Straight answers to the questions traders actually search: liquidity sweeps, opening range breakouts, volume profile, supply and demand, position sizing and psychology.
A liquidity sweep is when price drives through an obvious swing high or low to trigger the cluster of stop orders sitting there, then reverses. The stop-run is not a failure of the level — it is the mechanism. Institutions use that flood of triggered orders as the liquidity to fill their own opposite position.
Because your stop was where everyone else's was — just beyond an obvious swing point. That cluster is the liquidity a large order needs to get filled. The fix is not a wider stop; it is placing the stop beyond the swept wick rather than at the level itself.
Watch the close, not the wick. A genuine break holds outside the range and leaves a fast displacement move behind it. A fake break spikes through and closes back inside within the same candle, with no shift in market structure afterwards.
Mark the swing high or low that is obvious on a 6-hour lookback — that is where stops sit. A stop hunt spikes through it and closes back inside the range, then shifts structure in the opposite direction. Without that structure shift it was just a wick.
Equal highs are a magnet: two or more touches at the same level tell every chart reader to put stops just above. Taking them out is how the market reaches that liquidity. What matters is what happens next — acceptance above, or an immediate close back inside.
The London open and the London–New York overlap carry the volume, which is when ranges expand enough to pay for the spread. Our own testing filters entries to the 07:00–15:00 server window; outside it, the same setups produced materially worse results.
You define a range over the first fixed period of a session, then trade a break of that range in the direction it breaks. The logic is that a contraction of range tends to be followed by expansion — quiet periods precede directional moves.
We tested it on XAUUSD M15 over 2.54 years (2024-01-05 to 2026-07-21) with 30 points round-trip spread subtracted from every trade. It did not clear costs in our testing, so we retired it rather than keep teaching it. The published numbers and the retirement decision are both on the blog.
There is no universal answer, and anyone quoting one without a test is guessing. Shorter ranges give more signals and more noise; longer ranges give fewer, cleaner breaks. Test the window on your own instrument and session before committing to it.
The point of control is the price where the most volume traded in a session — the market's agreed fair price. It acts as a magnet that price returns to, which makes it far more useful as a target or a context marker than as an entry to chase.
The value area is the price band containing roughly 70% of a session's traded volume. Inside it, the market has agreed on price. Outside it, the market is exploring. Whether price is accepting or rejecting a level matters more than the level itself.
Look for high-volume nodes, where the market spent a lot of business, and low-volume nodes, where it spent almost none. Price tends to stall and rotate at high-volume nodes and move quickly through low-volume ones.
A high volume node is a price level where an unusually large amount of volume traded. It represents agreement — lots of business done at that price — so price returning there tends to slow down and rotate rather than cut straight through.
Find the base a strong, impulsive move departed from. That departure is the fingerprint of unfilled institutional orders. The cleaner and tighter the base, and the more violent the move away, the more meaningful the zone.
Support and resistance are lines drawn where price previously turned. Supply and demand zones are areas defined by the strength of the move that left them. The distinction matters: a zone with no impulsive departure is just a line, and it will behave like one.
Most commonly because the zone had already been used. The unfilled orders that made it work were filled the first time price returned. A retested zone is a weaker zone, and a zone with a sluggish departure was never strong to begin with.
Judge the exit, not the base. Strong zones are left by a fast, one-directional move that breaks structure. Weak zones are left by a slow drift. If you cannot point to the impulsive departure, you are looking at a level, not a zone.
Small enough that a losing streak cannot end your account. Position sizing, not entry selection, is what determines whether an edge survives — one cited study attributed about 91% of performance variability to sizing. Fix the risk per trade first, then worry about entries.
The honest answer is that it depends on your win rate, because the two are inseparable. Break-even win rate is 1÷(1+R): at 2R you need 33% winners, at 3R you need 25%. A high ratio with a low win rate is not automatically better.
Exactly 1÷(1+R), before costs. At 1R you need more than 50%; at 2R, 33%; at 3.5R, about 22%. Costs push all of these higher, which is why a strategy that looks profitable without spread modelling often is not.
Rarely because of a bad entry. Usually because size was too large for the drawdown the strategy normally produces, or a losing trade was allowed to run past its stop. Both are sizing and discipline failures, not analysis failures.
Recognise that it comes from treating one trade as a verdict on you rather than one sample from a distribution. Any single trade can lose while the edge is intact. A hard daily loss limit that ends the session removes the decision from you at the worst moment.
Expect them and size for them. Losing runs are a statistical certainty, not evidence the strategy is broken — a 40% win rate produces long strings of losses routinely. Knowing your normal streak length in advance is what stops you abandoning a working system.
Usually because the rules were never written precisely enough to follow under pressure. 'Wait for confirmation' is not a rule; 'wait for a 15-minute close back inside the range' is. Vague rules always lose to impulse in the moment.
Two reasons, and both are measurable. Demo has no real spread, slippage or fill risk, and demo has no fear — you take the setup mechanically. Model your costs explicitly and reduce size until live behaviour matches the plan.