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Lernen / Market Basics / Reading the Numbers

Day, Week, YTD, YoY: Reading Percentage Moves

6 Min. Lesezeit Aktualisiert Aug 10, 2026

The percentage-change columns on a market data table — Day, Week, Month, YTD, and YoY — each measure a different time window and answer a different question about how a price has moved. Understanding what window each column covers, and what can distort it (especially base effects in year-over-year figures), helps readers interpret data accurately rather than jumping to the wrong conclusion. A worked example table and plain-English explanations make each column easy to decode.

Why Percentage, Not Points?

When you glance at a market quote, the raw price level tells you one thing. The percentage change tells you something more useful: how big that move actually was, relative to where the price started. A ten-point move in a stock priced at $20 is enormous — a 50% swing. The same ten-point move in a stock priced at $2,000 is barely a rounding error.

Percentage change strips away the difference in scale and lets you compare apples to apples. That is why the data tables on this site — whether you are browsing commodities, currencies, crypto, or stocks — always show percent columns alongside the price level.

What Each Column Measures

Each percent column answers a specific question. They are not interchangeable.

Day (Daily Change)

The Day column shows how much the price has moved since the previous session's official closing price — or, during live trading, from that close to the current moment. It answers: What happened today? Traders watching short-term momentum typically keep this column front and center, because it reflects the freshest information: a surprise earnings report, a central bank statement, or a geopolitical headline.

Week

The Week column measures the change over the last five trading days (rolling, not necessarily a Monday-to-Friday window). It answers: How has the trend looked over this week? A single volatile day can dominate a daily reading but look modest when averaged into a week of mixed sessions.

Month

The Month column covers roughly the last 21 trading days. It answers: What is the medium-term direction? Economists and analysts often look here to filter out the noise of daily swings and judge whether a move is building into something sustained.

YTD — Year to Date

YTD (year to date) measures the change from the first trading day of the current calendar year to now. It answers: How has this asset performed since January? YTD is a natural benchmark because it resets every January, matching how many institutions report performance. The catch: early in January, YTD and the daily change are nearly identical; by December, YTD can paint a very different picture from the most recent weeks.

YoY — Year over Year

YoY (year over year) compares today's price to the price on the same calendar date twelve months ago. It answers: How does this moment compare to the same moment last year? This is the column that shows up most in economic reporting — Consumer Price Index inflation, for instance, is almost always quoted year over year to remove seasonality (the predictable rhythm of prices that rises and falls at the same time each year). YoY is powerful, but it comes with a well-known trap explained below.

The Base-Effect Trap

The base effect is the single biggest source of misreading in year-over-year figures. The idea is simple: your percentage change depends not just on where you are today, but on where you started — your base. If last year's base was unusually low because of a crash or a shock, this year's number will look enormous even if the recovery has been ordinary.

A vivid real-world case: oil prices turned briefly negative in April 2020, an extraordinary collapse in demand caused by pandemic-era lockdowns. When prices recovered over the following twelve months, the year-over-year percentage gains looked historic — not because anything dramatic happened in 2021, but because the starting point (the base) was so extreme.

A large YoY number can mean "things are surging now" — or it can mean "things were terrible this time last year." Always ask what was happening twelve months ago before drawing conclusions.

The same logic applies to GDP growth and inflation readings. Economists explicitly flag base effects when interpreting data releases on the economic calendar, precisely because a high YoY print can reflect last year's weakness rather than this year's strength.

Compounding: The Asymmetry of Losses and Gains

One of the most counterintuitive facts in finance is that percentage losses and gains are not symmetric. If something falls 50%, it takes a 100% gain just to get back to where it started — because the 100% gain is calculated on the new, lower base.

Suppose an asset is priced at $100 (hypothetical example). A 50% drop takes it to $50. To recover from $50 back to $100, the price must double — that is a 100% gain. The math works like this:

  • Loss of 50%: $100 × (1 − 0.50) = $50
  • Gain needed to recover: ($100 − $50) ÷ $50 = 100%

This asymmetry is why market commentators talk about drawdown — the peak-to-trough decline — as a key measure of risk. A 20% loss needs only a 25% gain to recover. A 50% loss needs 100%. A 75% loss needs 300%. The deeper the hole, the harder the climb. This is the basic intuition behind compounding, and it is why percentage-change columns for assets with high volatility (such as those in the crypto market) can look dramatic in both directions without an asset actually returning to its prior peak.

Worked Example: Reading a Percent Table

The table below is entirely hypothetical — invented numbers used purely to illustrate what each column is telling you.

Asset (Example) Day % Week % Month % YTD % YoY %
Commodity A +2.1% +1.4% −3.2% +8.5% +42.0%
Commodity B −0.3% +3.8% +5.1% −12.0% −6.5%
Currency Pair C +0.1% −0.5% −1.2% +2.0% +1.1%

Reading Commodity A: today's session is positive (+2.1%), but zoom out and the past month is actually down (−3.2%) — so the daily move is bouncing off a recent downtrend. The YoY of +42.0% looks dramatic, but without knowing whether last year's price was depressed by a supply shock or demand collapse, that number alone tells an incomplete story. This is the base-effect question in practice.

Reading Commodity B: the daily move is nearly flat (−0.3%) and this week is positive (+3.8%), but YTD is deeply negative (−12.0%). That pattern — short-term stabilization within a longer-term decline — is something traders typically watch closely when reading price charts. The recovery may be real, or it may be a brief pause in a continuing slide.

Currency Pair C shows the tight percentage moves typical of major currency markets, where a 1%–2% annual move in a major pair can be significant. Percentage columns help communicate that even small-looking numbers carry real weight depending on the asset class.

Putting It Together

Each percent column answers a different question. The Day column is for today's news. Week and Month filter noise into trend. YTD is a calendar-year scorecard that resets every January. YoY is the broadest context — but the most vulnerable to base effects, so always ask what was happening twelve months prior.

Percentage change beats raw point moves for cross-asset comparison. And the math of compounding means losses are harder to recover from than their mirror-image gain would suggest — a 50% drop always requires a 100% rise to get back. Understanding these mechanics is foundational to reading any data table on this site, from bonds to economic indicators.

For a deeper look at how individual quotes are structured — what the bid, ask, and settlement figures actually mean — see How Market Quotes Work. To understand how these percentage moves show up visually on a chart, Reading Price Charts picks up from here.

Häufig gestellte Fragen

What is the difference between YTD and YoY percentage change?
YTD (year to date) measures the change from the first trading day of the current calendar year to today, resetting every January 1. YoY (year over year) measures the change from the exact same date twelve months ago, which stays useful for spotting trends across calendar years and for removing seasonal patterns from economic data like inflation.
Why does a 50% loss require a 100% gain to break even?
Percentage gains and losses are calculated on different bases. If an asset falls 50% from $100 to $50 (hypothetical), the recovery gain is calculated on the new lower price of $50 — so you need the full $50 back, which is 100% of $50. This asymmetry means deep losses are proportionally much harder to recover from than they were to incur.
What is a base effect, and why does it distort year-over-year figures?
A base effect occurs when the starting point of a year-over-year comparison was itself unusually high or low, making the resulting percentage change misleading. For example, if prices collapsed to very low levels last year because of a crisis, this year's normal price will produce an enormous YoY gain — not because conditions are exceptional now, but because last year's base was so depressed.
Why do currency percentage moves look smaller than commodity or crypto moves?
Major currency pairs trade in a deep, highly liquid global market and are anchored by relatively stable economic fundamentals, so daily and even annual moves tend to be fractions of a percent to low single digits. Commodities and cryptocurrencies have thinner markets and more volatile supply-and-demand drivers, which produces much larger percentage swings — making the percent column essential for comparing moves across these very different asset classes.
Nur zu Bildungszwecken — keine Anlageberatung oder Empfehlung. Märkte sind mit Risiken verbunden; die in den Beispielen gezeigten Zahlen dienen der Veranschaulichung.

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