3 SMA Crossover Signals - Improved SELL TimingSELL Logic Adjustment: SELL Signal Logic: Uses the ta.crossunder(sma2, sma3) condition to detect SMA 2 to below SMA 3 crossovers early. Added the condition that SMA 1 > SMA 2 > SMA 3 to ensure all SMAs are in descending order: SMA 1 (highest) → SMA 2 → SMA 3 (lowest). Change: Condition ta.crossunder(sma2, sma1) removed to speed up signal detection, as it slowed down SELL signals. BUY Signal: No change, keep using: SMA 2 cuts SMA 3 from bottom to top. Sequence SMA 1 < SMA 2 > SMA 3. Result: BUY Signal: A green arrow appears below the candle when a BUY condition is detected. SELL Signal: A red arrow appears faster above the candle when a SELL condition is detected. How to Use: Copy this code into the Pine Script Editor in TradingView. Save and add to your chart. Signal: BUY Signal (green arrow): Appears when the SMA crosses upwards. SELL Signal (red arrow): Appears faster when the SMA crosses downwards.
Циклический анализ
TLU2025//@version=5
strategy("RSI + MA + BB30 Strategy", overlay=true)
// === Cài đặt RSI ===
rsiLength = input(14, title="RSI Length")
rsiOverbought = input(80, title="RSI Overbought Level")
rsiOversold = input(25, title="RSI Oversold Level")
rsi = ta.rsi(close, rsiLength)
// === Cài đặt MA ===
maLength20 = input(20, title="MA20 Length")
maLength50 = input(50, title="MA50 Length")
ma20 = ta.sma(close, maLength20)
ma50 = ta.sma(close, maLength50)
// === Cài đặt Bollinger Bands (BB30) ===
bbLength = input(30, title="Bollinger Bands Length")
bbStdDev = input(2, title="BB Standard Deviation")
= ta.bb(close, bbLength, bbStdDev)
// === Điều kiện giao dịch ===
// Điều kiện Long
longCondition = (rsi < rsiOversold) and (ma20 > ma50) and (close < bbLower)
// Điều kiện Short
shortCondition = (rsi > rsiOverbought) and (ma20 < ma50) and (close > bbUpper)
// === Mở lệnh giao dịch ===
if (longCondition)
strategy.entry("Long", strategy.long)
if (shortCondition)
strategy.entry("Short", strategy.short)
// === Hiển thị chỉ báo trên biểu đồ ===
// Hiển thị MA
plot(ma20, color=color.blue, title="MA20")
plot(ma50, color=color.red, title="MA50")
// Hiển thị Bollinger Bands
plot(bbUpper, color=color.green, title="BB Upper")
plot(bbBasis, color=color.gray, title="BB Basis")
plot(bbLower, color=color.green, title="BB Lower")
// Hiển thị RSI và mức quan trọng
hline(rsiOverbought, "RSI Overbought", color=color.red, linestyle=hline.style_dashed)
hline(rsiOversold, "RSI Oversold", color=color.green, linestyle=hline.style_dashed)
plot(rsi, color=color.purple, title="RSI")
Economic RegimeThis indicator, "Economic Regime" , provides a comprehensive analysis of market conditions by combining multiple asset classes and financial metrics. It uses normalized scores and trend analysis to classify the current economic regime into one of four categories: Goldilocks, Reflation, Inflation, or Deflation. The classification is based on inputs like S&P 500 performance, bond yields, commodity prices, volatility indices, and sector ETFs. Additionally, it plots key financial spreads, including the yield spread (10Y-2Y) and credit spread (HYG-LQD), to offer deeper insights into liquidity and market sentiment. The background color dynamically reflects the identified economic regime, facilitating quick visual interpretation.
☼ MAH ☾ - High-Low Fractal SignalThis indicator works based on the market fractal and provides signals.
In a specific time interval that can be adjusted in the indicator settings window, the ceiling and floor of this range are determined, and whenever the price leaves this specified range, a buy or sell signal is issued according to the failure of each of these levels.
By looking at the situation, the trader can enter a position by observing all risk and capital management issues if he sees a suitable and powerful candle.
Note 1: To set the appropriate time frame, be sure to set the chart time to UTC+3:30, otherwise you must set the correct time frame in the indicator settings window and apply your time zone difference to it.
Note 2: The appropriate Time frame for this strategy is 5 and 15 minutes.
Note 3: It is better if the breakout candle is strong and has a small opposite shadow, and also if the candle is pulled back to the broken level and then a suitable candle is seen, the probability of this setup being successful increases.
I hope you find this indicator useful and please send me your feedback.
ZelosKapital Weekly/Monthly HLThe ZelosKapital Weekly/Monthly high low indicator is designed to display the weekly and monthly high and low levels directly on the price chart. It helps traders easily identify key support and resistance zones by marking the highest and lowest points of the current week and month. The indicator automatically updates these levels as the price moves, providing a clear visual reference for intraday trading strategies.
Ideal for both Day Trading and Swing Trading, this tool offers valuable insights into potential reversal points, breakout areas, and zones of consolidation. By monitoring these significant price levels, traders can make more informed decisions, timing their entries and exits with greater precision. Whether you're looking for short-term price action or longer-term trends, the weekly and monthly highs and lows serve as critical levels to guide your trades.
Liquidity Pool Price Range with Alerts (Clean)Monitor the upper and lower limits of your LP investments with this script.
Download and log in to Trading View on your mobile to get alerts when you fall out of range
EMA SHIFT & PARALLEL [n_dot]BINANCE:ETHUSDT.P
This strategy was developed for CRYPTO FUTURES, (the settings for ETHUSDT.P) . I aimed for the strategy to function in a live environment, so I focused on making its operation realistic:
When determining the position, only 80% (adjustable) of the available cash is invested to reduce the risk of position liquidation.
I account for a 0.05% commission, typical on the futures market, for each entry and exit.
Concept:
I modified a simple, well-known method: the crossover of two exponential moving averages (FAST, SLOW) generates the entry and exit signals.
I enhanced the base idea as follows:
For the fast EMA, I incorporated a multiplier (offset) to filter out market noise and focus only on strong signals.
I use different EMAs for long and short entry points; both have their own FAST and SLOW EMAs and their own offset. For longs, the FAST EMA is adjusted downward (<1), while for shorts, it is adjusted upward (>1). Consequently, the signal is generated when the modified FAST EMA crosses the SLOW EMA.
Risk Management:
The position includes the following components:
Separate stop-losses for long and short positions.
Separate trailers for long and short positions.
The strategy operates so that the entry point is determined by the EMA crossover, while the exit is governed only by the Stop Loss or Trailer. Optionally, it can be set to close the position at the EMA recrossing ("Close at Signal").
Trailer Operation:
An entry percentage and offset are defined. The trailer activates when the price surpasses the entry price, calculated automatically by the system.
The trailer closes the position when the price drops by the offset percentage from the highest reached price.
Example for trailer:
Purchase Price = 100
Trailer Enter = 5% → Activation Price = 105 (triggers trailer if market price crosses it).
Trailer Offset = 2%
If the price rises to 110, the exit price becomes 107.8.
If the price goes to 120, the exit price becomes 117.6.
If the price falls below 117.6, the trailer closes the position.
Settings:
Source: Determines the market price reference.
End Close: Closes positions at the end of the simulation to avoid "shadow positions" and provide an objective result.
Lot proportional to free cash (%): Only a portion of free cash is invested to meet margin requirements.
Plot Short, Plot Long: Simplifies displayed information by toggling indicator lines on/off.
Long Position (toggleable):
EMA Fast ws: Window size for FAST EMA.
EMA Slow ws: Window size for SLOW EMA.
EMA Fast down shift: Adjustment factor for FAST EMA.
Stop Loss long (%): Percent drop to close the position.
Trailer enter (%): Percent above the purchase price to activate the trailer.
Trailer offset (%): Percent drop to close the position.
Short Position (toggleable):
EMA Fast ws: Window size for FAST EMA.
EMA Slow ws: Window size for SLOW EMA.
EMA Fast up shift: Adjustment factor for FAST EMA.
Stop Loss short (%): Percent rise to close the position.
Trailer enter (%): Percent below the purchase price to activate the trailer.
Trailer offset (%): Percent rise to close the position.
Operational Framework:
If in a long position and a short EMA crossover occurs, the strategy closes the long and opens a short (flip).
If in a short position and a long EMA crossover occurs, the strategy closes the short and opens a long (flip).
A position can close in three ways:
Stop Loss
Trailer
Signal Recrossing
If none are active, the position remains open until the end of the simulation.
Observations:
Shifts significantly deviating from 1 increase overfitting risk. Recommended ranges: 0.96–0.99 (long) and 1.01–1.05 (short).
The strategy's advantage lies in risk management, crucial in leveraged futures markets. It operates with relatively low DrawDown.
Recommendations:
Bullish Market: Higher entry threshold (e.g., 6%) and larger offset (e.g., 3%).
Volatile/Sideways Market: Tighter parameters (e.g., 3%, 1%).
The method is stable, and minor parameter adjustments do not significantly impact results, helping assess overfitting: if small changes lead to drastic differences, the strategy is over-optimized.
EMA Settings: Adjust FAST and SLOW EMAs based on the asset's volatility and cyclicality.
On the crypto market, especially in the Futures market, short time periods (1–15 minutes) often show significant noise, making patterns/repetitions hard to identify. I recommend setting the interval to at least 1 hour.
I hope this contributes to your success!
Optimized Smart Entry/Exit StrategyOptimized Smart Entry/Exit StrategyOptimized Smart Entry/Exit StrategyOptimized Smart Entry/Exit StrategyOptimized Smart Entry/Exit StrategyOptimized Smart Entry/Exit StrategyOptimized Smart Entry/Exit StrategyOptimized Smart Entry/Exit StrategyOptimized Smart Entry/Exit StrategyOptimized Smart Entry/Exit Strategy
BAML Strategy (SPXL) - testbacktest of strategy based on BAML credit spread
330d ema
180 days horizon to define local top/highs
all major parameters could be adjusted
NOT finalized and polish - could contain some errors
Simulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2x
Simulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2xSimulação de Compra Diária com Alavancagem 2x
SMA Crossover Strategy with VWAPSMA Crossover Strategy with VWAP swing trade for 1hr chart and intraday for 1min chart
Savas Cum Inverse Fisher Transform on RSI and CCIAl ve sat sinyallerini belli oranda paylaşan ve trendi takip etmenize imkan sunan bir Pine Editör seknesidir
ZelosKapital Market BehaviourThe ZelosKapital Market Behaviour Indicator is a powerful tool designed to visually highlight market structure periods directly on your trading chart. This indicator identifies and labels the four key price action phases: Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL). Understanding these phases is critical for traders aiming to follow the trend or anticipate potential reversals.
MVRV Z-Score (Topos e Fundos)No MVRV Z-Score, a linha roxa (que representa o valor do indicador) atingir ou ultrapassar a faixa vermelha geralmente indica que o ativo está em uma zona de sobrevalorização. Isso significa que o mercado pode estar próximo de um topo, e historicamente, esses momentos tendem a ser seguidos por correções de preço.
O que acontece quando a linha roxa atinge a faixa vermelha?
Zona Vermelha (Topo):
Quando a linha roxa entra na faixa vermelha, o ativo está sendo negociado muito acima do seu valor realizado (Realized Value).
Isso sugere que muitos investidores estão com lucros não realizados significativos, o que pode levar a vendas em massa e, consequentemente, a uma correção de preço.
Sinal para traders e investidores:
Para traders, pode ser um sinal de que o preço está próximo de um topo e que pode ser um bom momento para realizar lucros.
Para investidores de longo prazo, pode ser um alerta para evitar compras nesse momento, aguardando uma possível correção.
E se a linha roxa não atingir a faixa vermelha?
Se a linha roxa não atingir a faixa vermelha, o ativo pode ainda ter espaço para valorização antes de atingir um topo. No entanto, é importante observar outros fatores do mercado, como volume, sentimento e contexto macroeconômico.
CMS-Inspired SMC Strategy with Liquidity and FVG//@version=5
indicator("CMS-Inspired SMC Strategy with Liquidity and FVG", overlay=true)
// === إعدادات المستخدم ===
capital = input.float(1000, title="رأس المال ($)", step=10) // رأس المال الكلي
risk_percent = input.float(1, title="نسبة المخاطرة (%)", step=0.1) // نسبة المخاطرة
max_trades = input.int(2, title="عدد الصفقات اليومية", step=1) // الحد الأقصى للصفقات اليومية
session_start = input.time(timestamp("0000-01-01 08:00 +0000"), title="بداية الجلسة") // جلسة لندن
session_end = input.time(timestamp("0000-01-01 16:00 +0000"), title="نهاية الجلسة") // جلسة لندن
news_time = input.time(timestamp("0000-01-01 09:00 +0000"), title="وقت الأخبار المهمة") // الوقت المتوقع للأخبار
// === أدوات إضافية ===
session_active = (time >= session_start and time <= session_end) // الجلسة الزمنية
atr = ta.atr(14) // مؤشر ATR
// === تحديد مناطق السيولة ===
highest_liq = ta.highest(high, 20) // أعلى نقطة في الـ 20 فترة
lowest_liq = ta.lowest(low, 20) // أدنى نقطة في الـ 20 فترة
// === فجوات القيمة العادلة (FVG) ===
fvg_condition = close > high and close < high // عندما يكون هناك فجوة بين الإغلاق والارتفاع
// === إشارات التداول ===
// كسر الهيكل (BOS)
high_break = ta.highest(high, 5) < close
low_break = ta.lowest(low, 5) > close
// مناطق Order Block
bullish_ob = close < open // إشارات الشراء بناءً على الإغلاق
bearish_ob = close > open // إشارات البيع بناءً على الإغلاق
// إشارات الشراء والبيع بناءً على جميع الشروط
long_signal = session_active and high_break and bullish_ob and fvg_condition and not (time >= news_time and time <= news_time + 3600000) // تجنب الأخبار
short_signal = session_active and low_break and bearish_ob and fvg_condition and not (time >= news_time and time <= news_time + 3600000) // تجنب الأخبار
// === إدارة رأس المال ===
capital_per_trade = (capital * risk_percent / 100) // نسبة رأس المال في الصفقة
lot_size = capital_per_trade / (atr * 1.5) // حجم اللوت بناءً على الـ ATR ووقف الخسارة
stop_loss = atr * 1.5 // وقف الخسارة بناءً على ATR
take_profit = stop_loss * 2 // الهدف (نسبة مخاطرة/عائد 1:2)
// === رسم الإشارات ===
var trade_count = 0 // عداد الصفقات اليومية
if session_active
if trade_count < max_trades
if long_signal
label.new(bar_index, high, "شراء", color=color.green, style=label.style_label_down)
trade_count += 1
if short_signal
label.new(bar_index, low, "بيع", color=color.red, style=label.style_label_up)
trade_count += 1
// === تنبيه إشارات ===
if long_signal or short_signal
alert("إشارة جديدة: " + (long_signal ? "شراء" : "بيع"), alert.freq_once_per_bar)
Regime Classifier Oscillator (AiBitcoinTrend)The Regime Classifier Oscillator (AiBitcoinTrend) is an advanced tool for understanding market structure and detecting dynamic price regimes. By combining filtered price trends, clustering algorithms, and an adaptive oscillator, it provides traders with detailed insights into market phases, including accumulation, distribution, advancement, and decline.
This innovative tool simplifies market regime classification, enabling traders to align their strategies with evolving market conditions effectively.
👽 What is a Regime Classifier, and Why is it Useful?
A Regime Classifier is a concept in financial analysis that identifies distinct market conditions or "regimes" based on price behavior and volatility. These regimes often correspond to specific phases of the market, such as trends, consolidations, or periods of high or low volatility. By classifying these regimes, traders and analysts can better understand the underlying market dynamics, allowing them to adapt their strategies to suit prevailing conditions.
👽 Common Uses in Finance
Risk Management: Identifying high-volatility regimes helps traders adjust position sizes or hedge risks.
Strategy Optimization: Traders tailor their approaches—trend-following strategies in trending regimes, mean-reversion strategies in consolidations.
Forecasting: Understanding the current regime aids in predicting potential transitions, such as a shift from accumulation to an upward breakout.
Portfolio Allocation: Investors allocate assets differently based on market regimes, such as increasing cash positions in high-volatility environments.
👽 Why It’s Important
Markets behave differently under varying conditions. A regime classifier provides a structured way to analyze these changes, offering a systematic approach to decision-making. This improves both accuracy and confidence in navigating diverse market scenarios.
👽 How We Implemented the Regime Classifier in This Indicator
The Regime Classifier Oscillator takes the foundational concept of market regime classification and enhances it with advanced computational techniques, making it highly adaptive.
👾 Median Filtering: We smooth price data using a custom median filter to identify significant trends while eliminating noise. This establishes a baseline for price movement analysis.
👾 Clustering Model: Using clustering techniques, the indicator classifies volatility and price trends into distinct regimes:
Advance: Strong upward trends with low volatility.
Decline: Downward trends marked by high volatility.
Accumulation: Consolidation phases with subdued volatility.
Distribution: Topping or bottoming patterns with elevated volatility.
This classification leverages historical price data to refine cluster boundaries dynamically, ensuring adaptive and accurate detection of market states.
Volatility Classification: Price volatility is analyzed through rolling windows, separating data into high and low volatility clusters using distance-based assignments.
Price Trends: The interaction of price levels with the filtered trendline and volatility clusters determines whether the market is advancing, declining, accumulating, or distributing.
👽 Dynamic Cycle Oscillator (DCO):
Captures cyclic behavior and overlays it with smoothed oscillations, providing real-time feedback on price momentum and potential reversals.
Regime Visualization:
Regimes are displayed with intuitive labels and background colors, offering clear, actionable insights directly on the chart.
👽 Why This Implementation Stands Out
Dynamic and Adaptive: The clustering and refit mechanisms adapt to changing market conditions, ensuring relevance across different asset classes and timeframes.
Comprehensive Insights: By combining price trends, volatility, and cyclic behaviors, the indicator provides a holistic view of the market.
This implementation bridges the gap between theoretical regime classification and practical trading needs, making it a powerful tool for both novice and experienced traders.
👽 Applications
👾 Regime-Based Trading Strategies
Traders can use the regime classifications to adapt their strategies effectively:
Advance & Accumulation: Favorable for entering or holding long positions.
Decline & Distribution: Opportunities for short positions or risk management.
👾 Oscillator Insights for Trend Analysis
Overbought/oversold conditions: Early warning of potential reversals.
Dynamic trends: Highlights the strength of price momentum.
👽 Indicator Settings
👾 Filter and Classification Settings
Filter Window Size: Controls trend detection sensitivity.
ATR Lookback: Adjusts the threshold for regime classification.
Clustering Window & Refit Interval: Fine-tunes regime accuracy.
👾 Oscillator Settings
Dynamic Cycle Oscillator Lookback: Defines the sensitivity of cycle detection.
Smoothing Factor: Balances responsiveness and stability.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
خطوط عمودی تایمفریم//@version=5
indicator("خطوط عمودی تایمفریم", overlay=true)
var line_color_daily = color.new(color.blue, 50) // رنگ خطوط روزانه
var line_color_weekly = color.new(color.green, 50) // رنگ خطوط هفتگی
var line_color_monthly = color.new(color.red, 50) // رنگ خطوط ماهانه
// بررسی تایمفریم
is_daily = timeframe.isintraday and timeframe.multiplier == 5 or timeframe.multiplier == 30
is_weekly = timeframe.isintraday and timeframe.multiplier == 60
is_monthly = timeframe.isintraday and timeframe.multiplier == 240
// رسم خطوط روزانه
if is_daily and ta.change(time("D")) != 0
line.new(x1=bar_index, y1=high, x2=bar_index, y2=low, color=line_color_daily, width=1)
// رسم خطوط هفتگی
if is_weekly and ta.change(time("W")) != 0
line.new(x1=bar_index, y1=high, x2=bar_index, y2=low, color=line_color_weekly, width=2)
// رسم خطوط ماهانه
if is_monthly and ta.change(time("M")) != 0
line.new(x1=bar_index, y1=high, x2=bar_index, y2=low, color=line_color_monthly, width=3)
Cameron's 1m Swing Structure IndicatorThis is based off of Pips2Profit's www.youtube.com
I am no programmer, took the CC and had ChatGPT do the coding. I found it amazing, thought I would share.
For educational use only. :P
