Direct answer
A worked example of “Four Hour” is a step-by-step, numbers-in, numbers-out scenario that demonstrates how someone is using a four-hour timeframe idea. It makes every assumption visible—such as the time unit, the rule you apply, how you measure price movement, and what you treat as fixed versus variable—so another person can reproduce the calculation and check whether the reasoning is internally consistent.
In forex terms, “four hour” usually refers to using a four-hour timeframe for observation or decision-making. A worked example does not predict what will happen next; it only shows what follows from your stated method and assumptions.
Mechanism and definition
A four-hour timeframe is a way to group market movement into candles (or observations) that each represent a fixed time span of four hours. In a worked example, you typically do three things:
- Choose a rule: what you will measure (for example, candle range, percentage change, or a hypothetical position’s profit/loss from a stated entry and exit).
- Fix the measurement details: what “start time” means, whether you use candle closes or highs/lows, and how you compute results (for example, using percentage change or pip difference).
- Separate stable mechanics from variable conditions:
- Stable mechanics are the math and the timeframe definition (what four hours means; how you compute returns from two prices).
- Variable market/provider conditions are things like spreads, execution quality, liquidity, and whether the real market moves as assumed. If you do not model these, your worked example should say so.
Worked example with explicit assumptions
Below is a fully specified numerical example using a generic four-hour observation rule. It is not a trade recommendation.
Assumptions (state these to verify the example):
- We measure movement using percentage change.
- We use two prices that are chosen for illustration only: an “observation start” price of 1.2000 and an “observation end” price of 1.2040.
- The “start” and “end” are the first and last price of a four-hour window. The example does not rely on which exact candle data provider you use.
- We ignore costs: no spread, fees, slippage, or financing effects.
Computation:
- Percentage change = (end − start) / start × 100
- = (1.2040 − 1.2000) / 1.2000 × 100
- = 0.0040 / 1.2000 × 100
- = 0.003333… × 100
- = 0.3333% (approximately)
What this “worked example” demonstrates:
- The four-hour part controls the time grouping of observations.
- The numeric result comes purely from the math of the stated two prices.
- Another reader can independently verify the 0.3333% figure as long as they accept the same assumptions.
Evidence by comparison (showing what changes vs what doesn’t)
To keep this an internal verification exercise, compare two scenarios using the same four-hour framework and the same formula:
Option A (smaller move): start 1.2000, end 1.2010
- Percentage change = (1.2010 − 1.2000) / 1.2000 × 100 = 0.0833% (approx)
Option B (larger move): start 1.2000, end 1.2050
- Percentage change = (1.2050 − 1.2000) / 1.2000 × 100 = 0.4167% (approx)
What stays the same:
- The mechanics: four-hour grouping definition and the percentage-change formula.
What changes:
- The end price, which changes the computed result.
This is the core “worked” value: it shows that the framework and calculations can be checked without claiming that any specific future move is guaranteed.
Limitations and risks (material failure modes)
A worked example can still fail to represent reality if key items are left out or misunderstood. Common limitations include:
- Costs and execution: If you ignore spreads, fees, and slippage, the calculated move may not match a real account outcome.
- Choice of price points: Using close-to-close versus high/low-to-high/low changes the measured movement, even within the same four-hour window.
- Selection bias: If you choose start/end values after seeing the future, the example can become misleading even when the arithmetic is correct.
- Model dependence: A method that works on one small numerical illustration may not generalize; historical relationships do not ensure future results.
- Jurisdiction and product differences: Different providers and account types can affect how trades are executed and how costs are applied, so a generic calculation may not transfer.