A Holistic View of the Market: Intermarket Analysis with Cumulative Delta
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Financial markets do not exist in a vacuum. They are interconnected in a complex web of relationships, with the movements of one asset class often influencing the movements of another. The study of these relationships is known as intermarket analysis. By understanding how different asset classes, such as equities, bonds, commodities, and currencies, interact with each other, traders can gain a more holistic view of the market and anticipate major shifts in the economic landscape. While traditional intermarket analysis relies on the correlation of price, a more nuanced and effective approach is to use Cumulative Volume Delta (CVD) to correlate the order flow between different asset classes. This article will explore the principles of intermarket analysis and the application of CVD in this fascinating field.
The Principles of Intermarket Analysis
Intermarket analysis is based on the idea that the global financial system is a single, interconnected entity. A change in one part of the system will inevitably have an impact on other parts. For example, a rise in the value of the US dollar will make US exports more expensive, which can hurt the earnings of multinational corporations and lead to a decline in the stock market. Similarly, a rise in interest rates will make bonds more attractive relative to stocks, which can lead to a flow of capital out of the equity market and into the bond market.
Using CVD to Correlate Asset Classes
While the correlation of price can provide some insights into the relationships between different asset classes, it can often be misleading. Price can be influenced by a variety of factors, including news events, sentiment, and algorithmic trading. A more direct and reliable way to correlate asset classes is to use CVD. By comparing the CVD of two different asset classes, traders can see if the same underlying buying or selling pressure is driving both markets. For example, if the CVD of the S&P 500 is rising, and the CVD of crude oil is also rising, it is a sign that there is broad-based risk-on sentiment in the market.
The Mathematics of Intermarket Correlation
The correlation between the CVD of two different asset classes can be calculated using the same formula as for the correlation between price and CVD:
Correlation(CVD1, CVD2) = Cov(CVD1, CVD2) / (Stdev(CVD1) * Stdev(CVD2))
Correlation(CVD1, CVD2) = Cov(CVD1, CVD2) / (Stdev(CVD1) * Stdev(CVD2))
Where:
Cov(CVD1, CVD2)is the covariance of the CVD of the two asset classes.Stdev(CVD1)is the standard deviation of the CVD of the first asset class.Stdev(CVD2)is the standard deviation of the CVD of the second asset class.
A high positive correlation indicates that the two asset classes are being driven by the same underlying order flow, while a negative correlation indicates that they are being driven by opposing order flow.
Identifying Leading and Lagging Indicators
Intermarket analysis can also be used to identify leading and lagging indicators. A leading indicator is an asset class that tends to move before another asset class. For example, the bond market is often considered to be a leading indicator for the stock market. A decline in bond prices (and a corresponding rise in interest rates) can be a sign of a future decline in the stock market. By using CVD, traders can get an even earlier signal. If the CVD of the bond market starts to decline while the CVD of the stock market is still rising, it can be a sign of a potential top in the stock market.
Developing a Global Macro Trading Strategy
By combining the principles of intermarket analysis with the power of CVD, traders can develop a sophisticated global macro trading strategy. This involves identifying the key intermarket relationships that are driving the market and then using CVD to time entries and exits. For example, a trader might notice that there is a strong positive correlation between the CVD of the Australian dollar and the CVD of copper. This is because Australia is a major exporter of copper. If the trader sees a strong rise in the CVD of copper, they might anticipate a corresponding rise in the Australian dollar and take a long position.
Example Data Table
| Date | S&P 500 CVD | US 10-Year Bond CVD | Correlation (30-day) |
|---|---|---|---|
| 2023-01-01 | 10,000 | -5,000 | -0.8 |
| 2023-01-02 | 12,000 | -6,000 | -0.85 |
| 2023-01-03 | 15,000 | -7,000 | -0.9 |
| 2023-01-04 | 13,000 | -5,000 | -0.8 |
| 2023-01-05 | 11,000 | -4,000 | -0.75 |
In this example, there is a strong negative correlation between the CVD of the S&P 500 and the CVD of the US 10-Year Bond. This is a classic risk-on/risk-off relationship. When the CVD of the S&P 500 is rising, the CVD of the bond market is falling, as investors are selling safe-haven assets and buying riskier assets.
By adopting a holistic, intermarket perspective, traders can gain a significant advantage in the market. The ability to see the big picture and to understand how the different pieces of the global financial puzzle fit together is a hallmark of the truly professional trader. The next article in this series will provide a practical guide to building a trading plan around the principles of Cumulative Delta Volume Profile Composite Analysis. ""