Part 7 · Connecting the economy to stocks · Lesson 36
Reading the sector map through interest rates, exchange rates and oil
When interest rates, exchange rates and oil prices all move at once, a single season can't describe it. Load the real data from the Macro Map and read the sector map yourself.
QToday's question
Interest rates are rising, the won is strengthening, and oil is rising. In a case like this, how can you see at a glance which sectors are favored?
So far you have learned, one at a time, how interest rates (Part 3), jobs and consumption (Part 4), exchange rates and exports (Part 5) and oil prices (Lesson 29) shake up sectors. In the real market, though, these forces move at the same time. Some push banks up while others pull them down. In this lesson we load the real data used by the Robin Invest Macro Map into this page and follow, by hand, how several factors are combined into a single sector map.
MAPLearning map for this lesson
We build it up in three steps. At the end of each step, a 'Quick check' lets you test your understanding before moving on.
In Lesson 18 you learned that interest rates can be revenue for some sectors and a cost for others; in Lesson 25, the winners and losers of a weak won; and in Lesson 29, how oil prices reach refiners, airlines and chemicals. Inflation and assets from Lesson 11, and consumer discretionary vs. staples from Lesson 22, come back here too. And in the previous Lesson 35 we looked at the sector clock by phase of the business cycle. This lesson is a hands-on exercise in reading the "Macro Map," which combines all of these relationships into numbers.
- STEP 1 · Core conceptsThe three layers of the Macro Map
Understand the structure of the Macro Map, from factor to impact to score, and read the (−1 to +1) of the six factors.
- STEP 2 · Understanding the mechanismReading one cell of the impact map
Tell apart the theoretical sign in a cell from the , and explain what a cell where the two disagree is saying.
- STEP 3 · Applying itDissecting the environment score and four exercises
Break one sector's into contributions by factor, and see for yourself how the result changes when you switch the .
STEP 1The three layers of the Macro Map
The Macro Map looks complicated, but it is really a three-story building. Let's go up from the ground floor.
An easy analogy · Weather forecast and what to wear
When you choose tomorrow's outfit, you don't look only at the temperature. You check temperature, wind and rain together, think about how each affects your clothes (an umbrella if it rains, a jacket if it's windy), and then decide the final outfit.
The Macro Map works the same way. It measures the "weather" such as interest rates, exchange rates and oil prices (floor 1), organizes how that weather affects each sector (floor 2), and combines the two into an "outfit score" for each sector (floor 3).
The three-layer structure
Floor 1 · Factor state
For each of six factors (rising rates, weak won, rising oil, rising inflation, improving economy, rising exports), it measures from −1 to +1 which way the factor is leaning right now and how clearly.See the current phase →Floor 2 · Impact map
A table of 180 cells: 6 factors × 30 sectors and assets. Each cell holds both the theoretical sign and the correlation coefficient from real data.See the impact map →Floor 3 · Environment score
A score made by multiplying and summing floors 1 and 2. It shows in 5 levels whether the current macro environment is favorable for each sector.See the environment score →See it in a chart: the six factors right now
The chart below is drawn by loading the Macro Map's latest data directly when this page opens. A bar to the right of the center line (blue) means the flow in the direction of the factor's name; to the left (orange) means the opposite flow.
Loading Macro Map data…
Source: Robin Invest Macro Map (interest rates FRED DGS10, exchange rate FRED DEXKOUS, oil FRED DCOILWTICO, inflation FRED CPIAUCSL, jobs FRED PAYEMS·UNRATE, exports Bank of Korea ECOS export value index). Factor states are calculated from the change over the last 3 months and the position within the last 5 years, and update automatically every day.
Here is how it reads using data from October 4, 2026, when this lesson was written. The US 10-year yield was 5.28%, in the top 2% of the last 5 years, so "rising rates" was +0.98, a clear rising-rate trend. USD/KRW fell 12.3% over 3 months, so "weak won" was −0.62, meaning a clear strong-won trend. WTI oil rose 30.7% over 3 months to +0.86, and Korean exports grew 75.8% year over year to +1.00. Inflation (−0.37), on the other hand, was easing in its upward trend, and jobs (−0.24) also showed a cooling trend. The numbers in the chart you see now may have been updated since.
There is one important habit here. Factor names are always written in the "rising" direction. So if the state of "weak won" is negative, read it as a strong won, and if "improving economy" is negative, read it as a slowing economy. If you get confused, recall "a higher exchange rate = a weaker won" from Lesson 23.
Quick checkIf the state of the "rising oil" factor is −0.7, what phase is oil in right now?
STEP 2Reading one cell of the impact map
The floor-2 has as many as 180 cells, but once you can read one cell properly, the rest is just the same method repeated.
Each cell holds two answers
The first is the theoretical sign. Using the principles you have learned so far, it records as +1, −1 or 0 whether, as this factor plays out, the sector is generally helped, hurt or not clearly affected. For example, "rising rates × banks" is favorable (+1) because the loan-deposit spread tends to widen (Lesson 18). "Weak won × semiconductors" is favorable (+1) because dollar sales translate into larger won-denominated profits (Lesson 25).
The second is the answer from real data. Every month from January 2016 to September 2026, it measures with a how much the factor's movement and the sector ETF's monthly return moved in the same direction. Close to +1 means almost always the same direction, close to −1 means almost always the opposite direction, and near 0 means no clear relationship. So that a few extreme months don't sway it, the Macro Map compares ranks (Spearman rank correlation).
Putting the two answers side by side, cells fall into four types: cells where theory and data point the same way, cells where the data relationship is weak, cells where theory is neutral but the data shows a clear relationship, and cells where theory and data are opposite. The last type is the most instructive.
See it in a chart: one factor, 30 sectors and assets
Pick a factor and you see how the 30 sectors and assets relate to it. The cell's background color is the theory (green favorable, red unfavorable, gray neutral), and the number is the actual correlation coefficient. A dotted border marks cells where theory and data are opposite. Try tapping a cell.
Source: Robin Invest Macro Map impact map. The correlation coefficient is the rank correlation between monthly price returns (excluding dividends) from Jan 2016 to Sep 2026 and the change in the factor; ETFs with a short history since listing cover a shorter period. Korean ETFs from Naver Pay Securities, factors from FRED and Bank of Korea ECOS.
Pick "weak won" and tap the semiconductor cell. Theory says favorable (+1), but with the data at the time this lesson was written, the correlation coefficient was −0.29. In months when USD/KRW rose, the semiconductor ETF's average return was −0.03%, and in months when it fell, +4.96%. This is the exact opposite of theory.
Why? In Lesson 24 you learned that one of the typical reasons the won weakens is "the rush into dollars in a crisis." In months when the global economy is shaky and worries about semiconductor demand grow, the won weakens too, so demand worries moved the stock price more than the translation-profit effect. Foreign investors' trading in Lesson 27 pushes in the same direction. It is better to read a mismatched cell not as "the theory is wrong" but as a signal that "a bigger force moved along with this relationship."
Common misconceptions
- "A correlation of −0.29 means a 29% chance of falling?"
- No. A correlation coefficient is not a probability; it is the degree to which two numbers moved in the same direction. Read −0.29 as "there was a weak tendency to move in opposite directions."
- "If a cell is green (favorable), you should buy that sector?"
- A cell looks at only one factor. In a real sector all six factors act at once, and bigger things such as earnings, price level and supply and demand flows matter as well. A cell is raw material for forming questions.
- "A large correlation means cause and effect are certain too?"
- Moving together does not guarantee that one moved the other. As with semiconductors and the won, a third force (the global economy) may have moved both.
Quick checkFor the cell "rising rates × US long-term Treasuries," the theory is unfavorable (−1) and the correlation coefficient is −0.94. What kind of cell is this?
STEP 3Dissecting the environment score and four exercises
Now let's go up to floor 3. If you know how the score is built, you can read the "why" instead of being swayed by a single number.
How the score is calculated
Sector score = Σ (factor weight × factor state × effect) ÷ sum of weights
The effect is a blend of 65% theoretical sign and 35% actual correlation coefficient (a correlation of ±0.3 is converted to ±1). A total of +0.22 or more is favorable, +0.08 or more somewhat favorable, −0.08 to +0.08 neutral, and −0.22 or less unfavorable.
Factor weights are 1.0 for interest rates, 0.9 for jobs, 0.8 for exchange rates and exports, and 0.7 for oil and inflation, so interest rates carry the most weight. As you learned in Part 3, interest rates shake the multiple lever of almost every asset. The formula looks long, but its meaning is simple: add up, in proportion to the strength of each wind, whether the winds blowing hard right now are a tailwind or a headwind for this sector.
See it in a chart: dissecting the environment score
Pick a sector and a scenario. Each bar is the share that one factor adds to the score. To the right (green) is a tailwind, to the left (red) a headwind.
Calculation: the same method as the Robin Invest Macro Map (the Macro Map's score calculation code is used as is). Scenarios are recalculated after swapping the states of some factors for assumed values.
Exercise 1 · Find sectors that benefit in a rising-rate phase
In the STEP 2 chart, pick "rising rates" and look for the green cells. In theory the beneficiaries are four: banks, insurance, US financials (XLF) and the dollar. But looking at the numbers, as of when this lesson was written, the ones with a clear relationship in the data too were insurance (+0.21) and the dollar (+0.23), while banks (+0.09) and XLF (+0.03) had weak relationships. This means that even a theoretical tailwind had other forces mixed in.
Exercise 2 · Dissect the banks' score
In the chart above, pick "Banks" and press "As of now." When this lesson was written, banks were "somewhat favorable" (+0.21). Of the +0.21 score, rising rates alone made +0.15, a strong won (+0.04) and rising oil (+0.03) added a little, and a slowing economy (−0.03) took some away. You need to read not just one score but the reason, "favorable thanks to rates," so that you know in advance the score will turn down if rates turn down.
Exercise 3 · Re-reading through scenarios
With banks still selected, press "Falling rates." The score drops to "neutral," and rate-sensitive growth sectors such as EV batteries rise to the top of the ranking table above. Press "Economic slowdown" and US long-term Treasuries and utilities rise; press "Weak won" and the dollar and shipbuilding rise. Even on the same map, when the direction of the wind changes, the sector ranking is shuffled dramatically. It is as if the sector rotation clock of Lesson 35 were running on numbers.
Exercise 4 · Find cells where theory and data disagree
In the STEP 2 chart, pick "weak won" and look only at Korean sectors. Export sectors that are favorable in theory, such as semiconductors, EV batteries, autos, shipbuilding and defense, all had dotted borders, meaning the data was the opposite. This is because months when the won weakened were mostly months of heavy global-economy worries. When mismatched cells are clustered in one row like this, it means a bigger common force is hiding behind that factor. In the Was it really so? section, you can see only the mismatched cells together.
For stocks, like this: a 10-minute routine once a week
| Order | What to do | Where to look |
|---|---|---|
| 1 | Write down the factors marked "clear" among the six factors | Current phase |
| 2 | Check whether your sector of interest is green, red or dotted in that factor's row | Impact map |
| 3 | Read the top 3 reasons behind your sector's score | Environment score |
| 4 | Switch scenarios and note which change in wind flips the score | Environment score scenarios |
When you see "US 10-year yield surges" in the news, you can sketch in advance that the state of the rising-rate factor will go up, that scores for banks and insurers will rise, and that scores for long-term bonds and growth sectors will fall. Then opening the real map to check whether it matches your expectation is the best practice.
Not always. The environment score is only a reference indicator that organizes whether the macro environment is a tailwind or headwind for a sector; it does not reflect company earnings, price level (P/E) or supply and demand flows. There is also no guarantee that past relationships will repeat in the future. This is not a recommendation to buy or sell any particular stock or ETF.
Quick checkA sector's score is "favorable," but its only top reason is "rising rates." What should you watch most closely going forward?
✓What we learned today
- The Macro Map has three layers: the current state of six factors (interest rates, exchange rate, oil, inflation, jobs, exports) → the impact between factors and sectors → the environment score, made by multiplying and summing the two.
- A factor state is a number between −1 and +1: + means the flow in the direction of the factor's name is showing, and − means the opposite flow. If "weak won" is −0.62, it means a clear strong-won trend.
- One cell of the impact map holds both the theoretical sign learned so far (favorable, unfavorable, neutral) and the actual correlation coefficient measured from monthly data since 2016. A cell where the two are opposite is a relationship where "a force other than the theory was bigger."
- The environment score is the sum of factor weight × factor state × effect. When you look at a score, first look at which factors built it rather than at the single number.
- Changing the scenario changes the ranking dramatically. The score is only a reference indicator summarizing the current direction of the wind; it does not reflect company earnings, price level or supply and demand flows.
If the sector map tells you "which way the wind is blowing," the remaining question is "so, is this stock expensive or cheap?" In the next lesson we take out the P/E from Lesson 1 again and, together with P/B, learn how interest rates change the fair multiple.
Quiz5-question quiz
Pick an answer and it's graded right away with an explanation.
Q1. On the Macro Map, the state of the "weak won" factor is −0.62. What phase is the exchange rate in now?
Factor names are written in the "rising" direction. A negative value means the opposite direction, i.e. a strong-won trend, and since it is below −0.5 it is labeled "clear strong won."
Q2. What two things does one cell of the impact map hold together?
One cell holds the theoretical sign decided from the principles you have learned so far, together with the actual correlation coefficient measured from monthly data since 2016. The cells where the two disagree are the most instructive.
Q3. For a cell like "weak won × semiconductors," where theory said favorable but the data was the opposite, what is the best explanation?
The rush into dollars in a crisis (Lesson 24) brought both a weak won and worries about semiconductor demand at the same time. A mismatched cell is a signal pointing to a "bigger common force."
Q4. Banks' environment score is "somewhat favorable," and most of it was made by "rising rates" alone. What generally happens if you switch to the "falling rates" scenario?
The tailwind that held the score up turns into a headwind, so the score falls with it. This is why, when you look at a score, you should first read "thanks to which factor."
Q5. Which statement about the environment score is NOT correct?
The environment score is only a reference indicator that organizes whether the macro environment is a tailwind or a headwind. It does not reflect earnings, price level or supply and demand flows, and it is not a buy or sell recommendation.
NextTerms · Next lesson · Related tools
A group of companies in similar businesses, divided into categories such as semiconductors, banks and autos.
Interest rateInterest rateThe price of borrowing money. When rates rise, the present value of future earnings falls, which tends to lower stock multiples.
Exchange rateExchange rateThe rate at which the currencies of two countries are exchanged. USD/KRW 1,400 means it costs 1,400 won to buy 1 dollar.
Weak wonWeak wonA rise in USD/KRW, that is, a fall in the value of the won. It is generally favorable for exporters.
Factor stateFactor stateA value, from −1 to +1, showing the recent direction and strength of the six factors on the Robin Invest Macro Map: interest rates, exchange rate, oil, inflation, jobs and exports. Factor names are based on the "rising direction," so a negative value means the opposite flow (e.g. weak won −0.6 = a strong-won trend).
Impact mapImpact mapA part of the Macro Map: a table of 6 factors × 30 sectors and assets, where each cell holds both the theoretical favorable, unfavorable or neutral and the correlation coefficient from real data.
Correlation coefficientCorrelation coefficientA value between −1 and +1 showing how much two numbers moved together. Close to +1 means the same direction, 0 means almost no relationship, and close to −1 means they moved in opposite directions. It reflects only a past relationship and does not imply cause and effect.
Macro environment scoreMacro environment scoreA reference indicator on the Macro Map that sums factor weight × factor state × effect (65% theory + 35% actual correlation) and organizes whether the current macro environment is a tailwind or headwind for a sector in five levels (favorable to unfavorable). It does not reflect earnings, price level or supply and demand flows.
Scenario analysisScenario analysisA method of recalculating the result under the assumption that some factors move differently (e.g. falling rates, economic slowdown). It is used to check which assumptions today's conclusion leans on.
Priced inPriced inA state in which something expected to happen is already reflected in prices such as stock prices or interest rates. If things happen as expected, prices do not move much.
Put what you learned to use right away
Macro Map→Macro Map · Current phase→Impact map→Was it really so?→Environment score→This is educational material and not investment solicitation. There is no guarantee that past relationships will repeat in the future.