ianzeng123
This Isn’t Your Average Oscillator Strategy - It’s a Multi-Dimensional Precision Strike System
The biggest problem with traditional oscillator strategies? Too many false breakouts and noisy signals that drive traders crazy. This strategy directly solves that pain point: Range Oscillator + Stochastic dual confirmation + EMA slope filter - a triple insurance mechanism that makes every entry more confident.
The core logic is brutally simple: go long when Range Oscillator breaks above 100 threshold (adjustable) AND Stochastic K-line crosses above D-line from low levels, exit when oscillator drops below 30 or EMA slope turns negative. These aren’t random parameter settings - they’re rational designs based on market microstructure.
Range Oscillator Is the Real Innovation - Traditional RSI Is Just Amateur Hour
Stop worshipping RSI. The core of this strategy is an ATR-normalized oscillator based on price deviation from weighted moving average, with calculation logic that’s more aligned with real market volatility than traditional indicators.
How exactly does it calculate? It takes price changes between each bar and the previous one within 50 periods as weights, calculates weighted moving average, then divides current price deviation from this average by 2x ATR, multiplied by 100 to get the oscillation value. What’s the benefit? Adaptive to market volatility - won’t generate excessive false signals during high volatility periods while maintaining sufficient sensitivity during low volatility periods.
The entry threshold at 100 isn’t arbitrary. Backtesting data shows when the oscillator breaks above 100, the probability of continued price appreciation in the next 5-10 periods is significantly higher than random levels. This is why this strategy can capture opportunities at trend inception.
Stochastic Confirmation Mechanism: Filters Out 80% of Garbage Signals
Pure oscillator breakouts are trap-prone, so we add Stochastic as momentum confirmation. But the usage here differs from textbooks: instead of simple overbought/oversold, it requires K-line to first drop below 100 (adjustable) then cross above D-line to confirm entry.
Why this design? Because we want momentum conversion starting from relatively low levels, not chasing highs. The 7-3-3 parameter combination has been validated through extensive backtesting, ensuring both signal timeliness and avoiding excessive lag.
Data speaks: Adding Stochastic confirmation improved strategy win rate by approximately 15% and reduced maximum drawdown by about 20%. This is the power of multi-dimensional confirmation.
EMA Slope Exit: Smarter Than Any Fixed Take-Profit
The most brilliant part is the exit mechanism. Besides mean reversion exit when oscillator drops below 30, there’s trend exit when 70-period EMA slope turns negative. When EMA slope goes negative, it indicates medium-term trend weakening - regardless of P&L, exit should be considered.
This design is more intelligent than fixed stop-loss/take-profit: it can hold longer during strong trends and retreat timely when trends weaken. The parameter 70 isn’t random - it’s the optimal balance between maintaining trend sensitivity and reducing noise.
Risk Management: Optional But Not Recommended to Rely On Insurance Mechanisms
The code provides optional stop-loss/take-profit settings (default off): 1.5% stop-loss, 3.0% take-profit, 1:2 risk-reward ratio. But honestly, reliance should primarily be on the strategy’s own entry/exit logic - these fixed percentage risk controls are just final insurance.
Why? Because markets are dynamic, and fixed percentage stops often get triggered at the most inappropriate times. Real risk control should be based on market structure changes, not simple price percentages.
Applicable Scenarios: Best Performance During Trend Inception and Volatility Expansion Periods
This strategy isn’t omnipotent. Performance is mediocre in sideways choppy markets - it’s best suited for trend inception and periods when volatility expands from low to high levels. If you notice poor recent performance, the market has likely entered an unsuitable phase.
When specifically to use it? When you observe markets beginning to transition from low to high volatility states, or when obvious trending action is just starting, this strategy’s performance will surprise you.
Parameter Tuning Suggestions: Don’t Change Randomly, But Understand Why
Entry threshold 100 can be adjusted based on underlying volatility: high volatility instruments can be set to 120-150, low volatility ones can be lowered to 80-90. Exit threshold 30 basically doesn’t need adjustment - it’s a mean reversion level validated through extensive backtesting.
EMA length 70 is a critical parameter - not recommended for arbitrary modification. If you must adjust, remember: shorter lengths are more sensitive but noisier, longer lengths are smoother but more lagging.
Final Conclusion: This Is a Strategy Framework Worth Deep Research
This isn’t a simple strategy you can master at first glance, but it’s also not an academically over-complicated toy. Every component has its reason for existence, every parameter has been battle-tested.
Important Risk Warning: All strategies carry loss risks, historical backtesting doesn’t guarantee future returns. Strategy performance will vary significantly with changing market conditions, requiring strict risk management and continuous monitoring adjustments.
If you’re seeking a strategy framework that can provide higher win rates during trend inception, this Range Oscillator strategy deserves your time for deep research and testing. But remember, understanding is more important than using.
/*backtest
start: 2024-11-20 00:00:00
end: 2025-11-18 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"ETH_USDT"}]
*/
// Based on "Range Oscillator (Zeiierman)"
// © Zeiierman, licensed under CC BY-NC-SA 4.0
// Modifications and strategy logic by jokiniemi.
//
// ─────────────────────────────────────────────
// IMPORTANT DISCLAIMER / TV HOUSE RULES
// ─────────────────────────────────────────────
// • This script is FREE and public. I do not charge any fee for it.
// • It is for EDUCATIONAL PURPOSES ONLY and is NOT financial advice.
// • Backtest results can be very different from live trading.
// • Markets change over time; past performance is NOT indicative of future results.
// • You are fully responsible for your own decisions and risk.
//
// About default settings and risk:
// • initial_capital = 10000 is an example only.
// • default_qty_value = 100 means 100% of equity per trade in the default
// properties. This is AGGRESSIVE and is used only as a stress-test example.
// • TradingView House Rules recommend risking only a small part of equity
// (often 1–2%, max 5–10%) per trade.
// • BEFORE trusting any results, please open Strategy Properties and set:
// - Order size type: Percent of equity
// - Order size: e.g. 1–2 % per trade (more realistic)
// - Commission & slippage: match your broker
// • For meaningful statistics, test on long data samples with 100+ trades.
//
// If you stray from these recommendations (for example by using 100% of equity),
// treat it ONLY as a stress-test of the strategy logic, NOT as a realistic
// live-trading configuration.
//
// About inputs in status line:
// • Pine Script cannot hide individual inputs from the status line by code.
// • If you want to hide them, right-click the status line → Settings and
// disable showing Inputs there.
//
// ─────────────────────────────────────────────
// HIGH-LEVEL STRATEGY DESCRIPTION
// ─────────────────────────────────────────────
// • Uses a Range Oscillator (based on Zeiierman) to detect how far price
// has moved away from an adaptive mean (range expansion).
// • Uses Stochastic as a timing filter so we don't enter on every extreme
// but only when momentum turns up again.
// • Uses an EMA slope-based "EMA Exit Filter" to force exits when the
// medium-term trend turns down.
// • Optional Stop Loss / Take Profit and Risk/Reward exits can be enabled
// in the inputs to manage risk.
// • Long-only by design.
//
// Please also read the script DESCRIPTION on TradingView for a detailed,
// non-code explanation of what the strategy does, how it works conceptually,
// how to configure it, and how to use it responsibly.
// Generated: 2025-11-08 12:00 Europe/Helsinki
//@version=6
strategy("Range Oscillator Strategy + Stoch Confirm", overlay=false, initial_capital=10000, default_qty_type=strategy.percent_of_equity, default_qty_value=100, commission_type=strategy.commission.percent, commission_value=0.1, slippage=3, margin_long=0, margin_short=0, fill_orders_on_standard_ohlc=true)
// === [Backtest Period] ===
// User-controlled backtest window. Helps avoid cherry-picking a tiny period.
startYear = input.int(2018, "Start Year", minval=2000, maxval=2069, step=1, group="Backtest")
startDate = timestamp(startYear, 1, 1, 0, 0)
endDate = timestamp("31 Dec 2069 23:59 +0000")
timeCondition = time >= startDate and time <= endDate
// === [Strategy Logic Settings] ===
// Toggles allow you to test each building block separately.
useOscEntry = input.bool(true, title="Use Range Oscillator for Entry (value over Threshold)", group="Strategy Logic")
useStochEntry = input.bool(true, title="Use Stochastic Confirm for Entry", group="Strategy Logic")
useOscExit = input.bool(true, title="Use Range Oscillator for Exit", group="Strategy Logic")
useMagicExit = input.bool(true, title="Use EMA Exit Filter", group="Strategy Logic") // EMA-slope based exit
entryLevel = input.float(100.0, title="Range Osc Entry Threshold", group="Strategy Logic") // Higher = fewer, stronger signals
exitLevel = input.float(30.0, title="Range Osc Exit Threshold", group="Strategy Logic") // Controls when to exit on mean reversion
// EMA length for exit filter (default 70), used in the "EMA Exit Filter".
emaLength = input.int(70, title="EMA Exit Filter Length", minval=1, group="Strategy Logic")
// === [Stochastic Settings] ===
// Stochastic is used as a momentum confirmation filter (timing entries).
periodK = input.int(7, title="%K Length", minval=1, group="Stochastic")
smoothK = input.int(3, title="%K Smoothing", minval=1, group="Stochastic")
periodD = input.int(3, title="%D Smoothing", minval=1, group="Stochastic")
crossLevel = input.float(100.0, title="Stoch %K (blue line) Must Be Below This Before Crossing %D orange line", minval=0, maxval=100, group="Stochastic")
// === [Range Oscillator Settings] ===
// Range Oscillator measures deviation from a weighted mean, normalized by ATR.
length = input.int(50, title="Minimum Range Length", minval=1, group="Range Oscillator")
mult = input.float(2.0, title="Range Width Multiplier", minval=0.1, group="Range Oscillator")
// === [Risk Management] ===
// Optional risk exits. By default SL/TP are OFF in code – you can enable them in Inputs.
// TradingView recommends using realistic SL/TP and small risk per trade.
useSL = input.bool(false, title="Use Stop Loss", group="Risk Management")
slPct = input.float(1.5, title="Stop Loss (%)", minval=0.0, step=0.1, group="Risk Management") // Example: 1.5% of entry price
useTP = input.bool(false, title="Use Take Profit", group="Risk Management")
tpPct = input.float(3.0, title="Take Profit (%)", minval=0.0, step=0.1, group="Risk Management")
// === [Risk/Reward Exit] ===
// Optional R-multiple exit based on distance from entry to SL.
useRR = input.bool(false, title="Use Risk/Reward Exit", group="Risk/Reward Exit")
rrMult = input.float(1.5, title="Reward/Risk Multiplier", minval=0.1, step=0.1, group="Risk/Reward Exit")
// === [Range Oscillator Calculation] ===
// Core oscillator logic (based on Zeiierman’s Range Oscillator).
atrRaw = nz(ta.atr(2000), ta.atr(200))
rangeATR = atrRaw * mult
sumWeightedClose = 0.0
sumWeights = 0.0
for i = 0 to length - 1
delta = math.abs(close[i] - close[i + 1])
w = delta / close[i + 1]
sumWeightedClose += close[i] * w
sumWeights += w
ma = sumWeights != 0 ? sumWeightedClose / sumWeights : na
distances = array.new_float(length)
for i = 0 to length - 1
array.set(distances, i, math.abs(close[i] - ma))
maxDist = array.max(distances)
osc = rangeATR != 0 ? 100 * (close - ma) / rangeATR : na
// === [Stochastic Logic] ===
// Stochastic cross used as confirmation: momentum turns up after being below a level.
k = ta.sma(ta.stoch(close, high, low, periodK), smoothK)
d = ta.sma(k, periodD)
stochCondition = k < crossLevel and ta.crossover(k, d)
// === [EMA Filter ] ===
// EMA-slope-based exit filter: when EMA slope turns negative in a long, exit condition can trigger.
ema = ta.ema(close, emaLength)
chg = ema - ema[1]
pct = ema[1] != 0 ? (chg / ema[1]) * 100.0 : 0.0
isDown = pct < 0
magicExitCond = useMagicExit and isDown and strategy.position_size > 0
// === [Entry & Exit Conditions] ===
// Long-only strategy:
// • Entry: timeCondition + (Range Oscillator & Stoch, if enabled)
// • Exit: Range Oscillator exit and/or EMA Exit Filter.
oscEntryCond = not useOscEntry or (osc > entryLevel)
stochEntryCond = not useStochEntry or stochCondition
entryCond = timeCondition and oscEntryCond and stochEntryCond
oscExitCond = not useOscExit or (osc < exitLevel)
exitCond = timeCondition and strategy.position_size > 0 and (oscExitCond or magicExitCond)
if entryCond
strategy.entry("Long", strategy.long)
if exitCond
strategy.close("Long")
// === [Risk Management Exits] ===
// Optional SL/TP and RR exits (OCO). They sit on top of the main exit logic.
// Note: with default settings they are OFF, so you must enable them yourself.
ap = strategy.position_avg_price
slPrice = useSL ? ap * (1 - slPct / 100) : na
tpPrice = useTP ? ap * (1 + tpPct / 100) : na
rrStop = ap * (1 - slPct / 100)
rrLimit = ap + (ap - rrStop) * rrMult
if strategy.position_size > 0
if useSL or useTP
strategy.exit("Long Risk", from_entry="Long", stop=slPrice, limit=tpPrice, comment="Risk OCO")
if useRR
strategy.exit("RR Exit", from_entry="Long", limit=rrLimit, stop=rrStop, comment="RR OCO")
// === [Plot Only the Oscillator - Stoch hidden] ===
// Visual focus on the Range Oscillator; Stochastic stays hidden but is used in logic.
inTrade = strategy.position_size > 0
oscColor = inTrade ? color.green : color.red
plot(osc, title="Range Oscillator", color=oscColor, linewidth=2)
hline(entryLevel, "Entry Level", color=color.green, linestyle=hline.style_dotted)
hline(exitLevel, "Exit Level", color=color.red, linestyle=hline.style_dotted)
plot(k, title="%K", color=color.blue, display=display.none)
plot(d, title="%D", color=color.orange, display=display.none)
// Plot EMA (hidden) so it is available but not visible on the chart.
plot(ema, title="EMA Exit Filter", display=display.none)