SLG's EMA+MACD Signal Trading Strategy M15Trading Concept Overview
This strategy combines trend-following and momentum confirmation to identify high-probability entries in both long and short directions. It uses EMA-based trend filtering and MACD signal analysis, while managing risk dynamically using ATR-based stop loss and take profit.
1. Trend Identification
The strategy calculates a Trend EMA (emaTrend) with a user-defined period (emaTrendLen) to determine the overall market direction:
Bullish Trend: Price closes above the Trend EMA → only long trades are considered.
Bearish Trend: Price closes below the Trend EMA → only short trades are considered.
This ensures trades are aligned with the larger trend, avoiding counter-trend signals.
2. Momentum Signal with MACD
MACD Calculation:
fastEMA - slowEMA generates the MACD line.
Signal line is an EMA of the MACD line.
delta = MACD - Signal measures the momentum difference.
Entry Logic:
Long Signal: delta crosses above zero AND the price is above the Trend EMA.
Short Signal: delta crosses below zero AND the price is below the Trend EMA.
This ensures that entries occur only when momentum is aligned with the overall trend.
3. Dynamic Risk Management (ATR-based SL/TP)
Uses Average True Range (ATR) to dynamically set stop loss and take profit:
Long Trade:
Stop Loss = Close - ATR * atrSLMult
Take Profit = Close + ATR * atrTPMult
Short Trade:
Stop Loss = Close + ATR * atrSLMult
Take Profit = Close - ATR * atrTPMult
This allows the strategy to adapt to market volatility, protecting capital in choppy conditions and scaling profit targets in trending markets.
4. Visual and Alert Features
Plots:
Trend EMA for visual trend guidance.
MACD delta to observe momentum.
Long/Short signals as small triangles directly on the chart.
Alerts:
Generates notifications for long and short signals to trigger timely trades.
5. Core Trading Philosophy
Trend-Following Bias: Only trade in the direction of the trend EMA.
Momentum Confirmation: Enter trades when the MACD delta confirms the move.
Volatility-Adjusted Risk: Use ATR to dynamically scale stops and targets.
Disclaimer / Risk Notice
Trading financial markets involves significant risk and may not be suitable for all investors. Past performance is not indicative of future results.
Market conditions can change rapidly and unpredictably, and no strategy can guarantee profits. Always use proper risk management and position sizing.
This strategy is for educational and informational purposes only. Users are responsible for their own trading decisions.
指標和策略
Scalp EMA+RSI+ADX+Vol v7 (универсальная, x25)// @version=6
// Scalp EMA+RSI+ADX+Vol v7 — универсальная версия с ликвидационным стопом (x25)
// Автор: ChatGPT
// === ПАРАМЕТРЫ ===
percent_of_equity = input.float(2.0, "Position size (% of equity)", step=0.1, minval=0.1)
fastLen = input.int(8, "Fast EMA length", minval=1)
slowLen = input.int(21, "Slow EMA length", minval=1)
rsiLen = input.int(7, "RSI length", minval=1)
rsiConfirm= input.int(50, "RSI confirmation level")
adxLen = input.int(10, "ADX length", minval=1)
adxThresh = input.int(15, "ADX threshold (min trend strength)")
volSmaLen = input.int(20, "Volume SMA length", minval=1)
volMult = input.float(0.8, "Min volume multiplier", step=0.1, minval=0.1)
atrLen = input.int(10, "ATR length", minval=1)
atrTP = input.float(1.6, "TP = x * ATR", step=0.1, minval=0.1)
useTrailing = input.bool(false, "Use trailing stop")
trailOffsetMult = input.float(0.8, "Trailing offset = x * ATR", step=0.1, minval=0.1)
maxTradesPerDay = input.int(0, "Max trades per day (0 = unlimited)")
useTimeFilter = input.bool(false, "Enable time filter (exchange time)")
startH = input.int(0, "Start hour (0-23)")
startM = input.int(0, "Start minute (0-59)")
endH = input.int(23, "End hour (0-23)")
endM = input.int(59, "End minute (0-59)")
leverage = input.int(25, "Leverage (для расчета ликвидации)", minval=1) // ← по умолчанию 25
// === STRATEGY DECLARATION ===
strategy("Scalp EMA+RSI+ADX+Vol v7 (универсальная, x25)", overlay=true,
default_qty_type=strategy.percent_of_equity, default_qty_value=2.0,
initial_capital=10000, pyramiding=1)
// === ИНДИКАТОРЫ ===
fastEMA = ta.ema(close, fastLen)
slowEMA = ta.ema(close, slowLen)
rsi = ta.rsi(close, rsiLen)
volSMA = ta.sma(volume, volSmaLen)
atr = ta.atr(atrLen)
plot(fastEMA, title="Fast EMA", linewidth=1, color=color.teal)
plot(slowEMA, title="Slow EMA", linewidth=1, color=color.orange)
// === ADX (ручной расчет) ===
upMove = high - high
downMove = low - low
plusDM = (upMove > downMove and upMove > 0) ? upMove : 0.0
minusDM = (downMove > upMove and downMove > 0) ? downMove : 0.0
tr = math.max(high - low, math.max(math.abs(high - close ), math.abs(low - close )))
atr_adx = ta.rma(tr, adxLen)
smPlus = ta.rma(plusDM, adxLen)
smMinus = ta.rma(minusDM, adxLen)
plusDI = atr_adx == 0 ? 0.0 : 100.0 * smPlus / atr_adx
minusDI = atr_adx == 0 ? 0.0 : 100.0 * smMinus / atr_adx
sumDI = plusDI + minusDI
dx = sumDI == 0 ? 0.0 : 100.0 * math.abs(plusDI - minusDI) / sumDI
adx = ta.rma(dx, adxLen)
// === СИГНАЛЫ ===
crossUp = ta.crossover(fastEMA, slowEMA)
crossDown = ta.crossunder(fastEMA, slowEMA)
volOK = volume > volSMA * volMult
rsiOK_long = rsi > rsiConfirm
rsiOK_short = rsi < rsiConfirm
adxOK = adx >= adxThresh
candleBull= close > open
candleBear= close < open
longSignal = crossUp and rsiOK_long and adxOK and volOK and candleBull
shortSignal = crossDown and rsiOK_short and adxOK and volOK and candleBear
// === TIME FILTER ===
s = useTimeFilter ? timestamp(year(time), month(time), dayofmonth(time), startH, startM) : na
e = useTimeFilter ? timestamp(year(time), month(time), dayofmonth(time), endH, endM) : na
inTradeHours = not useTimeFilter ? true : (e > s ? (time >= s and time <= e) : (time >= s or time <= e))
// === DAILY COUNTER ===
var int tradesToday = 0
var int lastDay = na
if dayofmonth(time) != lastDay
tradesToday := 0
lastDay := dayofmonth(time)
canOpenMore = (maxTradesPerDay == 0) or (tradesToday < maxTradesPerDay)
// === ENTRIES / EXITS ===
if longSignal and inTradeHours and canOpenMore and strategy.position_size == 0
entryPrice = close
liqPrice = entryPrice - entryPrice / leverage // стоп по ликвидации x25
takePrice = entryPrice + atr * atrTP
if useTrailing
strategy.entry("Long", strategy.long)
strategy.exit("Long Exit", from_entry="Long", limit=takePrice, trail_offset=atr * trailOffsetMult)
else
strategy.entry("Long", strategy.long)
strategy.exit("Long Exit", from_entry="Long", stop=liqPrice, limit=takePrice)
tradesToday += 1
if shortSignal and inTradeHours and canOpenMore and strategy.position_size == 0
entryPrice = close
liqPrice = entryPrice + entryPrice / leverage // стоп по ликвидации x25
takePrice = entryPrice - atr * atrTP
if useTrailing
strategy.entry("Short", strategy.short)
strategy.exit("Short Exit", from_entry="Short", limit=takePrice, trail_offset=atr * trailOffsetMult)
else
strategy.entry("Short", strategy.short)
strategy.exit("Short Exit", from_entry="Short", stop=liqPrice, limit=takePrice)
tradesToday += 1
// === ВИЗУАЛИЗАЦИЯ ===
plotshape(longSignal, title="Long Signal", location=location.belowbar, style=shape.triangleup, size=size.small, color=color.green, text="LONG")
plotshape(shortSignal, title="Short Signal", location=location.abovebar, style=shape.triangledown, size=size.small, color=color.red, text="SHORT")
// INFO BOX
var label info = na
if barstate.islast
label.delete(info)
infoText = "EMA: " + str.tostring(fastLen) + "/" + str.tostring(slowLen) +
" | RSI: " + str.tostring(rsiLen) + " (conf=" + str.tostring(rsiConfirm) + ")" +
" | ADX: " + str.tostring(adxLen) + "(thr=" + str.tostring(adxThresh) + ")" +
" | VolMult=" + str.tostring(volMult) +
" | ATR TP=" + str.tostring(atrTP) +
" | Leverage=" + str.tostring(leverage) + "x" +
" | TradesToday=" + str.tostring(tradesToday)
info := label.new(bar_index, high, infoText, xloc=xloc.bar_index, yloc=yloc.abovebar,
style=label.style_label_left, size=size.small, color=color.new(color.blue, 70))
Nirvana True Duel전략 이름
열반의 진검승부 (영문: Nirvana True Duel)
컨셉과 철학
“열반의 진검승부”는 시장 소음은 무시하고, 확실할 때만 진입하는 전략입니다.
EMA 리본으로 추세 방향을 확인하고, 볼린저 밴드 수축/확장으로 변동성 돌파를 포착하며, OBV로 거래량 확인을 통해 가짜 돌파를 필터링합니다.
전략 로직
매수 조건 (롱)
20EMA > 50EMA (상승 추세)
밴드폭 수축 후 확장 시작
종가가 상단 밴드 돌파
OBV 상승 흐름 유지
매도 조건 (숏)
20EMA < 50EMA (하락 추세)
밴드폭 수축 후 확장 시작
종가가 하단 밴드 이탈
OBV 하락 흐름 유지
진입·청산
손절: ATR × 1.5 배수
익절: 손절폭의 1.5~2배에서 부분 청산
시간 청산: 설정한 최대 보유 봉수 초과 시 강제 청산
장점
✅ 추세·변동성·거래량 3중 필터 → 노이즈 최소화
✅ 백테스트·알람 지원 → 기계적 매매 가능
✅ 5분/15분 차트에 적합 → 단타/스윙 트레이딩 활용 가능
주의점
⚠ 횡보장에서는 신호가 적거나 실패 가능
⚠ 수수료·슬리피지 고려 필요
📜 Nirvana True Duel — Strategy Description (English)
Name:
Nirvana True Duel (a.k.a. Nirvana Cross)
Concept & Philosophy
The “Nirvana True Duel” strategy focuses on trading only meaningful breakouts and avoiding unnecessary noise.
Nirvana: A calm, patient state — waiting for the right opportunity without emotional trading.
True Duel: When the signal appears, enter decisively and let the market reveal the outcome.
In short: “Ignore market noise, trade only high-probability breakouts.”
🧩 Strategy Components
Trend Filter (EMA Ribbon): Stay aligned with the main market trend.
Volatility Squeeze (Bollinger Band): Detect volatility contraction & expansion to catch explosive moves early.
Volume Confirmation (OBV): Filter out false breakouts by confirming with volume flow.
⚔️ Entry & Exit Conditions
Long Setup:
20 EMA > 50 EMA (uptrend)
BB width breaks out from recent squeeze
Close > Upper Bollinger Band
OBV shows positive flow
Short Setup:
20 EMA < 50 EMA (downtrend)
BB width breaks out from recent squeeze
Close < Lower Bollinger Band
OBV shows negative flow
Risk Management:
Stop Loss: ATR × 1.5 below/above entry
Take Profit: 1.5–2× stop distance, partial take-profit allowed
Time Stop: Automatically closes after max bars held (e.g. 8h on 5m chart)
✅ Strengths
Triple Filtering: Trend + Volatility + Volume → fewer false signals
Mechanical & Backtestable: Ideal for objective trading & performance validation
Adaptable: Works well on Bitcoin, Nasdaq futures, and other high-volatility markets (5m/15m)
⚠️ Things to Note
Low signal frequency or higher failure rate in sideways/range markets
Commission & slippage should be factored in, especially on lower timeframes
ATR multiplier and R:R ratio should be optimized per asset
AK EMA 200 Trend Filter StrategyStrategy Description – EMA 200 Trend Filter
This strategy uses the 200-period Exponential Moving Average (EMA) as a trend filter:
Entry Rule (Long only):
A long position is opened when the price crosses above the EMA 200 and closes above it.
Exit Rule:
The long position is closed if price closes back below the EMA 200.
Optional Short Trades (disabled by default, can be enabled):
A short position is opened when the price crosses below EMA 200 and closes below it.
The short is exited when price closes back above EMA 200.
Risk Management:
Configurable Stop Loss (%) and Take Profit (%) from entry price.
If enabled, trades are automatically protected with SL/TP levels.
Visualization:
EMA 200 is plotted in orange on the chart.
Green arrows mark long entries, red arrows mark exits.
✅ Use cases:
Works best on higher timeframes (1H, 4H, Daily) as a trend-following filter.
You can combine with additional indicators (RSI, MACD) to reduce false signals.
Always test in TradingView Strategy Tester before using in live trading.
DMI Toolbox StrategyThe Directional Movement Index (DMI) was originally developed by J. Welles Wilder Jr. in 1978. Wilder introduced the DMI along with the Average Directional Index (ADX) in his book, “New Concepts in Technical Trading Systems,” which became a foundational reference for technical analysis.
The indicator can offer a myriad of signals for building a trading strategy. In an effort to provide the user with a meaningful way to evaluate these signals, this DMI Toolbox Strategy offers the chance to back-test various combinations and permutations of DMI signals on long trades. By default it will open a long position on the +DI (upward movement) crossing above the -DI (downward movement). By default, It exits long positions when the ADX (trend strength) reverses.
Suggested Use
Try a wide variety of long entry and exit signals across many different timeframes to see what is most effective for the item you wish to trade. There is a table in the upper right corner that will give a quick view of which signal is dominant across 5 timeframes, based on your current settings. Adjust the pyramidding, slippage, and commission values to more closely match your situation.
Visual Helpers
The DMI indicator has been altered to include a smoothed version of the ADX, as well as a colored background to show which signal is dominant (+DI or -DI). Small up arrows call your attention to ADX crossovers that may indicate a significant threshold in trend strength.
Extremum Range MA Crossover Strategy1. Principle of Work & Strategy Logic ⚙️📈
Main idea: The strategy tries to catch the moment of a breakout from a price consolidation range (flat) and the start of a new trend. It combines two key elements:
Moving Average (MA) 📉: Acts as a dynamic support/resistance level and trend filter.
Range Extremes (Range High/Low) 🔺🔻: Define the borders of the recent price channel or consolidation.
The strategy does not attempt to catch absolute tops and bottoms. Instead, it enters an already formed move after the breakout, expecting continuation.
Type: Trend-following, momentum-based.
Timeframes: Works on different TFs (H1, H4, D), but best suited for H4 and higher, where breakouts are more meaningful.
2. Justification of Indicators & Settings ⚙️
A. Moving Average (MA) 📊
Why used: Core of the strategy. It smooths price fluctuations and helps define the trend. The price (via extremes) must cross the MA → signals a potential trend shift or strengthening.
Parameters:
maLength = 20: Default length (≈ one trading month, 20-21 days). Good balance between sensitivity & smoothing.
Lower TF → reduce (10–14).
Higher TF → increase (50).
maSource: Defines price source (default = Close). Alternatives (HL2, HLC3) → smoother, less noisy MA.
maType: Default = EMA (Exponential MA).
Why EMA? Faster reaction to recent price changes vs SMA → useful for breakout strategies.
Other options:
SMA 🟦 – classic, slowest.
WMA 🟨 – weights recent data stronger.
HMA 🟩 – near-zero lag, but “nervous,” more false signals.
DEMA/TEMA 🟧 – even faster & more sensitive than EMA.
VWMA 🔊 – volume-weighted.
ZLEMA ⏱ – reduced lag.
👉 Choice = tradeoff between speed of reaction & false signals.
B. Range Extremes (Previous High/Low) 📏
Why used: Define borders of recent trading range.
prevHigh = local resistance.
prevLow = local support.
Break of these levels on close = trigger.
Parameters:
lookbackPeriod = 5: Searches for highest high / lowest low of last 5 candles. Very recent range.
Higher value (10–20) → wider, stronger ranges but rarer signals.
3. Entry & Exit Rules 🎯
Long signals (BUY) 🟢📈
Condition (longCondition): Previous Low crosses MA from below upwards.
→ Price bounced from the bottom & strong enough to push range border above MA.
Execution: Auto-close short (if any) → open long.
Short signals (SELL) 🔴📉
Condition (shortCondition): Previous High crosses MA from above downwards.
→ Price rejected from the top, upper border failed above MA.
Execution: Auto-close long (if any) → open short.
Exit conditions 🚪
Exit Long (exitLongCondition): Close below prevLow.
→ Uptrend likely ended, range shifts down.
Exit Short (exitShortCondition): Close above prevHigh.
→ Downtrend likely ended, range shifts up.
⚠️ Important: Exit = only on candle close beyond extremes (not just wick).
4. Trading Settings ⚒️
overlay = true → indicators shown on chart.
initial_capital = 10000 💵.
default_qty_type = strategy.cash, default_qty_value = 100 → trades fixed $100 per order (not lots). Can switch to % of equity.
commission_type = strategy.commission.percent, commission_value = 0.1 → default broker fee = 0.1%. Adjust for your broker!
slippage = 3 → slippage = 3 ticks. Adjust to asset liquidity.
currency = USD.
margin_long = 100, margin_short = 100 → no leverage (100% margin).
5. Visualization on Chart 📊
The strategy draws 3 lines:
🔵 MA line (thickness 2).
🔴 Previous High (last N candles).
🟢 Previous Low (last N candles).
Also: entry/exit arrows & equity curve shown in backtest.
Disclaimer ⚠️📌
Risk Warning: This description & code are for educational purposes only. Not financial advice. Trading (Forex, Stocks, Crypto) carries high risk and may lead to full capital loss. You trade at your own risk.
Testing: Always backtest & demo test first. Past results ≠ future profits.
Responsibility: Author of this strategy & description is not responsible for your trading decisions or losses.
Options Straddle Strategy Backtester 140% APR for 2025This script provides the most convenient manual tool for backtesting a straddle stagy in options.
The straddle is when you buy a call and a put option at the same price and the expiration date. You profit when the price movement at expiry (8 am UTC) in either directions surpass the price of the premium paid. The price of opening this straddle on ETH is always 1.6% of the current ETH price including fees.
In my example I use ETH options, I am buying a straddle at 8:30 UTC every day with the next day expiration date. In the script it looks like I am opening a long position on ETH at 8:30 and then close it the next days. We need to use 1 minute chart, chart time set to UTC for exact results and deep back testing function to go back in time.
Once the system generates a trade report - we need to download it and go to the list of trades sections, there we do the following:
1) remove all long entry lines leaving only long exit lines that have all the information we need.
2) We add one column that calculates the cost of premium for every trade: Position size*1.6%=cost of premium with fees.
3)We add a second column copying all Net PNL in USDT changing negative amounts to positive - since it doesn't matter for us which direction the move was towards.
The results are quite impressive: If you were buying straddles during 2025 that is not ended yet you will get 69% return on investment (11K paid in premiums, 19K return, 8K net profit). 2024 and 2025 combined: 53% (29 K, 45 K, and 15 profits).
Moreover, since you have the date of the trade in the table you can filter the results further to figure out if trading on some days is less profitable. Interestingly trades from Sun to Mon given are not profitable at -15% and most profitable days are Mon to Tue - 103%, Friday to Sat - 102 %. So if we remove Sun to Monday trades we will be at 89% for the first 221 days of the year or 140% APR.
MuLegend's Break & Retest Strategy That worksThank you all for checking this out! This indicator works best on the 1 minute time frame for both MNQ & NQ. ES & MES it also can work too to help you be a sniper. Hopefully you will like it!!!
Trendline Breakout Strategy [KedArc Quant] Description
A single, rule-based system that builds two trendlines from confirmed swing pivots and trades their breakouts, with optional retest, trend-regime gates (EMA / HTF EMA), and ATR-based risk. All parts serve one decision flow: structure → breakout → gated entry → managed risk.
What it does (for traders)
Draws Up line (teal) through the last two Higher Lows and Down line (red) through the last two Lower Highs, then extends them forward.
Long when price breaks above red; Short when price breaks below teal.
Optional Retest entry: after a break, wait for a pullback toward the broken line within an ATR-scaled buffer.
Uses ATR stop and R-multiple target so risk is consistent across symbols/timeframes.
Labels HL1/HL2/LH1/LH2 so non-coders can verify which pivots built each line.
Why these components are combined
Pure breakout systems on trendlines suffer from three practical issues:
False breaks in chop → solved by trend-regime gates (EMA / HTF EMA) that only allow trades aligned with the prevailing trend.
Uneven volatility across markets/timeframes → solved by ATR-based stop/target, normalizing distance so R-multiples are comparable.
First break whipsaws near wedge apices → mitigated by the optional retest rule that demands a pullback/hold before entry.
These modules are not separate indicators with their own signals. They are support roles inside one method.
The pivot engine defines structure, the breakout detector defines signal, the regime gates decide if we’re allowed to take that signal, and the ATR module sizes risk.
Together they make the trendline breakout usable, testable, and explainable.
How it works (mechanism; each component explained)
1) Pivot engine (structure, non-repainting)
Swings are confirmed with ta.pivotlow/high(L, R). A pivot only exists after R bars (no look-ahead), so once plotted, the line built from those pivots will not repaint.
2) Trendline builder (geometry)
Teal line updates when two consecutive pivot lows satisfy HL2.price > HL1.price (and HL2 occurs after HL1).
Red line updates when two consecutive pivot highs satisfy LH2.price < LH1.price.
Lines are extended right and their current value is read every bar via line.get_price().
3) Breakout detector (signal)
On every bar, compute:
crossover(close, redLine) ⇒ Long breakout
crossunder(close, tealLine) ⇒ Short breakdown
4) Regime gates (trend filters, not separate signals)
EMA gate: allow longs only if close > EMA(len), shorts only if close < EMA(len).
HTF EMA gate (optional): same rule on a higher timeframe to avoid fighting the larger trend.
These do not create entries; they simply permit or block the breakout signal.
5) Retest module (optional confirmation)
After a breakout, record the line price. A valid retest occurs if price pulls back within an ATR-scaled buffer toward that broken line and then closes back in the breakout direction.
This reduces first-tick fakeouts.
6) Risk module (position exit)
Initial stop = ATR(len) × atrMult from entry.
Target = tpR × (ATR × atrMult) (e.g., 2R).
This keeps results consistent across instruments/timeframes.
Entries & exits
Long entry
Base: close breaks above red and passes EMA/HTF gates.
Retest (if enabled): after the break, price pulls back near the broken red line (within the ATR buffer) and holds; then enter.
Short entry
Mirror logic with teal (break below & gates), optionally with a retest.
Exit
strategy.exit places ATR stop & R-multiple target automatically.
Optional “flip”: close if the opposite base signal triggers.
How to use it (step-by-step)
Timeframe: 1–15m for intraday, 1–4h for swing.
Start defaults: Pivot L/R = 5, EMA len = 200, ATR len = 14, ATR mult = 2, TP = 2R, Retest = ON.
Tune sensitivity:
Faster lines (more trades): set L/R = 3–4.
Fewer counter-trend trades: enable HTF EMA (e.g., 60-min or Daily).
Visual audit: labels HL1/HL2 & LH1/LH2 show which pivots built each line—verify by eye.
Alerts: use Long breakout, Short breakdown, and Retest alerts to automate.
Originality (why it merits publication)
Trades the visualization: many “auto-trendline” tools only draw lines; this one turns them into testable, alertable rules.
Integrated design: each component has a defined role in the same pipeline—no unrelated indicators bolted together.
Transparent & non-repainting: pivot confirmation removes look-ahead; labels let non-coders understand the setup that produced each signal.
Notes & limitations
Lines update only after pivot confirmation; that lag is intentional to avoid repainting.
Breakouts near an apex can whipsaw; prefer Retest and/or HTF gate in choppy regimes.
Backtests are idealized; forward-test and size risk appropriately.
⚠️ Disclaimer
This script is provided for educational purposes only.
Past performance does not guarantee future results.
Trading involves risk, and users should exercise caution and use proper risk management when applying this strategy.
Enhanced TMA Strategy[BMM]This strategy combines multiple moving averages with pattern recognition and dynamic coloring to identify high-probability trades. It uses 3-line strike patterns, engulfing candles, and RSI-based trend analysis with proper risk management for consistent 75%+ win rates.
Ideal Settings by Timeframe
For clear signals strategy can be used with:
"The Arty" - The Moving Average Official Indicator
or
TMA Legacy - "The Arty"
5-Minute Charts:
MA Lengths: 21, 50, 100, 200
MA Type: EMA
Risk: 1%
Risk:Reward: 2:1
Enable RSI Filter: Yes
Sessions: London + NY only
15-Minute Charts:
MA Lengths: 21, 50, 89, 144
MA Type: SMMA
Risk: 1.5%
Risk:Reward: 2.5:1
Enable RSI Filter: Yes
Sessions: All major sessions
30-Minute Charts:
MA Lengths: 13, 34, 55, 89
MA Type: EMA
Risk: 2%
Risk:Reward: 3:1
Enable RSI Filter: No
Sessions: London + NY only
Key Features to Enable:
Dynamic line coloring
Trend fill
All pattern signals
Session backgrounds
Strategy alerts
Trade only during major session overlaps for best liquidity and volatility.
Cs Fenix Us30The price unbalances the Asia and Frankfurt range and if there is a structural change it highlights a possible entry with a stop and target level.
BSL/SSL Sweep + FVG Strategy Jobin (c) The New York ATM Model is a structured intraday strategy designed to capture algorithmic stop-hunts and reversals during the New York session open. It focuses on liquidity sweeps—either Buy-Side or Sell-Side—followed by a confirmation using Fair Value Gaps (FVGs).
RSI DCA StrategyThis strategy combines RSI oversold signals with a Dollar-Cost Averaging (DCA) buying approach.
Trigger:
When the RSI (Relative Strength Index) crosses below 30, the strategy marks an oversold condition.
DCA Entry:
Once triggered, the strategy executes up to three consecutive daily entries (1 per day), splitting the predefined capital equally (configurable by user).
Position Management:
Take Profit at a configurable % above the average entry price.
Stop Loss at a configurable % below the average entry price.
Exit Conditions:
The strategy automatically exits either on reaching Take Profit or Stop Loss.
Visualization:
RSI plotted with oversold line (30).
Take Profit and Stop Loss lines displayed after entry.
Performance Reporting:
Includes an optional monthly performance table for evaluating results by month.
Note:
This strategy is for testing RSI-based mean reversion with staggered entries. It is not financial advice and should be optimized and validated for each market or timeframe before practical use.
TQQQ – 200 SMA ±5% Entry / –3% Exit (since 2010) • Metrics by DE✅ In plain words:
You only buy TQQQ when it’s trading 5% above its 200-day SMA (a sign of strong uptrend momentum).
You stay long as long as the price holds above 3% below the 200-day SMA.
If price falls below that lower threshold, you exit to limit drawdown.
The strategy is designed to catch strong uptrends while cutting losses early.
AI+ Scalper Strategy [BuBigMoneyMazz]Based on the AI+ Scalper Strategy
A trend-following swing strategy that uses multi-factor confirmation (trend, momentum, volatility) to capture sustained moves. Works best in trending markets and avoids choppy conditions using ADX filter.
🎯 5-Minute Chart Settings (Scalping)
pine
// RISK MANAGEMENT
ATR Multiplier SL: 1.2
ATR Multiplier TP: 2.4
// STRATEGY OPTIONS
Use HTF Filter: ON
HTF Timeframe: 15
Latching Mode: OFF
// INDICATOR SETTINGS
ADX Length: 10
ATR Length: 10
HMA Length: 14
Momentum Mode: Stochastic RSI
// STOCH RSI
Stoch RSI Length: 10
%K Smoothing: 2
%D Smoothing: 2
5-Minute Trading Style:
Quick scalps (15-45 minute holds)
Tight stops for fast markets
More frequent signals
Best during high volatility sessions (market open/close)
📈 15-Minute Chart Settings (Day Trading)
pine
// RISK MANAGEMENT
ATR Multiplier SL: 1.5
ATR Multiplier TP: 3.0
// STRATEGY OPTIONS
Use HTF Filter: ON
HTF Timeframe: 60
Latching Mode: ON
// INDICATOR SETTINGS
ADX Length: 14
ATR Length: 14
HMA Length: 21
Momentum Mode: Fisher RSI
// STOCH RSI
Stoch RSI Length: 12
%K Smoothing: 3
%D Smoothing: 3
15-Minute Trading Style:
Swing trades (1-4 hour holds)
Better risk-reward ratio
Fewer, higher quality signals
Works throughout trading day
⚡ Best Trading Times:
5-min: Market open (9:30-11:30 ET) & close (3:00-4:00 ET)
15-min: All day, but best 10:00-3:00 ET
✅ Filter for High-Probability Trades:
Only trade when ADX > 20 (strong trend)
Wait for HTF confirmation (prevents false signals)
Avoid low volume periods (lunch time)
⛔ When to Avoid Trading:
ADX < 15 (choppy market)
Major news events
First/last 15 minutes of session
Pro Tip: Start with 15-minute settings for better consistency, then move to 5-minute once you're comfortable with the strategy's behavior.
Hilly's 0010110 Reversal Scalping Strategy - 5 Min CandlesKey Features and Rationale:
Timeframe: Restricted to 5-minute candles as requested.
Pattern Integration: Includes single (Hammer, Shooting Star, Doji), two (Engulfing, Harami), and three-plus (Morning Star, Evening Star) candlestick patterns, plus reversal patterns based on RSI extremes.
VWAP Cross: Incorporates bullish (price crosses above VWAP) and bearish (price crosses below VWAP) signals, enhanced by trend context.
Volume Analysis: Uses a volume spike threshold to filter noise, with a simple day-start volume comparison for financial environment context.
Financial Environment: Approximates the day's sentiment using early-hour volume compared to current volume, adjusted by trend.
Aggregation: Scores each condition (e.g., 1 for basic patterns, 2 for strong patterns like Engulfing, 3 for three-candle patterns) and decides based on weighted consensus, with trendStrength as a tunable threshold.
Risky Approach: Minimal filtering and a low trendStrength (default 0.5) allow frequent signals, aligning with your $100-to-$200 goal, but expect higher risk.
Suggested Inputs:
EMA Length: 10 (short enough for 5-minute sensitivity).
VWAP Lookback: 1 (uses current session VWAP).
Volume Threshold Multiplier: 1.2 (moderate spike requirement).
RSI Length: 14 (standard, adjustable to 7 for more sensitivity).
Trend Strength Threshold: 0.5 (balance between signals; lower to 0.4 for more trades, raise to 0.6 for fewer).
Hull Suite Strategy with Time Filter. it This script filter the initial false signal at the opening of market
ORB Breakout Strategy with reversalORB 1,5,15,30,60min with reversals, its my first strategy Im not 100% sure it works well. Im not a programmer nor a profitable trader.
Max stoploss in points sets maximum fixed stoploss
Stop offset sets additional points below/above signal bar
RR Ratio is pretty self explanatory, it sets target based on stoploss
American session is time when positions can be opened
ORB SessionIs basically almost the same but when the time runs it closes all positions\
ORB candle timeframe is the time which orb is measured
Enable reverse position enables reversing positions on stoploss of first position, stoploss of reverse position is based on max stoploss and target is set by RR times max stoploss
Im sharing this to share this with my friends, discuss some things and dont have to test it manually.
I made it all myself and with help of AI
Sorry for bad english
Structure Strategycreated to spot key area needed to take valid trades in most market conditions. use beside RSI MACD
Clear Signal Trading Strategy V5Clear Signal Trading Strategy - Description
This strategy uses a simple 0-5 point scoring system to identify high-probability trades. It combines trend following with momentum confirmation to generate clear BUY/SELL signals while filtering out market noise.
How it works: The strategy waits for EMA crossovers, then scores the setup based on trend alignment, momentum, RSI position, and volume. Only trades scoring above your chosen threshold are executed.
Recommended Settings by Market Type
For Beginners / Risk-Averse Traders:
Signal Sensitivity: Conservative
Volume Confirmation: ON
Risk Per Trade: 1-2%
Stop Loss Type: ATR
ATR Multiplier: 2.5
Risk:Reward Ratio: 2.0
For Trending Markets (Strong Directional Movement):
Signal Sensitivity: Balanced
Volume Confirmation: ON
Risk Per Trade: 2%
Stop Loss Type: ATR
ATR Multiplier: 2.0
Risk:Reward Ratio: 2.5-3.0
For Ranging/Choppy Markets:
Signal Sensitivity: Conservative
Volume Confirmation: ON
Risk Per Trade: 1%
Stop Loss Type: Percentage
Percentage Stop: 2%
Risk:Reward Ratio: 1.5
For Volatile Markets (Crypto/High Beta Stocks):
Signal Sensitivity: Conservative
Volume Confirmation: ON
Risk Per Trade: 1%
Stop Loss Type: ATR
ATR Multiplier: 3.0
Risk:Reward Ratio: 2.0
Best Practices
Timeframes:
15-minute to 1-hour for day trading
4-hour to daily for swing trading
Works best on liquid instruments with good volume
When to avoid trading:
When dashboard shows "HIGH" volatility above 4%
During major news events
When win rate drops below 40%
In markets with no clear trend (prolonged NEUTRAL state)
Success tips:
Start with Conservative mode until you see 10+ successful trades
Only increase to Balanced mode when win rate exceeds 55%
Never use Aggressive mode unless market shows strong trend for 5+ days
Always honor the stop loss - no exceptions
Take partial profits at first target if unsure
Hilega Milega v6 - Pure EMA/SMA (Nitesh Kumar) + Full BacktestHilega to milega
he Hilega Milega Strategy, inspired by the technique of Nitesh Kumar, is designed for intraday and swing traders who want structured entries and exits with clear demand–supply logic.
🔑 Core Features
Demand & Supply Zones – Automatically plots potential strong buying and selling zones for high-probability trades.
Trend Identification – Uses a blend of EMAs/SMA crossovers to identify bullish and bearish market bias.
Buy & Sell Signals – Generates real-time visual signals based on “Hilega Milega” rules for quick decision-making.
Risk Management – Suggested stop-loss levels are derived from recent demand–supply areas to minimize drawdowns.
Backtesting Enabled – Traders can test the performance across multiple assets (stocks, forex, crypto, commodities).
📊 How It Works
Buy Signal → When price action confirms a bullish zone with supporting trend filters.
Sell Signal → When price action confirms a bearish zone or reversal pattern.
Flat/Exit → Position closed when opposite signal triggers or demand–supply imbalance fades.
⚡ Best Use Cases
Intraday trading (5m, 15m, 1H charts).
Swing trading (4H, Daily charts).
Works across stocks, crypto, commodities, and forex.
⚠️ Disclaimer: This strategy is for educational purposes. Backtest thoroughly and apply proper risk management before live trading.
