No Market Is an Island: The Core Premise of Intermarket Analysis
No market operates in a vacuum. This is especially true in today's global, 24-hour electronic trading environment, where what happens in one market can quickly influence what happens in related markets. A trader watching a single instrument may see an unexplained move, only to discover later that a shift in another market — a currency, a commodity, or a bond market — was the underlying trigger. The interconnected nature of modern markets means that price action is rarely self-contained. Many traders naturally review a market's historical prices to judge how its past performance might foreshadow its future direction. That vertical, single-market view remains useful. But it is incomplete. Traders also need to look horizontally across other markets to assess how price changes there might affect the market they are trading. For example, movements in interest rates, commodity prices, or the U.S. dollar can ripple into foreign exchange pairs, equity indices, and fixed income markets. The relationships are not always obvious, but they are persistent enough to matter. Intuitively, most traders understand that markets are connected. An event that affects one market can produce effects elsewhere. Yet since the 1970s, when the author first entered the industry, many traders have continued to rely on single-market analysis tools and on information sources immediately at hand. The problem was not a lack of awareness that markets interact; it was the lack of a practical way to quantify those relationships so they could be used in day-to-day decision-making. Since the mid-1980s, research has focused on developing quantitative methods for intermarket analysis. Importantly, this approach is not a complete break from traditional single-market technical analysis, nor is it meant to replace it. Instead, it extends traditional technical analysis into the globally interdependent economic and financial environment of today. In the foreign exchange market in particular — which provides a pricing basis for many other markets — a method that reflects intermarket relationships in some form is essential. A central research question is which markets influence each other most, and how strongly.
From Intuition to Quantification: The Development of Intermarket Analysis
For a long time, traders and analysts recognized in a general way that markets were related. The difficulty was converting that general awareness into something measurable and actionable. Knowing that markets are connected is not the same as knowing how much a change in one market tends to affect another, or which market is the leader and which is the follower. Quantification is what turns a vague observation into a tool that can inform trading decisions. Beginning in the mid-1980s, research began to focus on creating quantitative methods for cross-market analysis. The goal was not to abandon the established tools of single-market technical analysis but to extend them. Traditional tools such as trendlines, moving averages, and momentum indicators describe the internal condition of one market. Intermarket analysis adds a second dimension: the external context created by related markets. Used together, they can offer a more complete picture than either approach alone. This extension matters most in markets that serve as pricing references for others. The foreign exchange market is a prime example. Because currencies underpin the relative value of assets across borders, shifts in exchange rates can influence commodity prices, bond yields, and equity valuations. A trader working in FX, or in any market sensitive to currency moves, benefits from a framework that explicitly accounts for cross-market effects rather than treating the target market as an isolated system. Another important line of research involves ranking markets by influence. Not all markets matter equally to a given target market, and the degree of influence can change over time. Some markets consistently act as drivers, while others are mostly responders. Identifying which markets are most influential, and measuring the strength of those links, is a core part of the intermarket approach. This is a more demanding task than simple pairwise comparison, because it requires handling several markets at once and allowing for relationships that shift as economic conditions evolve.
