Brian Shannon: Put Timeframes and Anchored VWAP to Work

A hypothetical stock breaks above 42.00 on a fifteen-minute chart while its daily chart sits beneath repeated highs at 42.50. The short-term move is real, but so is the nearby obstacle. Brian Shannon’s work gives chart readers a way to put those observations together without asking one timeframe to answer every question.

Alphatrends identifies Shannon as a Chartered Market Technician, a full-time swing trader using his own capital and the author of books on multiple timeframes and anchored VWAP. His article on multiple timeframes explains his use of chart context across different periods.

The examples below are hypothetical calculations and chart sequences created for this profile. They aren’t his trades or a complete reproduction of his method. Their purpose is to distinguish an observation, a reference level and a decision rule, especially when an attractive chart encourages stronger conclusions than the data can support.

Brian Shannon and the distance between two timeframes

In the opening example, a proposed entry at 42.10 leaves 0.40 to the daily reference at 42.50. If the hypothetical exit reference is 41.30, the planned initial risk is 0.80 per share. The distance to the nearby high is therefore half the initial risk.

The immediate geometry is now visible. Price could continue through 42.50, and a study might compare setups with little room to the next reference against those with more space while keeping entry and exit rules consistent.

I find the 0.40-versus-0.80 comparison useful because the fifteen-minute breakout alone hides it. The daily chart contributes a measurable constraint to the analysis. Whether that constraint improves a strategy’s results remains a separate research question.

The support and resistance guide provides a framework for marking the prior high. A level’s presence doesn’t supply a probability of rejection. Calling every aligned chart a higher-probability trade would require evidence beyond the fact of alignment.

An anchored average begins with a chosen event

Anchored VWAP accumulates price multiplied by volume from a selected starting point, then divides by the accumulated volume. In a simplified hypothetical dataset, 100 units trade at 20.00 and 300 at 22.00. The average is 8,600 divided by 400, or 21.50.

The greater volume at 22.00 gives that price more influence. A simple unweighted average of the two prices would be 21.00. The difference shows what volume weighting contributes, without requiring a story about the identity of the participants.

The anchored VWAP guide explains the reference in greater detail. Chart platforms may use a representative bar price rather than every individual transaction. The data resolution and calculation convention therefore belong in any comparison of displayed values.

The resulting line is an average of recorded activity. It doesn’t reveal the current cost basis of a particular institution. Participants may have traded repeatedly, closed positions or entered before the anchor. An aggregate calculation cannot identify who still holds what.

The same prices can produce different anchor stories

Add an earlier hypothetical block of 400 units at 18.00 to the previous dataset. An anchor that includes all three blocks produces 15,800 divided by 800, or 19.75. An anchor beginning after that early block remains at 21.50.

At a current price of 20.50, the market is above one average and below the other. Both calculations are correct for their chosen starting points.

The disagreement comes from the question being asked.

I would record why the 18.00 block was included before interpreting the 19.75 line. An event-based anchor, such as the start of an earnings session, has a reason that can be stated beforehand. Moving the anchor until the line fits a later bounce makes the visual agreement easier to manufacture.

A comparison can retain a fixed set of candidate events and record every resulting line. It should also preserve the cases where price crossed them without hesitation. Keeping only the lines that later acted as support gives a distorted picture of the tool’s usefulness.

A touch of the line still needs a defined response

Suppose price approaches an anchored average at 35.20, trades to 35.10 and closes at 35.40. A hypothetical study could define that as a brief penetration followed by a close above the line. Another study might require the entire bar to remain above it.

Those definitions classify this event differently. “Held VWAP” is too broad to distinguish them. The record also needs the line’s value at the decision point, because the average continues to change as new price and volume enter the calculation.

If the next session opens at 34.80, a planned exit around 35.00 may not execute at the reference price. The line supplies context, but it doesn’t guarantee liquidity or protect against a gap. Position management requires assumptions about what the order can actually do.

A useful replay exercise hides the next bar and asks the reader to record the proposed entry condition, the invalidation reference and the expected order timing. Revealing the next bar afterward makes it possible to assess the original decision without replacing it with hindsight.

Volume measures activity without naming its owner

A hypothetical breakout session trades 1.8 million shares against a prior 20-session average of 0.9 million. Its relative volume is 2.0. That establishes a comparison with the selected historical window.

It doesn’t establish that institutions caused the move, that all participants share a directional view or that the price will keep rising. Each completed transaction has counterparties, and the public total doesn’t describe their existing positions or reasons for trading.

The guide to volume confirmation on breakout candles can help turn activity into a defined study variable. A rule requiring twice the prior average needs to say whether the current session is excluded from that average and whether the final daily volume is available at entry.

Comparing a midday total with full-day historical totals introduces another mismatch. A time-adjusted comparison needs an appropriate same-time baseline. The attractive number on the chart deserves the same scrutiny as the price level beside it.

Choose the trade’s invalidation before its quantity

Consider a hypothetical entry at 60.00 after a pullback. One thesis depends on a recent low at 58.80 holding; another allows a retreat toward a wider base at 56.50. Example exit references at 58.70 and 56.40 create distances of 1.30 and 3.60 respectively.

With 360 of planned price risk, the first permits 276 whole shares before costs, while the second permits 100. The unused 1.20 in the first calculation comes from rounding down. Neither quantity is a recommendation; both illustrate how the reference changes exposure.

A trader can’t make the wider thesis fit 276 shares simply by pretending the 58.70 level invalidates it. That would combine the quantity from one trade with the reasoning from another. Recording the thesis beside the reference exposes the mismatch.

The JC Parets profile offers a related perspective on price-based analysis. For this example, the useful connection is the discipline of stating what price would have to do to contradict the proposed reading.

Keep conflicting charts in the record

A weekly chart can remain in a broad range while the daily chart develops an advance and the intraday chart pulls back. Those descriptions can all be true. A study needs a stated way of handling the combination.

For illustration, one version might accept daily setups inside the weekly range only when at least 2R remains to the range ceiling. Another might exclude them entirely. If the hypothetical entry is 42.10, the ceiling 42.50 and initial risk 0.80, the first version rejects the setup because only 0.5R remains.

The second version rejects it for a different reason. Recording the reason matters when later results are compared. Otherwise a profitable trade that was excluded can tempt the researcher to redefine the filter selectively.

These independently constructed rules turn the broader emphasis on timeframe context into a question precise enough to examine. Adding more charts without deciding their roles can increase interpretive freedom instead of reducing it.

Two books, two distinct study tasks

Technical Analysis Using Multiple Timeframes, by Brian Shannon, supports the study of how charts at different resolutions relate. A practical reading task is to annotate the 42.10 entry, 42.50 ceiling and 41.30 exit reference on the relevant timeframes, then explain which chart supplied each value.

Maximum Trading Gains with Anchored VWAP: The Perfect Combination of Price, Time & Volume, also by Shannon, concentrates on the anchored reference. The 19.75-versus-21.50 calculation above provides a simple starting exercise for understanding why the anchor changes the result.

Disclosure: As an Amazon Associate, I earn from qualifying purchases.

Technical Analysis Using Multiple Timeframes is linked in the hardcover edition: (US) Technical Analysis Using Multiple Timeframes, (UK) Technical Analysis Using Multiple Timeframes, (DE) Technical Analysis Using Multiple Timeframes.

Maximum Trading Gains with Anchored VWAP is linked in hardcover for the US and paperback for the UK and Germany: (US) Maximum Trading Gains with Anchored VWAP, Hardcover, (UK) Maximum Trading Gains with Anchored VWAP, Paperback, (DE) Maximum Trading Gains with Anchored VWAP, Paperback.

Name the anchor before interpreting the bounce

A line at 19.75 and a line at 21.50 can come from the same transaction sequence with different starting points. Writing down the anchor first keeps that choice visible. The next interaction with the line can then test an existing interpretation instead of supplying a convenient reason to redraw it.

Learn the pattern. Ride the trend. Keep the gains.

Educational content only. Not investment advice. Trading involves risk. You are responsible for your decisions.