WMA Crossover + Williams %R Filter

Q: Does adding Williams %R improve a WMA crossover?

It can reduce some false signals by skipping crossovers that fire into stretched momentum, but it also delays or removes some good entries, and it does not make the strategy predictive. Test it out-of-sample and account for costs. This is educational, not advice.

Q: What settings should I use?

9/21 for the WMAs and standard Williams %R settings are common starting points, but there is no universally correct value — choose lengths that fit your timeframe and validate out-of-sample rather than tuning to past data.

A combination strategy that uses a WMA crossover to define trend direction and Williams %R as a filter on those signals. The idea: only act on crossovers that agree with momentum, to skip some of the false signals a crossover alone produces. Educational only — not predictive, and trading involves risk of loss.

How it works

Trend trigger — WMA crossover. A moving average (MA) takes the average price over a chosen number of bars and plots it as a single line that updates each bar. Two WMAs of different lengths (e.g. 9 and 21) are plotted; the fast one crossing above the slow one is read as upward momentum, and below as downward.

Filter — Williams %R. Williams %R (Williams Percent Range), developed by Larry Williams, is a momentum oscillator that measures where the current close falls relative to the highest high and lowest low over a chosen lookback period (commonly 14 bars). Here it is used to Williams %R runs from -100 to 0; this filters out the most stretched readings.

Why combine them. A moving-average crossover defines direction but fires on every cross, including in choppy conditions; adding a Williams %R filter tries to skip crossovers that trigger into already-stretched momentum. Both components are lagging by construction, so this reduces some false signals at the cost of entering later — it does not remove risk or guarantee anything.

Entry rules

Long: the fast WMA crosses above the slow WMA on a closed bar, AND the Williams %R filter agrees (Williams %R < -20).
Short: the fast WMA crosses below the slow WMA on a closed bar, AND the Williams %R filter agrees.
Act only on confirmed crossovers from closed bars — an intrabar cross can vanish before the bar closes.

Exit rules

Exit-on-opposite-signal: close (or reverse) when the WMAs cross back the other way.
Or use an independent stop / target (e.g. an ATR multiple) defined before entry.

Risk notes

Nothing here is predictive; both the WMAs and Williams %R lag price.
The Williams %R filter will also suppress some good signals — filters cut both ways.
Trading involves risk of loss; position sizing and stops matter more than indicator settings.

Pine v6 example

//@version=6
strategy("WMA Crossover + Williams %R Filter (Educational)", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=10, process_orders_on_close=true)

fastLen = input.int(9, "Fast WMA length", minval=1)
slowLen = input.int(21, "Slow WMA length", minval=1)

fast = ta.wma(close, fastLen)
slow = ta.wma(close, slowLen)
oscVal = ta.wpr(14)

longCond  = ta.crossover(fast, slow)  and oscVal < -20
shortCond = ta.crossunder(fast, slow) and oscVal > -80

if longCond
    strategy.entry("Long", strategy.long)
if shortCond
    strategy.entry("Short", strategy.short)

plot(fast, "Fast WMA", color.aqua)
plot(slow, "Slow WMA", color.orange)

// Educational only. Not financial advice. Validate for look-ahead bias &
// repainting before trusting any backtest. Past results do not predict future.

Pitfalls

Whipsaw: in ranging markets the crossover fires repeatedly; the Williams %R filter reduces but does not remove this.
Over-optimising the lengths/thresholds to a backtest rarely carries forward.
Repaint/look-ahead: evaluate on closed bars and avoid future-referencing data (this generated script is validated for both).
Costs: more signals on lower timeframes mean spread/slippage/fees can dominate.

FAQ

Does adding Williams %R improve a WMA crossover?

It can reduce some false signals by skipping crossovers that fire into stretched momentum, but it also delays or removes some good entries, and it does not make the strategy predictive. Test it out-of-sample and account for costs. This is educational, not advice.

What settings should I use?

9/21 for the WMAs and standard Williams %R settings are common starting points, but there is no universally correct value — choose lengths that fit your timeframe and validate out-of-sample rather than tuning to past data.

Indicators in this strategy

Moving Averages (SMA & EMA)Williams %R

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Educational & software only — not financial advice, not a recommendation to trade. Backtests are illustrative; past performance does not predict future results. Trading involves substantial risk of loss.