Intermarket analysis: the channels through which interest rates and commodities reach a share price

Intermarket analysis reads the price of an instrument through the state of other markets: interest rates, government debt, currency, commodities and fund flows. It does not produce a forecast and does not replace an entry signal. Its job is to narrow the set of plausible hypotheses and to explain why a familiar relationship has suddenly stopped working. In the Russian market the chain is short, which makes it testable. A key rate decision shifts the OFZ curve. The curve changes the required return on equities and the flows of money between debt, deposits and funds. Commodity prices and the rouble exchange rate feed through differently into the balance sheets of exporters and of companies that depend on domestic demand.

A channel, not a correlation

Intermarket analysis begins where you can name a transmission mechanism rather than point to two charts that happen to move together. Our market has only a few such mechanisms, and they can be described in words rather than found by curve-fitting.

The first is the discount rate. The yield on risk-free debt sets the hurdle against which every cash flow is measured. When the short end of the curve moves up, money becomes more expensive for companies carrying floating-rate debt, and the present value of distant cash flows falls. Growth stories feel this most, mature dividend payers least.

The second is currency translation. An exporter earns revenue in foreign currency but pays its costs and taxes in roubles, so a weaker rouble widens its margin mechanically, without any improvement in operations. For a company that relies on imported equipment and a domestic regulated tariff, the same exchange rate works in the opposite direction.

The third is competition for capital. When debt and deposits offer a yield comparable to the expected return on equities, with lower volatility, money leaves equities even though company reports have not deteriorated. You can see this in fund flows and in how dividend stocks behave ahead of payouts. The nearest record dates are:

The fourth is the cost of leverage and risk appetite. Expensive money squeezes margin positions, and under stress correlations between asset classes converge: there are fewer "defensive" corners than the diversification model assumed.

The Russian chain: what responds to what

In practice the chain runs as follows. First comes the monetary policy block: the rate meeting, the central bank's guidance and inflation expectations. Next comes the reaction of the government bond curve: the short end responds to the rate itself, the long end to views on its future path and on risk. Then come equities, with different sectors moving in different directions. Banks react to the shape of the curve and the quality of their loan books, developers to the cost of mortgage funding, and exporters more to commodities and the exchange rate than to the rate.

A separate, external layer consists of commodity prices, logistics and payment restrictions. Since 2022 this layer has no longer passed directly into the rouble price: discounts, currency controls and changed trade routes now sit between the global quote and actual revenue. A relationship learned before the regime change is dangerous here precisely because it still looks familiar.

The calendar for this work is made up of earnings releases and corporate events: financial reports, the events calendar and the news feed.

Where intermarket logic breaks down

The usual ways of fooling yourself: mistaking a common driver for a causal link (both markets are reacting to the interest rate, not to each other); choosing a lag after the fact to fit a result that is already known; carrying a relationship over from an index to a single stock with a different revenue and debt structure; drawing conclusions from markets with different trading hours and treating the divergence as a signal. It also helps to remember the limits of a neighbouring tool: technical analysis describes price behaviour within a market, not flows between markets — what it cannot do is covered in the limits of technical analysis.

Piling up relationships without ever reaching a decision is a condition of its own, and it has a name: analysis paralysis. The more markets you bring in, the greater the chance that there will always be one that contradicts the trade.

Turning an observation into a rule

Step 1 — write the hypothesis down in words before looking at the data: which market leads, which follows, through what mechanism, with roughly what lag and in which regime it holds.

Step 2 — test it on a period you did not use when formulating it, and separately on stretches where the regime changed. The testing methodology is set out in the piece on quantitative analysis; how robust the conclusion is to shifts in the lag and the window is a matter of sensitivity analysis.

Step 3 — spell out exactly what would refute the relationship, and turn it into scenarios: scenario analysis is more useful than a point forecast because it sets out an action for each branch from the start. For checks against balance sheets and financial statements, turn to fundamental analysis; for definitions of terms, see the glossary.

A fair caveat: the site has no ready-made intermarket correlation metric, so one cannot be inserted with a directive. Relationships have to be calculated independently from the data series in the equities and debt sections — and recalculated from scratch after every regime change rather than inherited from the previous cycle.