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The best indicator for Willis Towers Watson (WTW)

We backtested 382 indicators across daily, weekly and hourly charts on real Willis Towers Watson (WTW) history. Here's what actually worked — risk-adjusted, out-of-sample, with costs.

Signaling LONG right now — Camarilla Pivots (Weekly) has been long for 2 bars. Signal computed on 2026-09-07, 3 days behind the price data on this page (it is rebuilt on a separate schedule).
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Key levels · as of 2026-09-10

Where Willis Towers Watson (WTW) stands

315.41
last daily close (2026-09-10)
298.88
200-day simple moving average price 5.5% above
319.28
50-day simple moving average price 1.2% below
241.24–350.75
52-week range

Computed from our own daily OHLCV history, not quoted from a third party. Moving averages use closing prices; "52-week" is the last 252 trading sessions.

Mean Reversion · Weekly

Camarilla Pivots

On the weekly chart, this is the strongest risk-adjusted edge we found for Willis Towers Watson (WTW) over ~25.1 years — beating buy-and-hold by 1.8% CAGR.

11.4%
CAGR
0.73
Sharpe
-24.1%
Max DD
46.0%
Win rate
0.88
Profit factor
+1.8%
vs Buy&Hold
Chart

Willis Towers Watson (WTW) on the weekly chart

The timeframe our backtest found best for this asset. The chart is live market data; the results above are hypothetical and historical.

Chart by TradingView. Loading it contacts tradingview.com, which may set its own cookies — see our privacy policy.

NOTHING BEAT BUY-AND-HOLD
Full strategy report — every setup ranked out-of-sample, corrected for data-mining, and forward-tracked in public.
Read the verdict
Confluence · Daily

Best multi-indicator combo

StochasticQQE

Going long only when all 2 agree was the strongest confluence setup we found for Willis Towers Watson (WTW) — trailing buy-and-hold by 6.7% CAGR, out-of-sample. Fewer, higher-conviction trades than any single indicator.

3.0%
CAGR
0.26
Sharpe
55.2%
Win rate
212
Trades
-6.7%
vs Buy&Hold
Best by timeframe

The winner on each chart

Weekly
Camarilla Pivots
+1.8% · Sharpe 0.73
Daily
Projection Bands
-1.1% · Sharpe 0.58
Full results

Every indicator, ranked

Ranked by Sharpe (risk-adjusted return). Hypothetical, fees included.

#IndicatorTFCAGRSharpeMax DDWinTradesvs B&H
1Camarilla Pivots Weekly11.4%0.73-24.1%46.0%2721.8%
2Fibonacci Pivots Weekly9.3%0.65-35.2%48.8%203-0.3%
3Pivot Points (Standard) Weekly8.4%0.61-35.2%48.1%187-1.2%
4Demand Index Weekly9.9%0.6-48.8%71.9%640.3%
5Projection Bands Daily8.6%0.58-32.1%66.4%214-1.1%
6Murrey Math Lines Daily8.4%0.57-35.8%79.7%69-1.3%
7MA Envelope Daily7.9%0.54-32.3%65.9%132-1.7%
8SMC: Liquidity Sweep Daily8.9%0.53-45.2%75.8%91-0.8%
9Keltner Mean-Reversion Daily6.2%0.52-28.4%67.2%67-3.4%
10MA Envelope Weekly7.6%0.52-45.2%75.9%54-2.0%
11Ultimate Oscillator Daily7.5%0.5-43.2%80.0%20-2.1%
12Order-Flow Reversion Daily6.4%0.5-28.6%68.3%82-3.3%
13Intraday Momentum Index Daily6.8%0.49-30.0%74.6%71-2.8%
14Projection Bands Weekly6.4%0.48-36.4%74.4%43-3.2%

= held up out-of-sample. Hypothetical, costs included. See methodology.

The leverage question

What it would take to beat buy & hold on Willis Towers Watson (WTW)

11 of 648 tested setups beat buy-and-hold on Willis Towers Watson (WTW) outright. Another 62 could get there with leverage they would survive — but 103 would be liquidated by their own drawdown before they caught it.

IndicatorBeats B&H unlevered Leverage neededLeverage survived
MA Envelope2none needed4.43×
Pivot Points (Standard)2none needed4.85×
Fibonacci Pivots2none needed5.1×
Projection Bands11.23×4.43×
Demand Index11.79×3.72×
Camarilla Pivots13.07×4.75×

Out-of-sample, costs included. A setup is only listed if the leverage it needs is less than the leverage its own worst drawdown survives — when it isn't, no amount of leverage gets there. Volatility drag isn't modelled, so these are the optimistic case. Every indicator, ranked this way

What this means

For Willis Towers Watson (WTW), Camarilla Pivots on the weekly timeframe gave the best balance of return and risk in our test. It beat buy-and-hold — but remember: this is a hypothetical backtest of a standard rule, not a recommendation. Markets change. See the methodology and disclaimer.

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