Direct answer: what a worked example of a downtrend is
A worked example of a downtrend is a fully specified scenario where you list a sequence of swing highs and swing lows and then check whether each new swing high is lower than the last one, and each new swing low is also lower. In plain terms: the market is making progressively lower turning points. A typical worked example must also state how you define “swing,” because different definitions can change whether the sequence counts as a downtrend.
Mechanics: definition and the step-by-step logic
Downtrend (concept): A price series is in a downtrend when it forms a sequence of lower swing highs and lower swing lows.
Key term—swing high / swing low: A swing high is a local peak (a turning point) and a swing low is a local trough (another turning point). There is no single universal rule for identifying swings; common approaches depend on a chosen timeframe and a method for detecting local maxima/minima.
How the worked example works (the test):
- Choose a timeframe (or at least a rule for grouping observations).
- Produce an ordered list of swing points (highs and lows) in time.
- Check two conditions:
- Every new swing high is lower than the previous swing high.
- Every new swing low is lower than the previous swing low.
- Treat any break of either condition as evidence that the downtrend characterization may no longer hold (or may be ambiguous).
Evidence / worked example (numbers and assumptions)
Below is one self-contained numerical scenario. Assumptions are explicit so you can verify the logic without any live data.
Assumptions
- We observe price once per day: Day 1, Day 2, …, Day 10.
- We do not assume any real market instrument; this is a hypothetical price path.
- We define swing points using a simple, fixed rule for this example: a day is a swing high if it is higher than the immediately previous and next day; a day is a swing low if it is lower than the immediately previous and next day.
- We will label only swing highs/lows found by that rule. If a day does not qualify, it is ignored.
Hypothetical daily prices
Day 1: 105 Day 2: 107 Day 3: 103 Day 4: 100 Day 5: 102 Day 6: 98 Day 7: 99 Day 8: 95 Day 9: 96 Day 10: 94
Identify swing highs and swing lows using the rule
- Swing highs: Day 2 (107 is higher than Day 1=105 and Day 3=103); Day 5 is 102 (higher than Day 4=100 and Day 6=98); Day 7 is 99 (not a swing high because Day 6=98 and Day 8=95 makes 99 higher than both, but it is also higher than neighbors, so it does qualify as a swing high under our rule).
- Swing highs: (Day 2: 107), (Day 5: 102), (Day 7: 99)
- Swing lows: Day 3 (103 is lower than 107 and 100); Day 4 (100 is lower than 103 and 102); Day 6 (98 is lower than 102 and 99); Day 8 (95 is lower than 99 and 96); Day 10 cannot be a swing low because it lacks a “next” day in the rule.
- Swing lows: (Day 4: 100), (Day 6: 98), (Day 8: 95)
(Notice Day 3=103 is also a swing low under the rule, but to keep the downtrend test clean we can use the most recent swing low before the next swing high as the “effective” swing low. This is another measurement choice; your definition should be stated.)
Apply the downtrend test
- Lower swing highs check:
- 107 → 102 → 99 : each is lower ✅
- Lower swing lows check (using 100, 98, 95):
- 100 → 98 → 95 : each is lower ✅
Conclusion for this scenario: Under the stated swing-identification rule, the price path exhibits a downtrend because it produces sequential lower swing highs and lower swing lows.
Limitations and risks (what can go wrong)
- Swing detection is ambiguous: Different swing rules (e. g. , using a larger neighborhood than one day, or requiring a minimum percentage move) can change which points you count. That can turn “downtrend” into “no clear downtrend. ”