Micro vs Macro – what a trader really cares about

Economics splits into micro and macro, but for a trader that split is not academic. They are two different sources of risk and two different decision horizons. Microeconomics tells you what happens inside a company, a sector, and the order book. Macroeconomics tells you what happens to the cost of money, consumer sentiment, and the direction of capital flows. If you do not tell one from the other, you will explain a move in the interest rate with one company’s quarterly results – and the other way round.

The goal of this lesson is to build a map: which data belongs to micro, which belongs to macro, how they overlap, and which of them really affects your trading plan. Without that map every piece of information looks important, and in trading information without context is noise.

Microeconomics: what affects one company, not the whole market

Micro is the analysis of individual entities: the consumer, the company, the sector. For an equity and ETF trader, micro shows up in:

• Company financial results: revenue, margin, earnings per share, debt.
• Business model: pricing power, dependence on a single supplier, sensitivity to the price of a commodity.
• Competitor behaviour: the entry of a new player, a price war, sector regulation.
• Market microstructure: spread, order book depth, volume, a liquidity gap.

Micro is your main filter when you select an instrument. A technology ETF can rise on a macro wave, but if 30% of its holdings are companies with no cash flows, your micro risk is high.

Macroeconomics: what affects every company at once

Macro is aggregates: inflation, unemployment, interest rates, the exchange rate, the trade balance. Macro changes the cost of money over time, and that changes the valuation of every asset.

Three channels through which macro reaches your portfolio:

1. The interest rate channel: higher rates = a higher discount rate in the valuation model. It lowers the present value of future earnings.
2. The demand channel: a strong consumer = higher revenue for cyclical companies.
3. The risk channel: geopolitical tension, a liquidity crisis – capital runs to assets considered safer.

A trader who trades only micro will be surprised by a central bank decision. A trader who looks only at macro will buy a weak company in a strong economy.

Table: how information splits into micro and macro

How to measure it and put it into one picture

You need two simple measures so that you do not lose the proportions.

The formula for the risk split:

Total_Risk = Macro_Risk + Micro_Risk + Execution_Risk

Macro_Share = Rate_Sensitivity * Rate_Volatility
Micro_Share = Sector_Beta * Company_Volatility

In practice: if you trade an S&P 500 ETF before a Fed decision, your Macro_Share is 80-90% of the whole risk. If you trade the results of a small company on a day with no macro data, Micro_Share is 80%.

The second measure – an information filter:

Information_Value = (Impact_on_Thesis * Probability_of_Plan_Change) / Time_Needed_for_Analysis

If you spend 2 hours analysing a micro news item that has a 5% chance of changing your plan, the Information_Value is low. Reject it.

When the plan says DO NOT TRADE

1. You mix levels of analysis: you explain a move in an index with one company (“Apple fell, so the S&P will fall”) or a move in one company with a Fed decision alone. That is a category error.
2. You have conflicting signals: macro says risk-off (rising yields) and you want a long on micro – a growth company with negative cash flows. A plan requires consistency, not hope.
3. No data to judge with: you do not know whether the market is reacting to micro or macro today. Your calendar has CPI and 20 company results at the same time. If you cannot attribute the dominant factor, you have no edge.
4. You trade an instrument whose micro you do not understand: a leveraged ETF, a company from another accounting system, a market with different liquidity. Microstructure is part of micro – ignoring it is trading without knowing your costs.

Mistakes that cost the most

1. Overrating micro in a macro world. After a rate decision all correlations go to 1. Your brilliant fundamental analysis of a company will not protect you from a 2% gap across the whole market.

2. Ignoring micro when trading macro. “I will buy any technology ETF, because rates will fall”. The difference between QQQ and an ETF of random growth companies can reach 40% in a year under the same macro.

3. The narrative effect. Micro gives great stories (“a revolutionary product”), macro gives boring numbers. The brain prefers stories. A trader pays for it with a position in a company with no revenue, only because the narrative was convincing.

4. Analysis without a measure of exposure. You do not measure how much macro risk you hold in the portfolio. Example: you have 3 long positions, all sensitive to rates (technology, real estate, small caps). You think you are diversified. You are not – you have one large position on falling yields.

Measurable exercise [15 minutes]

Goal: To build a Micro/Macro filter for your watchlist for this week.

Steps:

1. Pick 3 instruments you are watching (e.g. an ETF on the WIG20, an ETF on the Nasdaq, one company).
2. In a table, note for each of them 2 micro factors and 2 macro factors that could move the price this week. Use the calendar: company results = micro, CPI/NFP/Fed data = macro.
3. Rate the weight of each factor for your thesis on a scale of 1-5.
4. Calculate: Macro_Sum vs Micro_Sum. Write down which factor dominates on a given day.

Pass criterion: You have a 3x4 table with weights and you can point to one day this week on which macro dominates and one on which micro does. If you cannot – you do not trade on those days.

Workshop_Table:
Instrument | Micro_Factor_1 (Weight) | Micro_Factor_2 (Weight) | Macro_Factor_1 (Weight) | Macro_Factor_2 (Weight) | Dominant
... | ... | ... | ... | ... | ...

Check yourself

1. Company A reported a great EPS, but on the same day CPI came in above forecasts and the market falls 2%. Where does the dominant risk come from? a) Micro only, because EPS was good b) Macro – the cost of money overshadowed the good micro result c) It is a buy signal, because the market is wrong

Correct: b) On the day a major macro indicator is published, the interest rate channel dominates a single earnings result.

2. Which piece of information is micro? a) Wage growth in the US services sector b) A change in the WTI oil price c) The gross margin of company X fell from 45% to 38% because of higher logistics costs

Correct: c) It is a problem specific to one company’s business model.

3. You have 4 long positions in growth companies. What should you calculate before the next long signal? a) The average EPS of the portfolio b) Total exposure to macro risk (sensitivity to rates) c) The number of Twitter followers

Correct: b) It is the same risk factor in different disguises.

Frequently asked questions

Do I even need to know micro as a day trader? Yes, if you trade stocks – spread, volume, and the reaction to news are micro, and they decide your slippage. If you trade only indices, micro matters less, but market microstructure (liquidity at 14:30 Polish time around data releases) is still critical.

Can I trade macro only and ignore companies? You can, by choosing broad ETFs (e.g. on whole indices). But even then you have to understand what that ETF holds – concentration in 7 companies is hidden micro risk.

How do I know what matters more on a given day? From the calendar and from the market’s reaction. If at 14:30, after CPI data, all sectors move in the same direction, macro dominates. If only one sector reacts to regulatory news, micro dominates.

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This is not investment advice. It is educational material about measuring risk and categorising information.

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