades can go from profit to loss with almost no warning.

A popular chaos theory axiom (known as the “butterfly effect” because of the title of a paper given by the mathematician Edward Lorenz in 1972 to the American Association for the Advancement of Science in Washington, D.C. entitled “Predictability: Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?”) stipulates that a small change in the initial condition of the system (the flapping of the wing) causes a chain of events leading to large-scale phenomena. Had the butterfly not flapped its wings, the trajectory of the system might have been vastly different.

A financial series would appear to be chaotic in nature, but its statistics are not because, as well as being orderly in the sense of being deterministic, chaotic systems usually have well defined statistics.

The rapid progress of global communications has contributed to the integration of all international financial markets as the world has gotten smaller due to the ability to communicate almost instantaneously. Relationships that were dismissed as irrelevant in the past cannot be ignored any more as the globalization of the markets contributes to a convergence of formerly unrelated markets.

Take a look at the comparison chart in Fig. 1.1. The S&P 500 is depicted with a bold thick line. The second one however is not even a stock index. It is the Japanese yen exchange rate (USD/JPY).

The next composite chart in Fig. 1.2 is of three stock indices. The first two (depicted with a bar chart and thick line) are of the S&P 500 and the Nasdaq Composite respectively. The third chart (thin line) is the Athens General Index which, surprisingly, correlates better with the S&P 500 than its compatriot, the Nasdaq Composite.

Figure 1.1 Comparison chart of the S&P 500 (in bold with the scale on the right Y-axis) and the yen (USD/JPY) (with the scale on the left axis) from June 2006 to January 2008.

The above examples are included to illustrate that the integration of global markets can extend beyond the obvious relations.

I often hear CNBC guests suggesting investing in international markets as a means of diversifying one’s portfolio away from the US equity markets. Although some emerging markets may have relatively medium to low correlation with US markets, one important question to ask is whether diversification works when it is needed most. Evidence from stock market history suggests that periods of negative shocks and poor market performance were associated with high, rather than low, correlations. The events of 21 January 2008 are still fresh in my mind, when a 2.9 % correction in the S&P 500 was followed the next day by a devastating 7.2 % drop in the German DAX, wiping out nine months of profits in a day. Emerging markets sunk even more with the Jakarta Composite falling more than 12 % in two days while Brazil’s Bovespa lost more than 8.5 %. Indeed, investors who have apparently relied upon diversification in the past to protect them against corrections of the market have been frequently disappointed.

Figure 1.2 Weekly comparison chart of the S&P 500 (thick line with the scale on the right Y-axis), the Nasdaq (in bold with the scale on the left axis) and the Greek Athens General Index (ATG) from 1999 to 2008.

The only effective method of diversifying one’s portfolio is by including asset classes with low or negative correlation to stocks such as cash, foreign exchange or commodities. Whatever the relationship is – leading, lagging, or divergent responses to economic conditions – a strong negative correlation coefficient between two markets is a suggestion that these markets will move against each other sometime in the future. And, of course, the higher the absolute value of the coefficient of correlation, the higher the diversity of their performances.

Although intermarket analysis has been classified as a branch of technical analysis, it has not been embraced fully by analysts. The majority of traders continue to focus on only one market at a time and they tend to miss the forest for the trees. No market exists in a vacuum, and traders who focus on the bigger picture portrayed through all international markets tend to be the ones that deliver be...

Table of contents

• Title Page
• Copyright Page
• Dedication
• Acknowledgments
• Introduction
• Part I
• Part II
• Appendix A - MetaStock Code and Test Specifications
• Appendix B - Neural Network Systems
• Appendix C - Rectangles
• Glossary
• ABBREVIATIONS
• Bibliography
• Index