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2017issue C0448-56

Constructing a volume-weighted moving-average crossover

April 2017 implementations treat a 50-bar volume-weighted average crossing a 70-bar simple moving average as a chart condition, typically on 15-minute bars. The same construction is then written as a next-bar market order, a five-bar scan-window, and a trailing-stop that bounds open risk after entry.

  • April 2017 implementations used a 50-bar volume-weighted average crossing a 70-bar simple moving average, typically on 15-minute charts.
  • The volume-weighted-average-price divides the sum of price times volume by the sum of volume, using trade volume on daily-or-higher bars and tick count on finer bars when those series differ.
  • A companion strategy bought or sold the next bar at market on the moving-average-crossover, while packaged and reconstructed versions added a per-share stop, a profit-triggered trailing-stop, and reentry-confirmation.
  • A scan-window looked for that upward cross within the last five bars on a 15-minute chart, and a short daily rescale of the same lengths produced many whipsaws.
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What the 2017 code implements

The April 2017 code implementations treat the technique as a 50-bar volume-weighted average crossing a 70-bar simple moving average, typically on 15-minute charts. A companion strategy buys the next bar at market when the volume-weighted line crosses above the simple average and sells the next bar at market on the opposite cross.

How the volume-weighted line is assembled

The volume-weighted-average-price is a length-based average that divides the sum of price times volume by the sum of volume, so heavier-participation bars pull the line more than quiet bars. The volume-weighted calculation uses trade volume on daily-or-higher bars and tick count on finer bars when those series differ.

The false-breakout-filter is the claim that adding volume to the average can reduce breakouts that occur on thin participation.

How the crossover is coded and scanned

A moving-average-crossover is a long or short signal generated when the volume-weighted line crosses a simple moving average of a different length. An alternative buy formula fires on the same crossover or, after that event, on a new high above the highest high since the last crossover while the volume-weighted line remains above the simple average.

A scan implementation looks for the 50-bar volume-weighted average having crossed up through the 70-bar simple average within the last five bars on a 15-minute chart. That scan-window is a recent-bar lookback used to find symbols where the crossover has already occurred, rather than waiting for a live tick.

How a trailing-stop bounds the open risk

A trailing-stop is a profit-triggered dollar trail or support-based exit that bounds the open risk after entry rather than relying on the next opposite crossover. One packaged strategy places a per-share stop loss and, once open profit reaches a dollar threshold, switches to a per-share trailing stop.

One reconstruction adds optional stop-out modes plus reentry-confirmation. After a trailing or support stop, a new long requires a break above the prior trailing high while the volume-weighted line is still above the simple average.

What happens if the lengths are rescaled to daily bars

A daily-bar rescaling of the original 15-minute lengths was illustrated as roughly two versus three days, or a 1.4 factor between the two averages. Those short daily lengths produced many whipsaws on a wider window.

NASDAQ 100 daily VWMA/SMA crossover versus the S&P 500

On daily bars of the NASDAQ 100 from 31 December 2008 through 10 February 2017, a 50-bar volume-weighted average crossing a 70-bar simple average booked 304 trades. Winners averaged +18.04 percent and losers −6.64 percent, so the book still made +5.29 percent per trade, while the S&P 500 over the same holding windows was slightly negative. Every figure is copied from the AIQ account-statistics table that accompanies the April 2017 Traders’ Tips code.
On daily bars of the NASDAQ 100 from 31 December 2008 through 10 February 2017, a 50-bar volume-weighted average crossing a 70-bar simple average booked 304 trades. Winners averaged +18.04 percent and losers −6.64 percent, so the book still made +5.29 percent per trade, while the S&P 500 over the same holding windows was slightly negative. Every figure is copied from the AIQ account-statistics table that accompanies the April 2017 Traders’ Tips code.NASDAQ 100 · Daily · 2008-12-31T00:00:00.000Z to 2017-02-10T00:00:00.000Z

The test took at most three new names a day and ten open positions, 10 percent of equity each. Neutral trades were zero. Annualized IRR was 17.42 percent against an 18.57 percent peak-to-valley drawdown; S&P 500 buy-and-hold over the same span returned 19.66 percent a year.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
13 of 18 in the Volume-weighted average price track
201726-29 pp.Next on Volume-weighted average priceConstructing anchored volume-weighted average price maps for crowd-visible execution costsFinancial survival is framed as locating focal points or friction places, not merely choosing among many private trading beliefs.
All readings on this track · 18 readings
  1. 2000Volume-weighted average price as a baseline for indicator construction
  2. 2001Constructing VWAP support and resistance from cumulative volume
  3. 2001An elastic volume-weighted moving average from a share-count lookback
  4. 2001Constructing an elastic volume-weighted average and volatility bands
  5. 2004Volume-weighted column averages and crossovers on point-and-figure charts
  6. 2004Session volume-weighted average for limit placement and listed routing
  7. 2008Building MIDAS curves from an anchored volume-weighted average
  8. 2008Construct a launch-point VWAP as support and resistance filters
  9. 2014Workstation order routing, VWAP, and session filters
  10. 2015Constructing price gravity and float turnover filters
  11. 2015Constructing four-stage cycles with anchored VWAP
  12. 2017Constructing a volume-weighted crossover and breakout as one swing rule set
  13. 2017Constructing a volume-weighted moving-average crossover
  14. 2017Constructing anchored volume-weighted average price maps for crowd-visible execution costs
  15. 2018Order book heatmaps, VWAP, and flow for execution
  16. 2018Constructing futures rolls ahead of first notice day
  17. 2019Evaluate a mechanical futures system as one procedure
  18. 2020Every bounce is a falsifiable regime test
All 19 readings tagged Volume-weighted average price
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